Humans have always been hopeless at predicting the future…most people now generally agree that the margin of viability in prophecy appears to be 1 ten years. Even sophisticated research endeavours in this arena tend ...
ISBN:
(数字)9783540399728
ISBN:
(纸本)9783540211532;9783642059421
Humans have always been hopeless at predicting the future…most people now generally agree that the margin of viability in prophecy appears to be 1 ten years. Even sophisticated research endeavours in this arena tend to go 2 off the rails after a decade or so. The computer industry has been particularly prone to bold (and often way off the mark) predictions, for example: ‘I think there is a world market for maybe five computers’ Thomas J. Watson, IBM Chairman (1943), ‘I have traveled the length and breadth of this country and talked with the best people, and I can assure you that data processing is a fad that won’t last out the year’ Prentice Hall Editor (1957), ‘There is no reason why anyone would want a computer in their home’ Ken Olsen, founder of DEC (1977) and ‘640K ought to be enough for anybody’ Bill Gates, CEO Microsoft (1981). 3 The field of Artificial Intelligence – right from its inception – has been particularly plagued by ‘bold prediction syndrome’, and often by leading practitioners who should know better. AI has received a lot of bad press 4 over the decades, and a lot of it deservedly so. How often have we groaned in despair at the latest ‘by the year-20xx, we will all have…(insert your own particular ‘hobby horse’ here – e. g.
“Fuzzy Control - the revolutionary computer technology that is changing our world” - these and other headlines could be read when in the early 90’s news from Japan came over telling us about the success of fuzzy co...
ISBN:
(数字)9783540317661
ISBN:
(纸本)9783540317654;9783642068638
“Fuzzy Control - the revolutionary computer technology that is changing our world” - these and other headlines could be read when in the early 90’s news from Japan came over telling us about the success of fuzzy controllers. The idea which was put into practice had been suggested by Lot? A. Zadeh in Berkeley in 1965. It had been developed and tested in some practical - plications, especially in Europe. In Japan fuzzy control was celebrated as a technology re?ecting the Japanese way of thinking by its unsharpness and - plicitoverlappingofseveralstatements. Anewtechnologyboomwaspredicted for Japan which would make Europe lose ground. Consequently, this news created unrest. Research projects were initiated and development departments were engaged to translate fuzzy control into products. Adversaries and supporters hurried up to inform themselves and intensely discussed whether the “conventional” or the fuzzy control were the better alternative. Finally, the excitement cooled down since in recent years fuzzy control was analyzed fromthe classical pointofview. Thus,amoreobjective evaluation of its strong and weak points was possible. Furthermore, it was shown how fuzzy systems could be put to use in the steering level which is the level above the control loop, especially in interaction with other methods of softcomputing and arti?cial intelligence. Based on these fundamentals, the aim of this book is to support the convenient use of fuzzy controllers and fuzzy systems in the branch of control engineering and automation systems.
This book presents the synthesis and analysis of fuzzy controllers and its application to a class of mechanical systems. It mainly focuses on the use of type-2 fuzzy controllers to account for disturbances known as ha...
ISBN:
(数字)9783030031343
ISBN:
(纸本)9783030031336
This book presents the synthesis and analysis of fuzzy controllers and its application to a class of mechanical systems. It mainly focuses on the use of type-2 fuzzy controllers to account for disturbances known as hard or nonsmooth nonlinearities. The book, which summarizes the authors’ research on type-2 fuzzy logic and control of mechanical systems, presents models, simulation and experiments towards the control of servomotors with dead-zone and Coulomb friction, and the control of both wheeled mobile robots and a biped robot. Closed-loop systems are analyzed in the framework of smooth and nonsmooth Lyapunov functions.
We describe in this book, new methods for intelligent manufacturing using softcomputing techniques and fractal theory. softcomputing (SC) consists of several computing paradigms, including fuzzy logic, neural networ...
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ISBN:
(数字)9783790817669
ISBN:
(纸本)9783790815474;9783662002964
We describe in this book, new methods for intelligent manufacturing using softcomputing techniques and fractal theory. softcomputing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems. Fractal theory provides us with the mathematical tools to understand the geometrical complexity of natural objects and can be used for identification and modeling purposes. Combining SC techniques with fractal theory, we can take advantage of the "intelligence" provided by the computer methods and also take advantage of the descriptive power of the fractal mathematical tools. Industrial manufacturing systems can be considered as non-linear dynamical systems, and as a consequence can have highly complex dynamic behaviors. For this reason, the need for computational intelligence in these manufacturing systems has now been well recognized. We consider in this book the concept of "intelligent manufacturing" as the application of softcomputing techniques and fractal theory for achieving the goals of manufacturing, which are production planning and control, monitoring and diagnosis of faults, and automated quality control. As a prelude, we provide a brief overview of the existing methodologies in softcomputing. We then describe our own approach in dealing with the problems in achieving intelligent manufacturing. Our particular point of view is that to really achieve intelligent manufacturing in real-world applications we need to use SC techniques and fractal theory.
The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriat...
ISBN:
(数字)9783790817744
ISBN:
(纸本)9783790815238;9783790825183
The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem. Motivation. Researchers have accumulated much evidence on the impor tance of appropriate representations for the efficiency of AI systems. The same problem may be easy or difficult, depending on the way we describe it and on the search algorithm we use. Previous work on the automatic im provement of problem descriptions has mostly been limited to the design of individual learning algorithms. The user has traditionally been responsible for the choice of algorithms appropriate for a given problem. We present a system that integrates multiple description-changing and problem-solving algorithms. The purpose of the reported work is to formalize the concept of representation and to confirm the following hypothesis: An effective representation-changing system can be built from three parts: • a library of problem-solving algorithms; • a library of algorithms that improve problem descriptions; • a control module that selects algorithms for each given problem.
This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete in...
ISBN:
(数字)9783319390147
ISBN:
(纸本)9783319390123;9783319817934
This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.
In the beginning of 1983, I came across A. Kaufmann's book "Introduction to the theory of fuzzy sets" (Academic Press, New York, 1975). This was my first acquaintance with the fuzzy set theory. Then I tr...
ISBN:
(数字)9783790818703
ISBN:
(纸本)9783790812282;9783790824636
In the beginning of 1983, I came across A. Kaufmann's book "Introduction to the theory of fuzzy sets" (Academic Press, New York, 1975). This was my first acquaintance with the fuzzy set theory. Then I tried to introduce a new component (which determines the degree of non-membership) in the definition of these sets and to study the properties of the new objects so defined. I defined ordinary operations as "n", "U", "+" and "." over the new sets, but I had began to look more seriously at them since April 1983, when I defined operators analogous to the modal operators of "necessity" and "possibility". The late George Gargov (7 April 1947 - 9 November 1996) is the "god father" of the sets I introduced - in fact, he has invented the name "intu itionistic fuzzy", motivated by the fact that the law of the excluded middle does not hold for them. Presently, intuitionistic fuzzy sets are an object of intensive research by scholars and scientists from over ten countries. This book is the first attempt for a more comprehensive and complete report on the intuitionistic fuzzy set theory and its more relevant applications in a variety of diverse fields. In this sense, it has also a referential character.
In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzz...
ISBN:
(数字)9783540323884
ISBN:
(纸本)9783540250333;9783642421334
In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic because probabilities must add to one. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory.
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