Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

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Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download. The idea about this book has been on the author’s mind for almost a decade but it was only about a couple of years ago when the underlying research process was actually started. The reason for this delay has been the insufficient spare time for research being a lecturer in a ‘new’ UK university where the emphasis is mainly on teaching. And maybe this book would have never been written if the author had not been presented with the chance of developing new teaching modules in fuzzy logic that have given him food for thought in a research related context and have helped him combine efficiently his teaching and research activities.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

The title of this book may sound too specialised but it has a much wider meaning. Fuzzy systems are any systems for modelling, simulation, control, prediction, diagnosis, decision making, pattern recognition, image processing, etc. which use fuzzy logic. Although fuzzy logic is an advanced extension of binary logic, the latter is still used predominantly today. The main reason for this anachronism is the high level of complexity that is usually associated with the use of fuzzy logic. So, if we were able to solve this problem by means of a suitable complexity management approach, fuzzy logic would gradually replace binary logic. In this context, the book is aimed at anyone who wants to explore new possibilities for using fuzzy logic more effectively and more efficiently.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

Complexity has always been an important attribute in research methods. Even nowadays, in the age of supercomputers capable of performing computations at a very high speed, there are still open problems in many research areas which are due to computational complexity, and in particular, to the lack of adequate methods for managing this complexity. For example, some large scale problems in cosmology and genetics are still unsolvable within a reasonable time with the computational power available at present. In the case of threat from terrorism or natural disasters, the amount of information that is relevant to the decision making process can be so large that it may not be possible to process this information reliably within a reasonable time even with the help of the fastest computers.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

We could possibly wait for computer technology to become more powerful to hopefully cope with the current challenges of complexity. Unfortunately, this process may take too long, and if and when it has been finally completed, the expected result may still be quite unreliable. The reason for this is that complexity as an attribute of the world that we live in has not only a quantitative dimension in terms of number and scale but also a qualitative dimension in terms of uncertainty and ambiguity. And until we learn how to deal with the qualitative aspects of complexity, we may never be in the position to solve some of the current problems however advanced the computer technology is.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

Also, we must bear in mind that efficiency of computer software usually has a much greater impact on computational times associated with large scale problems than the speed of computer hardware on which the software is running. So, if we want to tackle successfully the current challenges of complexity, we need to be able to develop and implement efficient and intelligent computational algorithms. These algorithms must be capable of not only dealing with the quantitative aspects of complexity on the basis of their efficiency but also with its qualitative aspects by means of their intelligence.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

In this context, fuzzy systems in the form of rule bases are possibly the best tool available for accounting qualitative aspects of complexity such as the uncertainty of the environment. However, the processes of fuzzification, inference and defuzzification usually make these systems suffer from some quantitative aspects of complexity such as the large number of fuzzy rules and associated operations on the fuzzy membership functions of the inputs and the outputs. The focus of this book is on the management of complexity in fuzzy rule based systems.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

This problem has been pushed from a marginal location into the mainstream of fuzzy logic research in recent years. The reason for this move is due to the ever more increasing demand for using fuzzy logic not only for small scale domestic purposes but also in large scale industrial and other applications. As a result, many papers and books on fuzzy logic have started to discuss the complexity aspects of the proposed methods in separate paragraphs or even whole sections. Moreover, a number of specific methods for complexity reduction in fuzzy systems have already been developed and used. This work is possibly a first attempt to deal with the problems of complexity in fuzzy rule based systems at a monographic level. The underlying philosophy is based on the idea of managing complexity rather than only reducing it.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

In this context, management is viewed as a group of activities such as perception, understanding, and analysis of complexity with the intention of simplifying it formally in a universal and systematic way. This type of approach is quite different from most of the existing complexity reduction methods, which are usually characterised by a limited application scope and empirical nature. In fact, many of these methods simplify the complexity in fuzzy systems by actually ignoring it without adequate justification and with the hope that the resultant simplified system would behave similarly to the original complex one.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

As opposed to the complexity reduction methods mentioned above, this book does not rely on semi-mechanistic simplifications and hopes for good luck in a gamble. It is based on the assumption that the inherent redundancy in fuzzy systems should be exploited not by empirical trials but through a sound and formal systematic process. This redundancy and the resulting complexity are attributes of the virtual fuzzy world created by us for the purpose of dealing with the uncertainty in the real crisp world.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

So, it is only up to us to identify this redundancy accurately, remove it safely and then arrive quickly at the desired destination in the real world once the job has been done. It may look a bit like the plot in the famous movie ‘The Matrix’ The author would like to thank some people and institutions without whom this book possibly would not have been what it is. He is very grateful to Prof Robert Babuska from the Systems and Control Centre at the Delft University of Technology, The Netherlands, for the enlightening discussions on the topic, and to the Editor-in-chief for this book series Prof Janusz Kacprzyk for the kind invitation to submit this work which had a stimulating effect on the overall research and writing process.

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

Complexity Management in Fuzzy Systems by Alexander Gegov pdf free download

 

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