Emerging Research in Artificial Intelligence and Computational Intelligence

Optimal water distribution in irrigation district (ID) is an important method and countermeasure for reasonably restraining the water requirements, effectively increasing the water supply, and actively protecting the ecological environment etc. According to the genetic theory, it is essential to discarding the traditional binary system coding for solving water distribution. Considering GA sinking into the partial solution easily, a free search algorithm is introduced. It extend the search space for algorithms, enhancing the quality of gene coding, adjusting the discharge of canal , making every canal closed at the same time, decreasing the discarding water of canal, reducing the time of manual work. It has excellent theoretical and realistic effect on distributing water.

Evaluation measure of web site is an important tool for web mining and information release. Fatherly, maintainability is a notable merit among the evaluation. But, the measure which is able to stably attain standardized maintainability is absent in present. In fact, the merit is just implied in the search engines. When the spiders of search engine periodically visits web site to find new information and information update, both updating history and interval of web site page, which reflect the maintainability of web site, are recorded into search engine cache. By comparing latest web caches with current web pages, maintainability degree of web site can be calculated, and then maintainability of a web site is obtained too. The paper presents a search engine based maintainability evaluation measure of web site. Some experiments aim to test the measure illustrate the evaluation result and performance are credible and valuable.

Modeling plant growth is important to further study on the plant development process, especially for digital agriculture field. Virtual plant model can help to observe the plant growth process and discover some recondite rules, which could be constructed based on large numbers of experimental data during the plant development. The growth model can be obtained after dealing with experimental data, while the changes including topological structure and organ morphology during the plant growth could be described using virtual technology. Then the virtual plant development model can be expressed with the information fusion and reconstruction method. The experimental results showed that the presented model was feasible and effective on simulating plant growth on computer, which also greatly demonstrated its valuable evidences in predicting the plant growth rules under different environmental conditions.

Because the credit industry has a lot of bad debt problems, credit assessment has become a very important topic in financial institutions. Recent studies have shown that many algorithms in the fields of machine learning and artificial intelligence are competitive to statistical methods for credit assessment. Random forests, one of the most popular ensemble learning techniques, is introduced to the credit assessment problem in this paper. An experimental evaluation of different methods is carried out on the public dataset. The experimental results indicate that the random forests method improves the performance obviously.

In the dynamic decoupling fuzzy control system, if singular or rectangle matrices are encountered in the state equation, the only way is to consider the decoupling control over partial states of the system. This paper presents a new conclusion with fewer parameters by virtue of generalized inverse matrix and realized decoupling fuzzy control over the system with multiple variables, which demonstrates good control effect.

It has become clear that the traditional Poisson model of data network traffic is insufficient for dimensioning and analyzing the performance of real-life networks.Fractal models are more appropriate for simulating the self-similar behavior of data traffic.To understand self-similarity on physical grounds in a realistic network environment is important when developing efficient and integrated network frameworks within which end-to-end QoS guarantees are fully supported. OPNET features the Raw Packet Generator (RPG) which contains several implementations of self-similar sources. This paper uses fractal analysis to characterize increasingly bursty industrial control network traffic.The goal is to develop a better understanding of the fractal nature of network traffic, which in turn will lead to more efficiency and better quality of services on industrial control network traffic. We present a comparison between the different RPG models in OPNET Modeler.

Routing on the surface of a sphere is a very interesting new topic. This paper presents a new discrete particle swarm algorithm, ENS-DPSO, to solve the travelling salesman problems on a spherical surface. Differently from previous approaches, ENS-DPSO redefines the path-relinking as velocity and position updating operators, and the hybridization with expanding neighborhood search (ENS) strategy is employed to improve the exploitation capabilities of the method. After visual implementation of the experimental tool in Java with 3D APIs, the effectiveness and efficiency of the proposed method are tested on various instances of random points with promising results.

An algorithm of object-oriented program comprehension and description is proposed in this paper. This methodology represents the program structure in visual form. Firstly, the code is analyzed. With the code analysis of compiling technique, knowledge related to the program structure can be concluded. Secondly, the knowledge is conducted for abstraction and inference. Lastly, software and algorithmic model are reconstructed. Program comprehension penetrates into algorithm structure analysis under function-level.

Based on the principle of simulated annealing algorithm and applying annealing model, this paper systematically analyzed the extended applied algorithm and its examples of Nondeterministic polynomial (NP) decision problem, evaluated the setting of the important parameters and the processes, and realized the global optimum solution for NP application.The results of the experiments tested under .NET confirm that SA algorithm can jump out from the trap of local optimum and find global optimum solution for combinatorial optimization. Meanwhile, optimization algorithm is competitive comparing with other local searching algorithm.

Premature convergence and low converging speed are the distinct weaknesses of the genetic algorithms. a new algorithm called ECCA (ecological competition coevolutionary algorithm) is proposed for multiobjective optimization problems, in which the competition is considered to be in important position. In the algorithms, each objective corresponds to a population. At each generation, these populations compete among themselves. An ecological population density competition equation is used for reference to describe the relation between multiple objectives and to direct the adjustment over the relation at individual and population levels. The proposed approach store the Pareto optimal point obtained along the evolutionary process into external set, enforcing a more uniform distribution of such vectors along the Pareto front. The experiment results show the high efficiency of the improved Genetic Algorithms based on this model in solving premature convergence and accelerating the convergence.

The Kerberos protocol has promoted the development of new techniques to support various kinds of distributed applications. However, the secret-key management is security core in the whole system. Using symmetric encryption algorithm Rijndael of AES (Advanced Encryption Standard), all secret-keys of the client were encrypted by the secret-key of the authentication server and stored in the database. The secret-key of the authentication server was protected by distributing its shares to the router, Ticket-granting Server (TGS) and the Web server. The authentication server did not store its secret-key in system, when the system needed this secret-key, the authentication server could synthesize it by distributed shares. Security analysis shows that this secret-key management has fault-tolerant and no-information leakage; it also defends collusive attack and cracking the secret-key attack.

At present, the watershed hydrology model in semiarid and semi-humid areas do less work whether in foreign or in our country, therefore studying on the hydrology simulation in semiarid and semi-humid area is very important. This paper focuses on the principle and the structure of Shuangchao hydrological model, which was applied to simulate 5 historical floods of Zhangfeng Reservoir in Shanxi, and the results show the model is very suitable for this basin. Finally, the author puts forward some suggestions for future improvement of Shuangchao hydrological model in the future.

Before the electric power equipments are in operation,the maintenance department of power system need to conduct a withstand test to them. The withstand test simulation system is based on the basic principle of withstand test. Through the operators’ visual build to the power modules,the software can simulate digitally and calculate automatically for the test.So,researchers were able to manage the withstand test visually. It maks them to manage the work of withstand test more effectively.

A depth-first search (DFS) algorithm requires much less memory than breadth-first search (BFS) one. However, the former doesn’t guarantee to find the shortest path in the VLSI (Very Large Integration Circuits) wire routing when the latter does. To remedy the shortcoming of DFS, this paper attempts to improve the DFS algorithm for VLSI wire routing by introducing a method of pruning and iterative deepening. This method guarantees to find all of the existing shortest paths with the same length in the VLSI wire routing to provide the wire routing designers more options for optimal designs.

The data of our private car ownership in recent years has been analyzed, a strong trend of exponential growth has been found in this data, and the GM (1,1) model for this data has been established in this paper.The result is given to show that the precision of the model is high, and is used to forecast the future of the private car ownership.

In this paper, three PFCFsare selected and whether they satisfies the rationality properties such as F

α

, F

β

, F

γ

, WFCA is investigated, then the satisfaction of preference-based fuzzy choice functions is obtained as a consequence.

It is the key for improving the control and management of smart grid to know how to make multiple utilization of internet of things technologies better. In this paper, the relationship between internet of things and smart grid is analyzed. This paper shows that smart grid is based on internet of things. The internet of things technologies needs of smart grid are put forward. Finally, detailed application process and the corresponding technologies are proposed aiming at the transmission link of smart grid.

In order to assess the flicker caused by electric arc furnace, the simulation method to assess flicker and its application in electric arc furnace power system is studied. Firstly, based on the Flicker Meter functional and design specifications recommended by IEC, an IEC Flicker Meter is designed concretely; Secondly, an IEC Flicker Meter model is established in SIMULINK, and a special M file which can be used to calculate the short term flicker sensation indicator (

P

st

) is compiled, according to the IEC criterion, the Flicker Meter model is tested; Finally, assess of the flicker caused by an actual electric arc furnace is achieved, the instantaneous flicker sensation

S(t)

in the point of common coupling is gained. The results show that application of simulation method to assess the flicker caused by electric arc furnace is an effective way.

The voltage transformer of the power system is a device which converts the high voltage of the primary side into the low voltage required by secondary device, and the primary side connects to the primary system, the secondary side connects to the measuring instrument, relay protection equipment and so on. This paper Introduces a kind of air switch with the ability of preventing the anti-charging occurring in the voltage transformer from secondary side of the to primary side in the ordinary air switch used in the practice. It will automatically handle the anti-charging phenomenon and protect the safety of the staff and equipments more effectively.

Steel-core belt is the large transport device in coal mine and other departments, the longitudinal rip of steel-core belt will bring great losses to production and safety, this article proposed one kind of online monitoring method based on distance measuring sensor and 8051 MCU. This method is to use distance measuring sensor to real-time monitor the width of the steel-core belt, and through compiling 8051 MCU process, realize online monitoring for the longitudinal rip of steel-core belt.

In order to avoid the traffic accidents caused by drivers, unmanned ground vehicles are expected to run on the road, so correct and safe driving behaviors are most important. This paper aims to give a new way of perception based on information processing for control system of intelligent vehicles, and focuses on the present overtaking ability of intelligent vehicles, meanwhile implies the ability of recognizing traffic environment. First we built intelligent driving behavior models with construction perception and pattern recognition on prototype matching; second, based on “Future Challenge” contest we investigated the features of velocity and latitudinal distance of intelligent driving. Our results describe that the intelligent vehicle does have the basic ability of cognizance, and it can make correct reactions corresponding to the driving environment, but its intelligence still needs improving.

In this study we examine the level at which inhibition of return (IOR) affects the processing of visual spatial stimuli. Experiment examined the effect of IOR on spatial Stroop interference. This results shows IOR could reverse the Stroop effects. We suggest that when attention is drawn away from a location, there is temporary inhibitory tagging of stimuli that are presented there. This tagging extends to the semantic and response-relevant properties of stimuli, helping to bias attention away from old and towards new events.

Chinese medicinal herbs, acupuncture, and patterns are important components in traditional Chinese medicine. In this paper, focused on facial nerve paralysis, we proposed an algorithm named two dimensions data slicing to mine rules of Chinese medicinal herbs, acupuncture, and patterns. The process of mining was done in two dimensions. The one-dimension analyzes the frequencies of Chinese medicinal herbs, acupoints, and patterns. The two-dimension analyzes the frequencies of co-existed keyword pairs. By examining the results of these two dimensions, although some noises existed, most regular knowledge of treating this disease is mined out. This algorithm might be useful in mining rules in the literature of traditional Chinese medicine.

This paper proposes a frequent closed itemsets mining algorithm based on FP-tree and COFI-tree. This algorithm adopts a relatively small independent tree called COFI-tree. COFI-Tree doesn’t need to construct conditional FP-Tree recursively and there is only one COFI-Tree in memory at a time, therefore this new mining algorithm reduces memory usage. Experiment shows that the new approach outperforms similar state-of-the-art algorithms when mining extremely large datasets in terms of execution time.

BOMO algorithm constructs conditional FP-Tree recursively so that it requires more memory and CPU resources. To solve this problem, an algorithm for mining N-most interesting itemsets based on COFI-Tree is presented. This algorithm adopts COFI-Tree. COFI-Tree doesn’t need to construct conditional FP-Tree recursively and there is only one COFI-Tree in memory at a time. Experiment shows that (1) the new algorithm based on COFI-tree performs faster than current best algorithm BOMO;(2) the algorithm has good performance for large data set, especially it shows the best when for k value is smaller than 4.

Kernel fuzzy C-means (KFCM) clustering Algorithm is one of the most widely used methods in data mining, but this algorithm still exists some defects, such as the local optima and sensitivity to initialization and noise data. Artificial bee colony (ABC) is a very simple, robust, stochastic global optimization tool which is used in many optimization problems. In this paper, an improved KFCM algorithm based on ABC (ABC-KFCM) is proposed. It can integrate advantages of KFCM and ABC algorithm. According to the test, compared with the FCM and KFCM clustering algorithm, the proposed algorithm improves the optimization ability of the algorithm, the number of iterations is fewer, and the convergence speed is faster. In addition, there is also a large improved in the clustering result.

Similarity measurement is the bases of clustering analysis. Current clustering algorithms mostly based on density and distance measurement, but these concepts become increasingly difficult to fit more and more complex data set and analysis works. SNN similarity, however, show more flexible ability to deal with different density, shape and multi-dimensions data process problems .In this paper we review mostly popular SNN based clustering method, give the definition of Local Agglomerative Characteristics during the procedure of the clustering, proposed a new clustering algorithm, that is, Improved Clustering algorithm based on Local Agglomerative Characteristics. Apply this clustering algorithm on experimental data set, the result show that it can work well on different type’s data objects, can find nature distribute clusters in target data set, can improve the quality of data clustering.

Cluster Analysis which plays an important role in Data Mining, is widely used. It has important value both in theory and application. Considering the stability of the Genetic Algorithm and the local searching capability of Particle Swarm Optimization in clustering, those two algorithms are combined. Particle Swarm Optimization operators are implemented after the crossover and mutation operators, and GA-PSO clustering algorithm is put forwarded. Simulation results are given to illustrate the stability and convergence of the proposed method. GA-PSO is proved to be easier to carry out, faster to converge and more stable than other methods.

In this paper, we present a model of a GEP-based test clustering research on counter propagation networks. The idea of the model is that it optimize the link weight vector by using the advantage of the GEP(Gene Expression Programming, GEP) in combinatorial optimization. We investigate how the value of weight in the network affect the performance of the text clustering by comparing it to a based on genetic algorithm and SOM network and the method of the traditional CPN(Counter Propagation Networks, CPN) .Furthermore, we improve and optimize the weight in the CPN network by the method of GEP, thus raise the quality of the text clustering in the network. Finally, in this paper, we demonstrated the validity and superiority of the presented model.

In the context of Prediction System of University Major Setting Research Project, for the machinery manufacturing industry, we study for the association rules model of the relation between majors and positions .We design a set of methods to discover this model, achieve this model with existing data and analyze the practical significance of this model. This association rules model provides a useful exploration to university major settings and employment trend analysis.

Complicated index system and unscientific index weights setting can’t adapt the goal of supply chain integration for partner selection. To solve these problems, a comprehensive evaluation index system is established in this paper. Secondly, PCA is used to reduce multiple indicators into a few principal components, yet retaining effective evaluation information. Finally, a partner evaluation model based on improved BP neural network which has self-learning function is constructed. The empirical analysis based on a garment enterprise shows that this model is effective and feasible.

FCA(Formal Concept Analysis), which is accurate and complete in knowledge representation, is an effective tool for data analysis and knowledge discovery. A new lattice structure named RCL (Rough Concept Lattice) is presented. Using the approximation method of rough sets, we described the extent as approximation extent so that it can deal with uncertainty knowledge. In the end, a construction algorithm CARCL is provided based on it.

Synthesized anti-submarine warfare (ASW) capability of submarine and formation in war can be improved through real and effective command-to-submarine in the field of formation’s cooperative ASW. As information is the primary content of communication which is the main way of command-to-submarine, the minimum share information set concept of formation’s cooperative ASW was presented including its definition and determining the time and content of information exchange. On the basis of fuzzy rules of command-to-submarine decision and ANFIS adopted, the command-to-submarine decision model was built. The corresponding conclusions were obtained according to decision training examples learned and decision verification examples validated.

With the development of Internet120, the information on the Web is more and more abundance. In this paper, combining Mobile Agent theory and Context-aware, a kind of Context-ware model based on Mobile Agent has been brought forward. The function of analyzing actual requirement of users which combines their context information, utilizing Mobile Agent to aware, process and manage context information, and providing precise knowledge to users are implemented. At last a Context-aware prototype system based on Mobile Agent which is on the Aglet software platform is realized, it can aware of user profile context and the experiment preferably educes the characteristic of Context-aware.

Storm flood forecasting can not accurately describe using one or several models. The chaos of the storm runoff systems make the prediction model must face with difficulty which can not be solved now. This paper will provide a new method to solve the problem proposed before. Use the information of the historical storm flood, establish rainstorm forecasting DSS knowledge base, take advantage of correlated identification between real-time storm flood and knowledge base, and offer important information about flood forecasting in order to provide expert consultations decision support of real-time storm flood forecasting.

To solve the problem of versatile sizes and irregular number in cut order planning (COP) for apparel mass customization, the mathematical model was built and optimization method based on probability search was proposed. Several cutting table layout plans were generated randomly with the production constriction. The optimized sizes combination plan was accordingly obtained using probability search algorithm. The optimization method could rapidly get the apparel cutting plan and decrease the number of cutting table.

Dynamic fuzzy problems exist extensively in realistic world. The dynamic fuzzy logic (DFL) programming language is to deal with dynamic fuzzy data. In order to implement DFL programming language, it should be firstly defined. In this paper, we give the denotational semantics of DFL programming language. The work mainly includes modifying the classical lambda calculus to introduce the character of dynamic fuzzy, the descriptions of semantic objects and the handling functions of semantics.

Considering the stochastic volatility of the wind turbine gearbox oil temperature, the wavelet packet is used to eliminate its noise. On this basis, the grey model is applied to forecast the wind turbine gearbox oil temperature. The predicted results show that the wavelet packet and the grey prediction method have better forecast accuracy. The wind turbine gearbox oil temperature trends can be predicted timely and accurately.

Lattice-valued logic plays an important role in Multi-valued logic systems. In this paper, a lattice valued logic system lp(X) is constructed. The semantics of lp(X) is discussed. It may be more convenient in application and study especially in the case that the valuation domain is finite lattice implication algebra.

In view of the problems that the traditional field irrigation controller can not take into account the impact of air temperature, is poor to drive pumps and inconvenient to be managed and so on, a fuzzy control system for integrative irrigation is designed in the paper. In this design, the power needed is supplied by biogas generator. The biogas digester, generating system, irrigation system, and control system are combined organically. Design mainly improve the traditional three-dimension fuzzy controller, its main control objective is the soil moisture while the secondary control objective is the air temperature; PLC which is stronger at driving is chose as the contrller.The local and remote communications are realized via the Ethernet and GPRS respectively. The system realizes saving water, power and fertilizer, at the same time, realizes monitoring of local and remote which makes it convenient to manage.

This paper proposes a common information integration model based on Multi-Agent and defines the communication protocol for the Agents on the base of the model. Analyze the Agents’ communication process and the transmission control mechanism. And it forms a completed Multi-Agent based information integration scheme.

This paper presents an efficient hardware architecture design for a dedicated transforms and quantization loop for intra16×16. Reusable hardware structure, and parallel processing in pipeline are adopted for DCT and Hadamard implementation. In order to enhance the speed of image processing, quantization, inverse quantization module also uses the parallel and pipeline structure. The design is decribed by Verilog language, implemented with 0.13

μ

m CMOS technology. Experimental results show that the processing speed of the proposed architecture can reach 548 fps for the video resolution of 1920×1080, which is far beyond the requirements of real-time processing requirements.

In recent years, both the number of online E-commerce sites and the types of goods have become more and more. However, because of it, customers have to integrate and analyze much more goods information to make shopping decision during online shopping. This study introduced a novel multi-agent model to automatically gather and provide products’ information to support the customer’s decision of online shopping. In this study, the user preference is applied to product searching process and XML Schema is used to gather cross-site data to achieve a personalized product recommendation. This study provides a forward-looking view for E-commerce intelligent decision support system research.

Research in motion planning has been striving to develop faster and faster planning algorithms in order to be able to address a wider range of applications. The paper provides a literature review of previous works on robot motion planning and collision avoidance. A study on a novel force field method for robot motion planning has been given. Firstly, force field method is present, then, subgoal-guided force field method is proposed, finally, simulations on robot motion planning are carried out in the Player/Stage platform. The Subgoal-Guided Force Field method is suitable for real-time motion planning and collision avoidance in partially known and dynamically changing environments. Simulation results verify the feasibility and performance of the proposed methods.

A construction of an on-line detection system for surface of the hot heavy rail is presented, and a kind of detection means based on the machine vision technology is proposed. In the paper, a description of the principle of machine vision detection, the operational principle of CCD and the construction of the system is made. The overall design of the system, including light controls, image acquisition, image processing and man-machine interface management is described in a modularized form. The system has been practically carried out in a Rail Beam Plant. The client in the local area network could observe the image, make information analysis by on-line or off-line, and manage lots of information. Good results have been obtained.

Though the traditional gas boiler system is both energy saving and environment protecting, there exists certain problems have to be solved. Therefore, A new method for settling the unreasonable control system is presented. The improved control scheme based on DMC-PID algorithm is proposed by analyzing the characteristics of the gas heating system, establishing the boiler system model and studying the characteristics of heating control system. Combined with the actual heating process, the algorithm and the implementation process are presented in detail. Finally, the performance of the algorithm is verified by use of simulation test. The results turn out that the improved algorithm has better efficiency than that of traditional algorithm, and thus has higher utility value.

This article introduces a kind of expert controller which is aimed at dissolved oxygen control system in wastewater treatment of T-type oxidation ditch process. The use of the controller is to control the number, speed and running time of oxidation ditch’s rotary brushes automatically. Meanwhile, it regulates the dissolved oxygen concentration of oxidation ditch .As a result; we can achieve the purpose of remove phosphorus from wastewater, denitrify, denitrify, and reduce the COD and BOD. At last, the effect of sewage disposal reaches the national emission standard.

Nowadays, under the progress of modern computer technology and intelligent control theory, the microprocessors centered distributed control systems provides a broad space for the development of textile industry. Among these systems, fuzzy control has become a major means of computer intelligent control. In this paper, in order to improve the production quality of the cotton cloth breaching process in the textile industry, a distributive fuzzy control system for cotton cloth bleaching is implemented with the industrial control computers, the variables, the rules and the controlling process of the fuzzy controller in this system are designed after analyzing the operational sequence of cotton cloth bleaching. The practice application showed that this system turns out to be meeting the design requirements with a 95% average approved quality of cotton cloth.

The way to diagnose the rolling bearing fault in advance is a key to safe production and avoids serious accidents in technology. This paper puts forward a update way to diagnose the fault in which the wavelet deletes the noises by the original signals handed out and differentiates the originals by frequency, and then use EMD to resolve the low-frequency signals got by wavelet decomposition and reconstruction to get a number of inherent IMF, each function of which is analyzed by time-frequency to know the fault frequency from spectrogram and compare Fourier transform and wavelet transform with strengths and weakness of the way to diagnose. This experiment has shown by the diagnosis we can pick up the fault frequency effectually and easy to judge and diffentiate fault types.

Oxygen respirator intelligent training check equipment used in colliery salvation is an intelligent system combining analysis, control and monitoring in performance, which can analyze the gas in the system, check the change of pressure, exhalation resistance and inhalation resistance, examine both the inhalation temperature and the environment temperature, automatically or manually change the treadmill speed, grade and time to control the work of ambulance man. It changes the traditional training model for ambulance man, makes check quality and quantity. Everything is based on data and eliminates the inkling for artificial feeling. This will realize ambulance man body information collection truly, improve the training mode to promote team members’ diathesis and supply science gist to judge team members’ body condition.

This paper presents a DSP-based intelligent calibrator of mine gas sensor, which is composed of micro-controller unit, signal conditioning unit, communication interface unit, keyboard and display unit, touch-control unit and gas circuit system. Based on CPU technology, electronic technology and control technology, this calibrator has overcome the problems existing in most of the current calibrators, i.e. low speed, low accuracy and labor-consuming, offering better services for mining safety.

According to the function of recycled water in Center Air-condition Set and the run mode of recycle pumper, this paper proposes the method of power saving, discusses the corresponding structure of automation control system, draws up the control system block diagrams for the temperature control and pressure control, describes the system configuration for hardware, as well as provides the method in programming for the temperature data sampling, digital filter, digital controller and etc.

This paper introduces a temperature and humidity monitoring/sending system, which is based on digital technology and computer technology, using the SHT1x sensor maken by Sensirion company of Swiss. The system overcomes disadvantages of poor linearity, low accuracy transmission complex use of traditional system with the analog humidity sensor and makes measurement for temperature and humiture higher precision.

Monitor video playback should get specific scenario by way of either traditional drag-and-drop or location on time line for long time, which is hard to search for necessary information fast and accurately due to mass of video data. However, the method used present in the paper that employs, color histogram to detect short-cut and implements content-based video playback by analyzing key frame image.

The variation of land use monitored by dynamically remote sensing can be calculated by gray value of corresponding inter-temporal image pixel difference. The image subtraction method can enhance the remote sensing images, which can highlight the variation data, and then dynamically monitor the variation. This Paper selects Xinrong District, Datong as an example, by using image interpolation method to deal with two remote sensing images for interpolation analysis, and then extract land change information. After the verification of field measurement, removing pseudo changing pixel, the land use database is updated, which achieve the purpose of using remote sensing method to monitor land use database dynamically. The experimental results show that the image interpolation method for extracting the variation of inter-temporal remote sensing images of land use is fast, accurate and practical.

This paper proposes a 3D volume clipping method based on volume distance field, which is suitable for texture-based volume rendering and exploit per-fragment operation on the graphics hardware to implement clipping. High frame rates are achieved and therefore interactive explorations and clippings of volume data are supported.

Real-time positioning for underground mine vehicle is a key to unmanned underground mining. Machine Vision-based positioning is a novel idea for it. Using Machine Vision method to position devices, landmarks with obvious visual feature and geographic information are needed. In this paper, a type of landmark with barcode is designed and an algorithm for recognizing it is proposed. This type of landmark carries geographic information and can be identified easily. The recognizing algorithm is suitable for real-time mine vehicle positioning because of its small computational and high precision.

Combustion process change of vacuum switching arc and heat radiation induced by combustion process in the vacuum gap have great influence of breaking capacity of vacuum circuit breakers. In this paper a set of image collection system was installed to collect vacuum switching arc images with high-speed and high-resolution CMOS camera. Then digital image processing technology is applied to the research of mutuality of vacuum arc image, according to the diffusion rate of vacuum switching arc in the whole igniting process, whole combustion process of vacuum arc can be divided into five parts: 1) initial stage, 2) diffuse stage I, 3) stable stage,4) diffuse stage II, 5) quenching stage; the distribution of diffusion flame velocity in different vacuum gaps and different magnetic is gotten at the same time. From the results we can see that in the same conditions of other parameters the greater the vacuum gap, the greater the gradient of internal vapor pressure in arc column and the faster radial diffusion speed of arc is; at the same time, with the controlling of axial magnetic, the breaking capacity of vacuum circuit breakers can be improved greatly. Combined with the results in this paper the understanding of the vacuum arc combustion diffusion flame mechanism is deepened.

The technology developed from AI planning has been applied in a lot of areas. However, how to model the planning process is a problem that has not been solved yet. In this paper, we model the process from the perspective of platform. A platform is defined as a linear system, by which sequential plan can be obtained. We also propose a parallel planning model based on multi-platforms, and provide a method for parallelizing a given sequential plan. At the last, we define the executable problem of platform-based planning, and analyze the corresponding complexity.

Emergency relief has characteristics of complexity, urgency, sustainability, technicality, and so on. In this paper a mathematical model to seek the shortest delivery time as the ultimate goal is established based on these characteristics, which is on the core of characteristics with the urgency and consider both the road conditions and on shortage of demand point of relief supplies. The problem of emergency logistics distribution routing optimization is solved by the improved ant colony algorithm—Fish-Swarm Ant Colony Optimization, simulation results show that, compared with basic ant colony algorithm, Fish-Swarm Ant Colony Optimization can find the higher quality to solve the problem of emergency logistics distribution routing optimization.

Arterial pulse wave velocity (PWV) measurement is of great theoretical importance and practical value in evaluating the arterial elasticity and stiffness. The goal of our work is to focus on health-related applications of wireless sensor network(WSN). In this paper we detail a hardware and software solution of pulse waves detection system based on wireless sense network.It can acquire remote multichannel pulse wave signal. Because of its features such as small,portable ,low-power, and wireless transmission, it makes a remote health care system possible between hospital, community health centres and families. The experimental result shows that the system can capture pulse wave signal accurately in real time . The physiologic signal included in signals contribute greatly to detect arteriosclerosis, with practical application value.

A new gray clustering analysis algorithm, which adopted cloud model as whiten function, was proposed to solve the subjective problem in power transformer condition assessment. The algorithm determined condition classification and parameters through their prior knowledge. The algorithm first optimized indicators of power transformer condition evaluation and stratified them. Then, cloud model was introduced as whiten function of gray clustering because the combination of these two methods could comprehensively consider randomness, ambiguity and gray of uncertainty problems. The parameters of cloud models determined according to prior knowledge of power transformer condition evaluation indicators, so it reflected the power transformer condition more really and objectively. Improved weight coefficient gray target theory analyzed dissolved gases and improved the accuracy of the model. Indicators polarities of the improved weight coefficient gray target theory were optimized so that it could evaluate normal state. For samples only with dissolved gases data, improved weight coefficient gray target algorithm can assess condition alone. Example indicates that condition evaluation results of the power transformer based on gray clustering with cloud whiten function consistent with the actual situation, and raise the scientific and objective of power transformer condition evaluation.

In this paper, with regards to the disadvantages of traditional gas sensor used in mine, an intelligent infrared detection method for methane gas based on Non-dispersive Infrared technology is presented. Through the introduction of the principle of infrared spectrum absorption, further to the adoptions of differential measurement method and the technology of single light beam & dual wavelength detection, the relationships between pyroelectric detector signal and gas concentration has been analyzed in details. A relevant formula has been given for between the gas absorption ratio

Fa

and the peak value of pyroelectric detector terminal voltage. Experimental results show that the measurement error is less than ±0.1% (when concentration of methane gas <4%), and meet the requirement of coal mine safety operation.

Semantic orientation extraction is the premise of text semantic tendency analysis and it is also the key process to obtain high precision and recall ratio. In this paper, basic semantic lexicon, conjunction corpus, and semantic distance between words are used to propose an approach of semantic orientation extraction of Chinese text based on multi-algorithm. Experiments show that the approach is better than some classical algorithms such as SO-PMI, HM, and measure of semantic distance between words.

To obtain formal semantics of Chinese discourse, compositional discourse representation theory was adopted to compose semantics from Chinese word to sentence and to discourse. According to syntactic rules and

λ

-box expressions of word categories, sentential logic expression could be created by translating from child nodes to father node in syntactic tree, then the formal representation of Chinese discourse could be further obtained by using construction procedure of DRT to resolve cross-sentential demonstrates and merge sentential DRSs. A rough prototype system was given to depict the implementment process, which will benefit establishing machine-inside representation of discourse semantics of contemporary Chinese.

A Chinese word sense disambiguation algorithm based on HowNet is proposed in this paper. After extracting the ambiguous words in the text, the correlative words which restrict the word sense in the context can be found by using dependency grammar analysis. Finally, by computing the semantic relevancy between the atomic term of ambiguous words and the correlative words, the correct meaning of the ambiguous word can be determined by the value of the semantic relevancy. Experimental results show that the method has a good effect on Chinese word sense disambiguation.

In this paper, it is first demonstrated that for given a linear chain of amino acids the quantum Boolean circuit of implementing the function of its folding in the two-dimensional hydrophobic–hydrophilic model is responsible for processing all the computational basis states and labeling the unique answer (its unique native structure). Next, it is shown that amplitude amplification of the unique answer can be completed by means of Shor’s quantum order-finding algorithm. Then, it is also proved that after a measurement on the unique answer is completed, the successful probability of obtaining the unique answer is the same as that of Shor’s quantum order-finding algorithm.

The establishment of Wu’s method founded an integrated theory and offered an efficient algorithm for solving polynomial equation systems. This paper focuses on the characteristic series algorithm, the core of Wu’s method. Wu’s method, based on symbolic computation, is very compute-intensive. This point usually leads to a time-consuming and inefficient computing process. So parallel computing is introduced to accelerate the computing process. In this paper the corresponding parallel algorithm is presented and its parallel implementation based on multithreading in Maple system is given. The experiment demonstrates a considerable speedup, which shows the high efficiency of this parallel algorithm.

This paper studied the influences of the sectional form of the labyrinth emitter used for single wing labyrinth drip irrigation hose on the hydraulic properties; analyzed theoretically the relationship between flow index of the emitter and flow pattern and the influences of the sectional form of the emitter on the flow index; simulated the flow field of the emitters with 5 different sectional forms under the conditions of 14 different discharges. The following conclusions are obtained: 1) To the non-compensatory drip emitter, the minimum flow index is 0.5 for completely turbulent flow; 2) Both discharge coefficient and flow index of the labyrinth emitter are positively correlation with the wetted perimeter. The bigger the wetted perimeter is, the higher the sensitivity of the emitter discharge to the pressure is. 3) With equivalent labyrinth path cross section area an emitter with a square shaped cross section performs better than one with a rectangle section.

The flotation process refined coal ash soft measuring is the key technology to the flotation process automation .Based on the generalized regression RBF neural network and the introduction of least squares support vector machines (SVM) algorithm ,by BP, RBF, generalized regression RBF and least squares support vector machine flotation refined coal ash soft measuring modeling comparison, in the circumstances of using small sample ,the model accuracy and generalization ability of the least squares support vector machine (SVM) which is based on statistics theory of learning can be well verified. It provide the reliable basis for the flotation process refined coal ash soft survey modeling which used the least squares support vector machines.

The color feature is demonstrated by the algorithm of the improved histogram. The texture feature is extracted by Gabor filters. On the basis of above contents, the article studies a method for image retrieval using combined color feature and texture feature. Then by studying the theory of support vector machines, the algorithm of the SVM relevance feedback is introduced. The results of experiments show that combined feature extraction and relevance feedback algorithm has better retrieval performance and the results can be obtained to better meet the need of users.

In order to implement the policy about strengthen drug safety supervision and management, National regulations the grade of drug supervision code must be above grade C [2]. In this paper, mainly selected a barcode optical parameters, in order to objective evaluate each index of the drug supervision code, adopted BP artificial neural network in neural network toolbox of MATLAB, used the data which measured from Barcode reflectance curve to establish BP neural network model of BP. The result indicates BP artificial neural network model can assess code every index and grade. The result also indicates that at the same time the BP artificial neural network in MATLAB neural network toolbox can be applied to the grade evaluation of the drug supervision code.

Web services are software systems designed to support interoperable machine-to-machine interaction over a network. There are mainly two problems in Web services discovery: how to describe service accurately and delicately to support precisely matchmaking and how to store, index and exchange the information of Web services in order to extend the scope of service discovery and guarantee the acceptable processing time of service discovery. In this paper we proposed a method for semantic Web services discovery using structured P2P technology. The service is published by the output concepts of service model in OWL-S. The service discovery is a two-steps task, service location through output concepts and service matchmaking through input concepts. Furthermore, we proposed the hashing technology based on synsets of WordNet to overcome the problem of lack of semantic information and only supporting exact searching in structured P2P networks.

The core concept of cloud computing is the resource pool. Hadoop MapReduce is a software framework for easily writing applications which process vast amounts of data in-parallel on large clusters of commodity hardware in a reliable, fault-tolerant manner. A MapReduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner. We distribute the total slots according to Pi which is the percent of job’s unfulfilled tasks in the total unfulfilled tasks. Since the P

i

of the large job is bigger, the large job will be allocated more slots. We can clearly improve the response time of the large jobs. This new scheduling algorithm can improve the performance of the system, such as throughout, response time.

The kinetics simulation is the key point of robot design. A robot kinetics simulation system based on AutoCAD is developed in this paper. By the Visual LISP which is in the Auto CAD software, the various robot models are obtained. The types and the size of robots can be arbitrarily chosen by user according to the practical requirement. The motion simulation of robots can be achieved in this system, and the parameters of kinetics also obtained with solving the kinetics equation. Based on this system, a typical robot is analyzed and the satisfied kinetics solutions are obtained. The results show this system is a well off-line programming simulation system.

An improved particle swarm optimization (IPSO) is proposed in this paper. In the new algorithm, the Optimal and sub-optimal locations, which each particle encountered and the swarm meted, are kept. Based on these locations, the IPSO produces four velocities for each particle and obtains the particle’s iterative position. The IPSO enlarges the search space and enhances global search ability. From the results obtained through benchmark problems, it is clearly seen that the proposed IPSO method is competitive to the PSO.

Traditional methods and techniques of retrieval are inefficient on vary large number of video data. But, the content-based retrieval shows a right direction for information retrieval. Analysis of the features of maximum matching and optimal matching, the former reflects only from the perspective of the visual similarity of the two shots, and the latter objectively point of view fully reflected the contents of the similar characteristics of the shots on the basis of maximum matching from, but the most optimal matching algorithm ignores the time sequence of video content. This paper presents an improved optimal matching algorithm, and the experimental results showed the algorithm in the recall and precision rates are both obtain more satisfactory results.

The traditional object tracking with cue fusion is inaccurate under complex background. Especially when some blocks exist, the targets may be lost. To solve this problem, improved cue fusion for object tracking algorithm based on particle filter is proposed. It uses color and motion as the observation information source. Color is the main observation information and motion is the auxiliary information. It weights particles followed by the order of information. Block detection, particle filter and mean-shift are used together to track the interest targets. The experimental results show that in complex scene, when the number of particles of the proposed method is half of the traditional cue fusion, the proposed method can improve effectively the accuracy of target tracking, and track object stably when the shape is changing. So the proposed method is more robust and real-time.

Reducing the transportation time on bus routes can increase the proportion of regular bus passengers, thus easing the traffic congestion. This paper presents a new model of bus routing based on an ant colony optimization (generally abbreviated as ACO) algorithm. The model, comprehensively taking traffic variables into account, figures out the quickest and optimal route, and is proved to be feasible by conducting researches and simulation experiments.

With the rapid development of Cloud computing, data mining and ANN technology, we try to combined cloud data mining and ANN technologies, Using the Capacity of these technologies such as data acquisition, data storage and analyzing large amounts of complicated non-1inear data, To construct a forecasting model for massive data real-time accurately which is difficult to complete on the traditional mode. This new model utilizes an enterprise sales data to test. The result proves that the model is feasible and effective. According to this model’s prediction result, we can provide scientific and real-time decision support for the enterprise management.

With the fast growth of Chinese economy and the society’s progress, the environment issues in China begin to attract people’s attention more and more. After United Nations Climate Change Conference in Copenhagen, Chinese begin to concern about the “carbon emissions” and the low carbon lifestyle. According to the expert’s forecast, China’s automobile industry’s carbon emissions possibly occupy about 5% of total emissions. And the automobile industry of our country is developing quickly, its carbon emissions rate in total emissions will be more and more. In this paper, it’s demonstrated that Rough Set Theory can find some potential knowledge by data analysis. Based on Rough Set Theory and the demand of prediction of car sales volume, a procedure of car sales forecast is proposed. Then automobile carbon emissions can be forecasted with obtained rules set and calculation of carbon emissions. The prediction is expected to have some effect on the establishment of Chinese twelfth five-year plan, especially the policy about the carbon emissions.

Inspired by the bacteria foraging process, the thought of bacteria foraging algorithm used in particle swarm algorithm, this paper puts forward a kind of bacteria foraging particle swarm algorithm. For the trend of the operation process of bacteria can guide particles toward the more optimal direction evolve, and the particle swarm algorithm and improve bacteria foraging algorithm convergence speed and optimization ability. And the algorithm is applied to attribute reduction. Numerical results show that the proposed bacteria foraging particle swarm optimization algorithm of the reduction in optimization ability, are better than Hu algorithm, particle swarm reduction algorithm and bacteria foraging reduction algorithm, can get a better minimum attribute reduction.

In this paper, a novel feature selection method of discernibility object pair set is provided. At first, the feature selection definition of new method is presented. What’s more, it is proved that the above feature selection definition is equal to the feature selection definition based on conditional information entropy. In order to compute discernibility object pair set, a quick algorithm for simplified decision system is introduced, whose time complexity is

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