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Über dieses Buch

Fuzzy Information & Engineering and Operations Research & Management is the monograph from submissions by the 6th International Conference on Fuzzy Information and Engineering (ICFIE2012, Iran) and by the 6th academic conference from Fuzzy Information Engineering Branch of Operation Research Society of China (FIEBORSC2012, Shenzhen,China). It is published by Advances in Intelligent and Soft Computing (AISC). We have received more than 300 submissions. Each paper of it has undergone a rigorous review process. Only high-quality papers are included in it containing papers as follows:

I Programming and Optimization.

II Lattice and Measures.

III Algebras and Equation.

IV Forecasting, Clustering and Recognition.

V Systems and Algorithm.

VI Graph and Network.

VII Others.

Inhaltsverzeichnis

Fuzzy Modeling of Optimal Initial Drug Prescription

This paper focused on a fuzzy approach in migraineurs drug prescription. There is no denying that medicine data records are mixed with uncertainty and probability so all methods concerning migraine drug prescription should be considered in fuzzy environment and designed according to the knowledge of an expert specialist. Overall it seems logical to propose fuzzy approach which could cover all uncertainties. According to fuzzy rule base concepts which are obtained by co-operation of an expert, fuzzy control has been used to model drug prescription system. Finally clinical experiences are used to confirm efficacy of drug prescription model. It should be considered that in most cases this disease may cause health social problems as well as financial obstacle for the companies and in upper stage for governments as a result of reduce work time among the employees. So prescribing optimal initial drug to make the disease stable is obligatory. With the corporation of experts 25 rule bases are introduced and tested on 50 different patient records, result shows that the accuracy of model is 94 %

$$\pm$$

±

5.5 with r-square equal to 0.9148.

Mostafa Karimpour, Ali Vahidian Kamyad, Mohsen Forughipour

Decision Parameter Optimization of Beam Pumping Unit Based on BP Networks Model

Beam pumping unit is the most popular oil recovery equipment. One of the most common problems of beam pumping unit is its high energy consumption due to its low system efficiency. The main objective of this study is modeling and optimization a beam pumping unit using Artificial Neural Network (ANN). Among the various networks and architectures, multilayer feed-forward neural network with Back Propagation (BP) training algorithm was found as the best model for the plant. In the next step of study, optimization is performed to identify the sets of optimum operating parameters by Strength Pareto Evolutionary Algorithm-2 (SPEA2) strategy to maximize the oil yield as well as minimize the electric power consumption. Forty-nine sets of optimum conditions are found in our experiments.

Xiao-hua Gu, Zhi-qiang Liao, Sheng Hu, Jun Yi, Tai-fu Li

Optimization Strategy Based on Immune Mechanism for Controller Parameters

Control quality of the controller depends on correct tuning of control parameter, and it is directly related to the control effect of whole control system. Aimed at the puzzle that the parameter of controller has been difficult to tune, the paper proposed a sort of optimization model based on immune mechanism for tuning of controller parameters. Firstly it defined the antibody, antigen and affinity of tuning parameter, and secondly explored the process of parameter tuning based on immune mechanism in detail, then explained the tuning method by means of optimizing parameters of PID controller as well as the seven parameters of HSIC controller. Finally it took a high-order process control as the example, and made the simulation to a large time delay process, and to a highly non-minimum phase process as well as HSIC controller. The simulation experiment results demonstrated that it is better in comparison with some other tuning methods for dynamic and steady performance. The research result shows that the proposed method is more effective for controller parameter tuning.

Xian-kun Tan, Chao Xiao, Ren-ming Deng

Preinvex Fuzzy-valued Function and Its Application in Fuzzy Optimization

Based on the ordering of fuzzy numbers proposed by Goetschel and Voxman, in this paper, the representations and characterizations of semi-E-preinvex fuzzy-valued function are defined and obtained. As an application, the conditions of strictly local optimal solution and global optimal solution in the mathematical programming problem are discussed.

Zeng-tai Gong, Yu-juan Bai, Wen-qing Pan

Posynomial Geometric Programming with Fuzzy Coefficients

In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either possibilistic programming or multiobjective programming methods. Unfortunately, all these methods have shortcomings. In this note, using the concept of comparison of fuzzy numbers, we introduce a very effective method for solving these problems. Then we propose a new method for solving posynomial geometric programming problems with fuzzy coefficients.

Ren-jie Hu, Bing-yuan Cao, Guang-yu Zhang

Global Optimization of Linear Multiplicative Programming Using Univariate Search

We show that, by using suitable transformations and introducing auxiliary variables, linear multiplicative program can be converted into an equivalent parametric convex programming problem, parametric concave minimization problem or parametric D.C. programming. Then potential and known methods for globally solving linear multiplicative program become available.

Xue-gang Zhou

Affine SIFT Based on Particle Swarm Optimization

As for ASIFT, ASIFT has been proven to be invariant to image scaling and rotation. Specially, ASIFT enables matching of images with severe view point change and outperforms significantly the state-of-the-art methods. It accomplished this by simulating several views of the original images. However, we found that the simulated parameters are continuous, namely, transformations acquired by ASIFT cant express the real relationship between reference and input images. Therefore, a particle swarm optimization based sample strategy is presented in this paper. The basic idea is to search the best transform in continuous parameter space. Experimental results show that the proposed PSO-ASIFT algorithm could get more matches compared with the original ASIFT and SIFT.

Xue-lian Cao, Guo-Rong Cai, Shui-li Chen

Genetic Quantum Particle Swarm Optimization Algorithm for Solving Traveling Salesman Problems

This paper presents a Genetic Quantum Particle Swarm Optimization (GQPSO) algorithm to solve Traveling Salesman Problems (TSPs). This algorithm is proposed based on the concepts of swap operator and swap sequence by introducing crossover, mutation and inverse operators in Genetic Algorithm (GA). Our algorithm overcomes such drawbacks as low convergence rate and local optimum when using Particle Swarm Optimization (PSO) or Quantum Particle Swarm Optimization (QPSO) algorithm to solve TSP. The experiment result shows that GQPSO algorithm has very powerful global search ability and its convergence rate is sharply accelerated compared to that of QPSO algorithm. GQPSO algorithm will have very good application prospects in solving combinational optimization problems.

Wei-quan Yao

An Improved Optimization Algorithm for Solving Real Eigenvalue and Eigenvector of Matrixes

In this paper, aiming to papers [

1

,

2

]’s deficiency, we propose a method which changes to use the Excel’s single variable equations and regional operations with the Excel VBA programming. Finally, we get a method to solve the matrix eigenvalues and the eigenvectors by using Excel. The facts show that the method in this paper is better than the references’ methods.

Wei-quan Yao

Fuzzy Diameter Approximate Fixed Point in Normed Spaces

We define fuzzy diameter approximate fixed point in fuzzy norm spaces. We prove existence theorems, we also consider approximate pair constructive mapping and show its relation with approximate fuzzy fixed point.

S. A. M. Mohsenialhosseini, H. Mazaheri

Cascade and Wreath Products of Lattice-Valued Intuitionistic Fuzzy Finite State Machines and Coverings

The concepts of the cascade products and the wreath products of lattice-valued intuitionistic fuzzy finite state machines, homomorphisms and weak coverings are given. At the same time, the covering relations of two homomorphisms lattice-valued intuitionistic fuzzy finite state machines are studied. The covering relations among the full direct products, cascade products, wreath products are disscussed. Some transitive properties of covering relations are obtained in the product machines.Therefore,it is an important step to study lattice-valued intuitionistic fuzzy finite state machines.

Li Yang, Zhi-wen Mo

Attribute Reduction of Lattice-Value Information System Based on L-Dependence Spaces

Lattice is a wide concept. All different kinds of information systems come down to lattice-value information system. Attribute reduction of different kinds of information systems could be boiled down to that of lattice-value information systems. In this paper, L-dependence space is established on lattice-value information system. Then attribute reduction of theory and algorithm is put forward and the effectiveness and feasibility of algorithm are explained by an example. Finally, the result of attribute reduction is compared with other algorithms by computational complexity.

Chang Shu, Zhi-wen Mo, Xiao Tang, Zhi-hua Zhang

A New Similarity Measures on Vague Sets

Vague set is a valid tool for processing uncertain information. The similarity measure of two uncertain patterns is important for intelligent reasoning. It is also a key problem to measure the similarity of vague values or vague sets in vague information processing systems. In this paper, according to the theory of similarity measure between intervals, it is shown that four factors influencing vague sets and vague values should be taken into account while calculating the similarity degree. Some existing similarity measures are reviewed and compared. Some faults of existed methods are pointed out. A new method for similarity measures between vague sets (values) is put forward, and is proved to satisfy some rules. The validity and advantage of this method are illustrated by an example.

Zheng-qi Cai, Ya-bin Shao, Shuang-liang Tian, Yong-chun Cao

Characterizations of $$\alpha$$ -Quasi Uniformity and Theory of $$\alpha$$ -P.Q. Metrics

In Wu Fuzzy Systems and Mathematics 3:94–99, 2012, the author introduced concepts of

$$\alpha$$

-remote neighborhood mapping and

$$\alpha$$

-quasi uniform, and obtained many good results in

$$\alpha$$

-quasi uniform spaces. This chapter will further investigate properties of

$$\alpha$$

-remote neighborhood mapping, and give some characterizations of

$$\alpha$$

-quasi uniforms. Based on this, this chapter also introduces concept of

$$\alpha$$

-P.Q. metric, and establishes the relations between

$$\alpha$$

-quasi uniforms and

$$\alpha$$

-P.Q. metrics.

Xiu-Yun Wu, Li-Li Xie, Shi-Zhong Bai

The Complex Fuzzy Measure

In this paper, we define the concept of complex Fuzzy measure, which is different from the concept of complex Fuzzy measure in [

2

], and discuss its properties and theorems. On the basis of the concept of complex Fuzzy measurable function in [

2

], we study its convergence theorem. It builds the certain foundation for the research of complex Fuzzy integral.

Sheng-quan Ma, Mei-qin Chen, Zhi-qing Zhao

Fuzzy $$\alpha$$ α -Ideals of BCH-Algebras

The aim of this paper is tointroduce the notions of fuzzy

$$\alpha$$

α

-ideals of BCH-algebras and to investigate their properties. The relations among various fuzzy ideals are discussed as well. The upper and lower rough ideals of BCH-algebras are defined. Then the properties of rough ideals are discussed. The left and the right rough fuzzy ideals are defined and researched. Finally, we characterize well BCH-algebras via fuzzy ideals.

Ju-ying Wu

Lattice-Semigroups Tree Automation’s Congruence and Homomorphism

The partial order of lattice elements in lattice-semigroup tree automata(LSTA) is defined in this paper. We proved the existence of semilattices and also lattices formed by different types of LSTA. Finally, we investigate the congruence and homomorphism of lattice-semigroup by LSTA formed from the algebra angle, Then we obtain homomorphism fundamental theorem of the LSTA.

Xiao-feng Huang, Zhi-wen Mo

( $$\in ,\in \vee q_{(\lambda ,\mu )}$$ ∈ , ∈ ∨ q ( λ , μ ) )-Fuzzy Completely Semiprime Ideals of Semigroups

We introduce a new kind of generalized fuzzy completely ideal of a semigroup called

$$(\in ,\in \vee q_{(\lambda ,\mu )})$$

(

,

q

(

λ

,

μ

)

)

-fuzzy completely semiprime ideals. These generalized fuzzy completely semiprime ideals are characterized.

Zu-hua Liao, Li-hua Yi, Ying-ying Fan, Zhen-yu Liao

Duality Theorem and Model Based on Fuzzy Inequality

This article reports a study on duality theorem and model with fuzzy approaches. The study focuses on the economical interpretation of duality theorem as well as on solving duality problems in a fuzzy mathematical perspective. Besides the regular duality concepts, this article puts forward the methods of drawing non-symmetric fuzzy duality programming from that of symmetric fuzzy duality and drawing symmetric fuzzy duality programming from that of non-symmetric fuzzy duality. It sums up the general rules of forming fuzzy duality programming and proves symmetric duality theorem of fuzzy inequality type.

Xin Liu

$$(\in ,\in \vee q_{(\lambda ,\mu )})$$ ( ∈ , ∈ ∨ q ( λ , μ ) ) -Fuzzy Completely Prime Ideals of Semigroups

We introduce a new kind of generalized fuzzy completely prime ideal of a semigroup called

$$(\in ,\in \vee q_{(\lambda ,\mu )})$$

(

,

q

(

λ

,

μ

)

)

-fuzzy completely prime ideals. These generalized fuzzy completely prime ideals are characterized. We also discuss the equivalence relationship between

$$(\in ,\in \vee q_{(\lambda ,\mu )})$$

(

,

q

(

λ

,

μ

)

)

-fuzzy completely prime ideals and

$$A_{t\vee q_{(\lambda ,\mu )}}$$

A

t

q

(

λ

,

μ

)

.

Zu-hua Liao, Yi-xuan Cao, Li-hua Yi, Ying-ying Fan, Zhen-yu Liao

Soft Relation and Fuzzy Soft Relation

Molodtsov introduced the concept of soft sets as a general mathematical tool for dealing with uncertainties. Research on soft set theory has been made progress in recent years. This paper firstly introduce the concept of soft relation and fuzzy soft relation; secondly we propose the concept of the projection and the section of fuzzy soft relation and study some properties; finally we give the concept of fuzzy soft linear transformation and get some conclusions.

Yu-hong Zhang, Xue-hai Yuan

Existence of Solutions for the Fuzzy Functional Differential Equations

In this paper, we consider the existence theorems of solution for fuzzy functional differential equations under the compactness-type conditions and dissipative type conditions, via the properties of the embedding mapping from fuzzy number to Banach space.

Ya-bin Shao, Huan-huan Zhang, Guo-liang Xue

The Generalized Solution for Initial Problems of Fuzzy Discontinuous Differential Equations

In this paper, we generalized the existence theorems of Caratheodory solution for initial problems of fuzzy discontinuous differential equation by the definition of the

$$\omega -ACG^{*}$$

ω

-

A

C

G

for a fuzzy-number-valued function and the nonabsolute fuzzy integral and its controlled convergence theorem.

Ya-bin Shao, Huan-huan Zhang, Zeng-tai Gong

A Revised Grey Model for Fluctuating Interval Fuzzy Series Forecasting

Grey models are built on the basis of the real number series, not the fuzzy number series. In this paper, GM (1, 1), a basic prediction model of grey models, is generalized to the fuzzy number series. GM (1, 1) based on interval fuzzy number series [IFGM (1, 1)] is proposed firstly, which is suitable for the prediction of interval number series with weak fluctuation. In order to extend its applicable range, a revised model is then proposed. Markov prediction theory is applied to revising IFGM (1, 1) to make it suitable for the fluctuating interval number series. The general development tendency of the raw series is embodied by grey model and the random fluctuation is reflected by Markov prediction. The first practical example has shown IFGM (1, 1) is effective for small sample and weak fluctuating series. The consumer price indexes of China from 1996 to 2009 are taken as an example of fluctuating interval number series. Revised IFGM (1, 1), IFGM (1, 1), double exponential smoothing method and autoregressive moving average (ARMA) are all applied to it. Comparison of the results has shown the revised IFGM (1, 1)has the best precision than the other models.

Xiang-yan Zeng, Lan Shu, Gui-min Huang

Exponential Forecasting Model with Fuzzy Number in Long-Distance Call Quantity

An exponential forecasting model, in this paper, is established with fuzzy numbers in long-distance call quantity, and a determining method is given in comparison with examples mentioned in the paper. Besides, the model is verified by example comparison, and the effectiveness of its method.

Bing-yuan Cao

Contingent Valuation of Non-Market Goods Based on Intuitionistic Fuzzy Clustering: Part I

In order to value the non-market goods, we consider the uncertain preference of the respondents for non-market goods, individual often have trouble trading off the good or amenity against a monetary measure. Valuation in these situations can best be described as fuzzy in terms of the amenity being valued. We move away from a probabilistic representation of uncertainty and propose the use of intuitionistic fuzzy contingent valuation. That is to say we could apply intuitionistic fuzzy logic to contingent valuation. Since intuitionistic fuzzy sets could provide the information of the membership degree and the nonmembership degree, it has more expression and flexibility better than traditional fuzzy sets in processing uncertain information data. In this paper, we apply intuitionistic fuzzy logic to contingent, developing an intuitionistic fuzzy clustering and interval intuitionistic fuzzy clustering approach for combining preference uncertainty. We develop an intuitionistic fuzzy random utility maximization framework where the perceived utility of each individual is intuitionistic fuzzy in the sense that an individual’s utility belong to each cluster to some degree. Both the willingness to pay (WTP) and willingness not to pay (WNTP) measures we obtain using intuitionistic fuzzy approach are below those using standard probability methods.

Zeng-tai Gong, Bi-qian Wu

Forecasting Crude Oil Price with an Autoregressive Integrated Moving Average (ARIMA) Model

In this chapter, an autoregressive integrated moving average (ARIMA) model is proposed to predict world crude oil. Data from 1970 to 2006 is used for model development. We find that the model is able to describe and predict the average annual price of world crude oil with the aid of SAS software. The mean absolute percentage error (MAPE) is 4.059 %. Experiment shows the model have the preferable approach ability and predication performance, particularly for the short - term forecast.

Chun-lan Zhao, Bing Wang

Use of Partial Supervised Model of Fuzzy Clustering Iteration to Mid- and Long-Term Hydrological Forecasting

Most operational hydrological forecasting systems produce deterministic forecasts and most research in operational hydrology has been devoted to finding the “best” forecasts rather than quantifying the predictive uncertainty. With the complex non-linear relation between forecasting indicators and forecasting object, it’s difficult to get forecasting results with high quality from satisfied forecasting model. Therefore, based on fuzzy clustering algorithm, a partial supervised model of fuzzy clustering iteration is presented with the history data supervised and the forecasting precision is improved. The forecasting model is distinct in mathematic and physical conception, and is of good dispersion. A case study of Yamadu station in Xinjiang, China, is given to show the effectiveness of the model in mid-and long- term hydrological forecasting.

Yu Guo, Xiao-qing Lai

A Fuzzy Clustering Approach for TS Fuzzy Model Identification

In this paper, a fuzzy clustering approach for TS fuzzy model identification is presented. In the proposed method, the modified mountainx clustering algorithm is employed to determine the number of clusters. Secondly, the fuzzy c-regression model (FCRM) algorithm is used to obtain an optimal fuzzy partition matrix. As a result, the initial parameters can be determined by the optimal fuzzy partition. Finally, gradient descent algorithm is adopted to precisely adjust premise parameters and consequent parameters simultaneously. The simulation results reveal that the proposed algorithm can model an unknown system with a small number of fuzzy rules.

Mei-jiao Lin, Shui-li Chen

Model Recognition Orientated at Small Sample Data

System modeling is a prerequisite to understand object properties, while the chances are that an industrial site may come along with restricted conditions, leading to less experimental data acquired about the objects. In this case, the application of traditional statistical law of large numbers for modeling certainly will influence the identification precision. Aiming at the problems in recognition of small samples being not that high in precision, it is proposed to introduce the bootstrap-based re-sampling technique, upon which the original small sample data are expanded in order to meet the requirements of the statistical recognition method for sample quantity, so as to meet the requirements of precision. The simulation results showed that the extended sample model recognition accuracy is substantially higher than that of the original small sample. This illustrates the validity of the bootstrap-based re-sampling technique, working as an effective way for small sample data processing.

Jun-ling Yang, Yan-ling Luo, Ying-ying Su

A New Fuzzy Clustering Validity Index with Strong Robustness

Cluster validity has been widely used to evaluate the fitness of partitions produced by fuzzy c-means (FCM) clustering algorithm. Many validity functions have been proposed for evaluating clustering results. Most of these popular validity measures do not work well for clusters with different fuzzy weighting exponent

$$m$$

m

and data with outliers at the same time. In this paper, we propose a new validity index for fuzzy clustering. This validity index is based on the compactness and separation measure. The compactness is defined by fuzzy Z-membership function based on the gold dividing point and separation is described by monotone linear function. The contrasting experimental results show that the proposed index works well.

Xiang-Jun Xie, Yong Wang, Li Zhong

Regional Economic Forecasting Combination Model Based on RAR+SVR

Regional economy has become a critical part in national economy system. Mastering its change is important for national economic decision-making. Yet many economic variables in regional economy system have characteristics of nonlinearity and instability, the result of forecasting achieved by traditional linear modeling and predicting technology doesn’t reach the demand of accuracy. Thus, a combination model based on Residual Auto-regressive and Support Vector Regression is proposed in this chapter. In the model the linear part of time series will be fitted by means of Residual Auto-regressive first, then the nonlinear part included in the residual will be draw by means of Support Vector Regression. The combination model helps to increase the accuracy of forecasting in regional economy system. At the end, a prediction of GDP in Guangdong province shows the efficiency of the model.

Da-rong Luo, Kai-zhong Guo, Hao-ran Huang

On Cycle Controllable Matrices over Antirings

In this paper, cycle controllable matrices are defined over an arbitrary commutative antiring

$$L.$$

L

.

Some properties for cycle controllable matrices are established, a necessary and sufficient condition for a cycle controllable matrix which has a given nilpotent index is obtained. Finally, expressions for a cycle controllable matrix as a sum of square-zero matrices are shown.

Jing Jiang, Xin-an Tian, Lan Shu

Control Strategy of Wastewater Treatment in SBR Method Based on Intelligence Fusion

To solve the puzzle of dissolved oxygen control for wastewater treatment in SBR method, the paper proposed a sort of intelligence fusion control algorithm. In the paper, it summarized up the main puzzles in control, proposed the intelligence fusion based control strategy, constructed the structure of controller, discussed the control algorithm, and made the simulation by means of intelligence fusion based control algorithm. The simulation curve demonstrated that the proposed control strategy would be stronger in robustness and suitable for the dissolved oxygen control of wastewater treatment. The research result shows that it is feasible and reasonable for wastewater treatment in SBR method.

Xian-kun Tan, Ren-ming Deng, Chao Xiao

Grey Bottleneck Transportation Problems

In some real situations, such as transporting emergency goods when a natural disaster occurs or transporting military supplies during the war, the transport network may be destroyed, the transportation cost (time or mileage) from sources to destinations may not be deterministic, but uncertain grey number. This paper investigated a new bottleneck transportation problem called the grey bottleneck transportation problem, in which the transportation time (or mileage) from sources to destinations may be uncertain, and introduces its mathematical model and algorithms.

Guo-zhong Bai, Li-na Yao

A Simulated Annealing Genetic Algorithm for Solving Timetable Problems

The post-enrolment course timetabling (PE-CTT) is one of the most studied timetabling problems, for which many instances and results are available. In this paper, we design a metaheuristic approach based on Simulated Annealing to solve the PE-CTT. We consider all the different variants of the problems that have been proposed in the literature and perform a comprehensive experimental analysis on all the public instances available. The outcome is that the solver, properly engineered and tuned, performs very well in all cases. Thus we provide the new best known results for many instances and state-of the-art values for the others. An algorithm SAGA for solving timetable problem was presented by analyzing all kinds of restricting conditions and special requirements in timetable arrangement of colleges and universities. Moreover, the crossover and mutation operators in the simulated annealing genetic algorithm were improved with adaptive strategy in order to enhance its searching ability and efficiency of the algorithm. The numerical experiments showed that the algorithm was efficient and feasible.

Yi-jie Dun, Qian Wang, Ya-bin Shao

Weighted Statistical Approximation Properties of the q-Phillips Operators

In this paper, the

q

-Phillips operators which were introduced by I. Yüksel are studied. By the means of the

q

-integral and the concept of the statistical convergence, the weighted statistical approximation theorem of the operators is obtained. Then a convergence theorem of Korovkin type is given. Finally, a Voronovskaja-type asymptotic formulas is also investigated.

Mei-ying Ren

Consistency Adjustment Algorithm of the Reciprocal Judgment Matrix

In this paper, firstly, according to the problem of the consistency of reciprocal judgment matrix, two kinds of consistency recursive iterative adjustment algorithms were given. The algorithm is based on adjustment by order, and fixed value randomly to adjust other value, then choose the matrix as consistency matrix which is corresponding the minimum deviation value. Then give an example to adjust the reciprocal judgment matrix to be consistency by using the two kinds of recursive iterative adjustment algorithm.

Wei-xia Li, Cheng-yi Zhang , Hua Yang

Wavelet Frequency Domain Adaptive Multi-Modulus Blind Equalization Algorithm Based on Fractional Lower Order Statistics

$$\beta$$

β

multi-modulus blind equalization algorithm based on Fractional lower order statistics (FLOS

$$\beta$$

β

FWTMMA) is proposed in the

$$\alpha$$

α

-stable distribution noise environment. This proposed algorithm uses Fractional lower order statistics to restrain

$$\alpha$$

α

-stable distribution noise, the equalizer output signal energy is optimized adaptively to obtain a joint blind equalization algorithm, its computational loads can be greatly reduced by using Fast Fourier Transform (FFT) and overlapping retention law. In the proposed algorithm, orthogonal wavelet transform is used to improve the convergence rate. The underwater acoustic channel simulation results show that the proposed algorithm has better performance.

Jun Guo, Xiu-zai Zhang, Ye-cai Guo

The Integrated Operator Base on Complex Fuzzy Valued Intuitionist Fuzzy Sets and Its Application in the Evaluation for Hospital

In this paper, based on intuitionist fuzzy sets, we firstly got the integrated operator base on Complex Fuzzy valued Intuitionist Fuzzy Sets, and then applied to the evaluation of the hospital in and got very good results.

Xue-ping Zhang, Sheng-quan Ma

Fuzzy Average Tree Solution for Graph Games with Fuzzy Coalitions

In this chapter, the model of graph games with fuzzy coalitions is proposed based on graph games and cooperative games with fuzzy coalitions. The fuzzy average tree solution of graph games with fuzzy coalitions is given, which can be regarded as the generalization of crisp graph games. It is shown that the fuzzy average tree solution is equal to the fuzzy Shapley value for complete graph games with fuzzy coalitions. We extend the notion of link-convexity, under which the fuzzy core is non-empty and the fuzzy average tree solution lies in this core.

Cui-ping Nie, Qiang Zhang

Algorithm of Geometry-Feature Based Image Segmentation and Its Application in Assemblage Measure Inspect

Aimed at the puzzle that the edge of industrial computerized tomography image is difficult to realize accurate measure for nondestructive inspection in work-piece, which is resulted from over-segmentation phenomenon when adopted traditional watershed algorithm to segment the image, the chapter proposed a sort of new improved image segmentation algorithm based fuzzy mathematical morphology. In the paper, it firstly smoothed the image by means of opening-closing algorithm based fuzzy mathematical morphology, and then it computed the gradient operators based on the mathematical morphology, after that it segmented the gradient image to get the result based on fuzzy mathematical morphology. And finally it made the assemblage measure inspect for large-complex workpiece. The result of simulation experiment shows that it is better in eliminating over segmentation phenomenon, and more applicable in image recognition.

Chao-hua Ao, Chao Xiao, Xiao-yi Yang

The Application of GA Based on the Shortest Path in Optimization of Time Table Problem

Time Table Problem (

TTP

) is a constraint Combinational Optimization Problem (

COP

) with multi- objective. Based on the analysis of advantages and disadvantages of Genetic Algorithm (

GA

) and Kruskal Algorithm (

KA

), this chapter put forward to a new hybrid algorithm—the Shortest path-based Genetic Algorithm (

SPGA

), which has the advantages of both

GA

and

KA

. In this algorithm, fitness function, selection operator, crossover operator and mutation operator are studied deeply and improved greatly, so that the hybrid algorithm can be used in the actual course arrangement. The simulation results show the effectiveness of this method.

Zhong-yuan Peng, Yu-bin Zhong, Lin Ge

Monitoring System of Networked Gas Stations Based on Embedded Dynamic Web

The oil is a sort of strategic material, and therefore strengthening the management of oil material has very important significance. Aimed at the difference in communication protocol among dispensers of gas stations, resulted in being difficult to realize the integration of monitoring system, this paper proposed a sort of integrated monitoring solution based on embedded Web. The core device of monitoring system selected a sort of embedded Web server based on Intel Xscale IXP-422 RISC CPU. The servers distributed in the industrial field of gas stations interconnected through industrial Ethernet, and composed a wide area network system based on Web service. The field bus of field device connected to Web server in the field local area of gas stations to complete the integrated monitoring of field device. The system adopted the architecture of distributed browser/server. By means of the approach of Apache+Html+PHP, the monitoring and management of the gas stations could be realized based on embedded Web, and the realization of dynamic Web browse could be completed by control unit. The actual test data demonstrated that it could be high in security level, stronger in anti-jamming, better in environment adaptability, and higher in real time performance. The research result shows that the proposed solution is feasible and reasonable.

Wei Huang, Kai-wen Chen, Chao Xiao

Research on Workflow Model Based on Petri Net with Reset Arcs

To satisfy the workflow modeling requirements in the ability of powerful expression, a method by adding reset arc to extend the workflow model has been put forward, and the formal representation is proposed in this paper. Then, the soundness analysis of this method is researched by using an insurance claim model and reachability graph. Therefore, this method improved the power of describing workflow model of WF-net, especially cancellation feature which was not supported by most Petri net models.

Chi Zhang, Sakirin Tam, Kai-qing Zhou, Xiao-bo Yue

The Closeness Centrality Analysis of Fuzzy Social Network Based on Inversely Attenuation Factor

Fuzzy centrality analysis is one of the most important and commonly used tools in fuzzy social network. This is a measurement concept concerning an actor’s central position in the fuzzy social network, and it reflects the different positions and advantages between social network actors. In this paper we extend the notion of centrality and centralization to the fuzzy framework, propose fuzzy inversely attenuation closeness centrality, and discussed fuzzy group closeness centralization based on inversely attenuation factor in fuzzy social networks.

Ren-jie Hu, Guang-yu Zhang, Li-ping Liao

Enterprise Innovation Evaluation Based on Fuzzy Language Field

In this paper, we use fuzzy language field and the method of fuzzy integrative evaluation algorithm that instead of the traditional method of Analytic Hierarchy Process in the background of the enterprise innovation level rating. And develop a system of computer-assisted innovation evaluation for evaluating the enterprise innovation.

Bing-ru Yang, Hui Li, Wen-bin Qian, Yu-chen Zhang, Jian-wei Guo

Integration on Heterogeneous Data with Uncertainty in Emergency System

Aimed at the puzzle to realize the integration for heterogeneous data, this paper proposed a sort of data exchange model of heterogeneous database based on unified platform of middleware. Based on the mapping of model drive, the data exchange could be realized by a concrete model. Its thought was to express XML document being a tree composed by data object, in which each element type corresponded to an object in object pattern, namely there was mapping among patterns. The paper gave an example of power emergency processing system, the application effect shows that the speed of emergency event processing can enhance five to ten times and it is able to realize the exchange and integration for heterogeneous data easily.

Wei Huang, Kai-wen Chen, Chao Xiao

Random Fuzzy Unrepairable Warm Standby Systems

Usually, the lifetimes of components in operation and in warm standby are assumed to be random variables. The probability distributions of the random variables have crisp parameters. In many practical situations, the parameters are difficult to determine due to uncertainties and imprecision of data. So it is appropriate to assume the parameters to be fuzzy variables. In this paper, the lifetimes of components in operation and in warm standby are assumed to have random fuzzy exponential distributions, then reliability and mean time to failure (MTTF) of the warm standby systems are given. Finally, a numerical example is presented.

Ying Liu, Lin Wang, Xiao-zhong Li

Separation Axioms in $$\omega _{\alpha }$$ - $$opos$$

In this paper, concepts of

$$\omega _{\alpha }$$

-

$$T_i$$

,

$$(i=0,1,2,3,4)$$

sets are introduced in

$$\omega _{\alpha }$$

-order preserving spaces and their characteristic properties are studied. They consist a new complete system of separation axiom, which is proved to be a good extension of both classical and fuzzy theories. Finally, their relationships are established and their differences are discussed by some exact examples.

Xiu-Yun Wu, Li-Li Xie, Shi-Zhong Bai

The Application of FHCE Based on GA in EHVT

Fuzzy Hierarchy Comprehensive Evaluation (FHCE) as a common evaluation method of the combination of qualitative analysis and quantitative analysis has been widely used in social life. At present, one of fuzzy comprehensive evaluation research difficulties is how to reasonably determine the weight of evaluation index. The main issue of analytic hierarchy process (AHP) in itself is to determine the each elements weight of judgment matrix which is artificially assigned, so it has highly subjective one-sidedness. In view of the above problems this paper attempts to propose a new model of FHCE, that is to structure judgment matrix according to interval scale of [1, 9] in AHP, and use the standard genetic algorithm (GA) to calculate each elements weight of judgment matrix.

Ge Lin, Zhong-yuan Peng

Theory and Practice of Cooperative Learning in Mathematical Modeling Teaching

Against the problems such as that teamwork of mathematical modeling is not strong enough, based on the characteristics and inherent laws of mathematical modeling, combined with the characteristics of the students, this paper presents several strategies. To the basic theory of cooperative learning as a guide, starting from the connotation of cooperative learning of mathematical modeling, analyzing the main factors that impacting the cooperative learning of mathematical modeling, this paper makes several teaching strategies of the cooperative learning of mathematical modeling for the research about the teaching strategies that the cooperative learning improves the modeling interest in learning, academic performance and learning ability. Empirical students have shown that the implementation of cooperative learning has a positive impact on improving student’s modeling interest in learning, academic performance and learning ability and so on. In this way, we not only expand the theory of cooperative learning from high school to college, but also achieve the combine of theory and practice. It provides approach to improve student’s comprehensive ability.

Yu-bin Zhong, Yi-ming Lei, Xu-bin Wang, Lei Yang, Gen-hong Lin

A Discrete-Time $$Geo/G/1$$ G e o / G / 1 Retrial Queue with Preemptive Resume, Bernoulli Feedback and General Retrial Times

In this work, we consider a discrete-time

$$Geo/G/1$$

G

e

o

/

G

/

1

retrial queue with preemptive resume, Bernoulli feedback and general retrial times. We analyze the Markov chain underlying the considered queueing system and derive the generating functions of the system state, the orbit size and the system size distribution. Using probability generating function technique, some interesting and important performance measures are obtained. We also investigate the stochastic decomposition property and present some numerical examples.

Cai-Min Wei, Yi-Yan Qin, Lu-Xiao He

Stability Analysis of T-S Fuzzy Systems with Knowledge on Membership Function Overlap

A new approach for reducing the conservativeness in stability analysis and design of continuous-time T-S fuzzy control systems is proposed in this paper. Based on a fuzzy Lyapunov function together with knowledge on membership function overlap, previous stability and stabilization conditions are relaxed by the proposed approach. Both the stability and the stabilization conditions are written as linear matrix inequality (LMI) problems. Two examples are given to illustrate the effectiveness of the proposed approach.

Zhi-hong Miao

Application of T-S Fuzzy Model in Candidate-well Selection for Hydraulic Fracturing

Hydraulic fracturing (HF) is the key technology of increasing production and injection for low permeable reservoirs. The candidate-well selection for HF is essential to oil and gas wells stimulation potential evaluation, which is crucial to improve fracturing operation efficiency and reduce HF investment risk. The candidate-well selection model is a high dimension, nonlinear, strong coupling, multi-input single-output system. However, the conventional methods, such as production performance comparisons can not be easy to use for this nonlinear model. As a solution, the advanced methods such as T-S models in this paper can be effectively used in the candidate-well selection for HF. First, the subtractive clustering (SC) algorithm is employed to partition the fuzzy space of the given input–output data, which is adopted as the initial premise structure and parameters. Second, the clusters obtained on the first stage are used to initialize the fuzzy c-means (FCM) algorithm, which can obtain optimal cluster number and cluster centers. Third, the consequent parameters are identified by using the orthogonal least-squares (OLS) algorithm. Finally, the proposed approach is successfully applied to candidate-well selection for HF in Hechuan gas field in Sichuan basin, and validation results have demonstrated the effectiveness of the proposed method.

Xie Xiang-jun, Yu Ting
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