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2004 | Buch

Introduction to Soft Computing Kapitel lesen Erstes Kapitel lesen

Soft Computing and its Applications in Business and Economics

verfasst von: Professor Rafik Aziz Aliev, Professor Bijan Fazlollahi, Professor Rashad Rafik Aliev

Verlag: Springer Berlin Heidelberg

Buchreihe : Studies in Fuzziness and Soft Computing

Enthalten in: Professional Book Archive

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Über dieses Buch

"Soft Computing and its Applications in Business and Economics," or SC-BE for short, is a work whose importance is hard to exaggerate. Authored by leading contributors to soft computing and its applications, SC-BE is a sequel to an earlier book by Professors R. A. Aliev and R. R. Aliev, "Soft Computing and Its Applications," World Scientific, 200l. SC-BE is a self-contained exposition of the foundations of soft computing, and presents a vast compendium of its applications to business, finance, decision analysis and economics. One cannot but be greatly impressed by the wide variety of applications - applications ranging from use of fuzzy logic in transportation and health case systems, to use of a neuro-fuzzy approach to modeling of credit risk in trading, and application of soft computing to e-commerce. To view the contents of SC-BE in a clearer perspective, a bit of history is in order. In science, as in other realms of human activity, there is a tendency to be nationalistic - to commit oneself to a particular methodology and relegate to a position of inferiority or irrelevance all alternative methodologies. As we move further into the age of machine intelligence and automated reasoning, we run into more and more problems which do not lend themselves to solution through the use of our favorite methodology.

Inhaltsverzeichnis

Frontmatter
1. Introduction to Soft Computing
Abstract
Artificial intelligence as a science has been existing for about 40 years now. The main problem of this science is replication of human reasoning processes and behavior with the aid of computers and other artificial devices as well as construction of machines simulating decision making by humans in imprecise and uncertain environments. In most cases these various areas, where precise models, methods, and algorithms for solving problems characterized by uncertainty are not available, are attributed to the field of artificial intelligence. Methods of artificial intelligence are based on two characteristic features:
1.
Use of information in symbolic form i.e. letters, words, phrases, signs, figures;
 
2.
Search with the aid of symbolic logic. When processing symbolic information, the computer converts the words and phrases to the form of binary digits. Then the computer recognizes or compares the sequences of such symbols (converted to digital form).
 
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
2. Constituent Methodologies of Soft Computing
Abstract
Let X be a classical set of objects, called the universe, whose generic elements are denoted x. Membership in a classical subset A of X is often viewed as a characteristic function ∝A from X to {0,1} such that
$$\propto (X) = \left\{ {\begin{array}{*{20}{c}} {1\quad iff\quad x \in A}\\ {0\quad iff\quad x \notin A} \end{array}} \right.$$
where {0,1} is called a valuation set; 1 indicates membership while 0 — nonmembership.
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
3. Emerging Combined Soft Computing Technologies
Abstract
Fuzzy logic [161] has been successfully applied in many areas, such as control of industrial processes, control of robotic manipulators, control of servo-motors, complex decision making, diagnostic systems and others [10,93,94,98]. When using fuzzy logic, input data in form of linguistic values are represented by membership functions which are used for defining fuzzy sets of crisp values and their corresponding membership degrees related to these sets. Many parameters of systems based on fuzzy logic should be defined with help of an expert. In the same time, however, the associated parameters construction processes are performed by the method of trial and error or some heuristic algorithms [143]. Moreover, a designer that knows the characteristics of the system also needs initial rules. Some researchers have suggested a number of mechanisms to generate fuzzy rules and developed methods of their modification on the basis of experience [131,134,140,141,142]. Among them we must distinguish the self-organizing fuzzy controller that is capable of forming and modifying fuzzy rules [134,142], the clustering algorithm for fuzzy partitioning the input data space [140], and the least square algorithm for defining a succession of parameters [140,141] that can be used to construct systems based on fuzzy logic.
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
4. Soft Computing Technologies in Business and Economic Forecasting
Abstract
One of the first explicit uses of neural networks for time series analysis was in 1987 when Lapedes and Farber demonstrated that feed-forward neural networks could be used for modeling deterministic chaos [15].
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
5. Soft Computing Based Decision Making and DSS
Abstract
A classical (crisp) linear programming problem can be written as
$$\begin{array}{l} \max imize\quad Z = cx\\ subject\,to\quad Ax \le b,\quad x \ge 0 \end{array}$$
(5.1)
where Z denotes the objective, Ax≤b represents the set of (rigid) constraints and x are the structural variables.
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
6. Soft Computing in Marketing
Abstract
Marketers often are interested in the decision rules the customers use when choosing and making a purchase. On evaluating the products the customers rely on various attributes such as price, quality etc. In other words a customer’s purchasing behavior frequently comes along with multiple-attribute decisions. On the other hand, the analysis of a customer’s purchasing behavior enables the possibility for customers to find better ways to offer products and improve marketing mixes [17].
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
7. Soft Computing Applications in Operations Management
Abstract
Problems in transportation logistics, such as routing, assignment, dispatching etc. are very complex combinatorial optimization problems and their solution is related with certain difficulties.
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
8. Soft Computing in Finance
Abstract
The stock market is very attractive due to high expected profit. On the other hand it is very risky. This creates a need for intelligent stock-trading systems that are intended to help the investors make realistic prediction for taking optimal decisions. Conventional approaches address Regression and Time Series Analysis methods for stock market prediction [5,14]. These methods do not give expected results in situations when the data are influenced by subjective factors such as psychological, macro-economical, or political issues. Also we cannot ignore those factors at all, because technical indexes only are not capable of proper description of a complicated real-world environment. An effective stock trading system must use both qualitative and quantitative factors.
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
9. Soft Computing in Electronic Business
Abstract
In an era of electronic commerce businesses and consumers have access to vast amounts of potentially important information. While this is beneficial for making informed decisions, the decision makers could easily become overwhelmed by the information, much of which may not be relevant. Thus, there is a pressing need for decision aiding tools that would effectively process, filter, and deliver the right information to the organizational and individual decision makers. In this work we argue that combination of DSS and agent technologies could prove a very powerful tool for rendering decision support in e-commerce application. We propose an architecture for a multi-agent DSS for e-commerce, and describe a prototype system for making on-line investment decisions.
Rafik Aziz Aliev, Bijan Fazlollahi, Rashad Rafik Aliev
Metadaten
Titel
Soft Computing and its Applications in Business and Economics
verfasst von
Professor Rafik Aziz Aliev
Professor Bijan Fazlollahi
Professor Rashad Rafik Aliev
Copyright-Jahr
2004
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-540-44429-9
Print ISBN
978-3-642-53588-8
DOI
https://doi.org/10.1007/978-3-540-44429-9