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Co-ordinated system of fuzzy logic and evolutionary programming based network reconfiguration for loss reduction in distribution systems

Co-ordinated system of fuzzy logic and evolutionary programm...

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： G.S. Wang P.Y. Wang Y.H. Song A.T. Johns Electric Power Research Institute Qinghe Beijing China School of Electronic and Electrical Engineering University of Bath Bath UK

In this paper, the co-ordinated system of fuzzy logic and evolutionary programming (FCEP), is presented. the main idea behind the FCEP is that a fuzzy mutation controller is implemented to adaptively update the mutation rate during the evolutionary process. the major advantage of the FCEP lies in its potential to quickly find the global optimal solution or the near optimal solutions under a series of constraints.

关键词： Fuzzy logic Genetic programming logic programming Switches Biological cells Genetic mutations Random number generation Genetic algorithms Testing Expert systems

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Fuzzy logic enhanced symmetric dynamic programming for speech recognition

Fuzzy logic enhanced symmetric dynamic programming for speec...

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： P. Mills J. Bowles Electrical and Computer Engineering University of South Carolina Columbia SC USA

Fuzzy logic allows effective decision making in the presence of uncertainty. Identifying spoken words, even in an ideal environment by a trained speaker, is a complex task filled with uncertainty. the speech waveform is nonlinear and variant, removing the possibility of simple analysis. Dynamic programming is a time normalization technique that allows static templates to be used to identify spoken words. Fuzzy logic enhancements enable the technique to handle noise and quantization errors better and improves classification accuracy. An important consequence of using a fuzzy based system is that the system's confidence in its identification can be used to accept the identification or to request further information.

关键词： Fuzzy logic Dynamic programming Speech recognition Uncertainty Speech analysis Flowcharts Milling machines Decision making Acoustic noise Quantization

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Fuzzy classes in object-oriented logic programming

Fuzzy classes in object-oriented logic programming

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： J.F. Baldwin T.P. Martin Advanced Computing Research Centre Department of Engineering Mathematics Queens Building University Walk Bristol UK

Object-oriented programming has been widely adopted as a powerful programming paradigm, enabling software engineers to design systems using structures which map naturally onto the problem domain. Using ideas from logic programming, a class definition can be treated as a logic theory, making it amenable to formal reasoning. Each class corresponds to a set of objects in the problem domain. We extend this idea, so that an object may have a degree of membership in more than one class, i.e. each class represents a fuzzy set of objects in the problem domain. Uncertainty is also allowed in data values and computational methods associated with objects. the problem of multiple inheritance is addressed by including methods for resolving conflict in class definitions. A system is being implemented in Fril, to allow development of fuzzy object oriented knowledge-based applications. this system is known as Fril++. the ideas are also applicable to other logic programming systems, assuming a method can be programmed at the object or meta-level to deal with uncertainty in terms, relations, and inference.

关键词： Fuzzy logic logic programming Object oriented programming Uncertainty Design engineering Power engineering and energy Systems engineering and theory Software design Fuzzy sets Fuzzy systems

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Analysis of the FLC with shrinking span membership functions

Analysis of the FLC with shrinking span membership functions

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： Cheng-Liang Chen Chung-Tyan Hsieh Sheng-Nan Wang Department of Chemical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)0780336453

this article aims to investigate the input-output parametric relationship of a class of crisp-type fuzzy logic controllers (FLCs) using various t-norm-sum-gravity inference methods. Two most frequently used t-norms, namely the standard intersection and the algebraic product, are applied in calculating the matching level of each control rule, and the summation operator and the center-of-gravity method are applied to evaluate the final crisp output. the explicit mathematical forms of reasoning surfaces are addressed. Reasoning surfaces of these crisp-type FLCs are proved to be composed of a two-dimensional multilevel relay, no matter which t-norm is used, and a local position-dependent nonlinear compensator with output pattern influenced by the t-norms selected.

关键词： Fuzzy logic Mathematical analysis Error correction Tellurium Chemical engineering Relays Fuzzy control Control systems Pattern analysis

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Using fuzzy logic and a hybrid genetic algorithm for metabolic modeling

Using fuzzy logic and a hybrid genetic algorithm for metabol...

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： J. Yen Bogju Lee J.C. Liao Center for Fuzzy Logic and Intelligent Systems Research Department of Computer Science Texas A and M University College Station TX USA Department of Chemical Engineering Texas A and M University College Station TX USA

the identification of metabolic systems such as metabolic pathways, enzyme actions, and gene regulations is a complex task due to the complexity of the system and limited knowledge about the model. Mathematical equations and ordinary differential equations have been used to capture the structure of the model, and the conventional optimization techniques have been used to identify the parameters of the model. In general, however, a pure mathematical formulation of the model is difficult due to parametric uncertainty and incomplete knowledge of mechanisms. In this paper, we propose a modeling approach that: (1) uses fuzzy rule-based model to augment algebraic enzyme models that are incomplete; and (2) uses a hybrid genetic algorithm to identify uncertain parameters in the model.

关键词： Fuzzy logic Genetic algorithms Biochemistry Fuzzy systems Equations Uncertainty Chemicals Biological system modeling Fuzzy reasoning Fuzzy sets

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A systematic tradeoff methodology for acquiring and validating imprecise requirements

A systematic tradeoff methodology for acquiring and validati...

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： J. Yen W.A. Tiao Xiaoqing Frank Liu Center for Fuzzy Logic Robotics and Intelligent SystemsDepartment of Computer Science Texas A and M University College Station TX USA Department of Computer Science Liniversity of Missouri Rolla MO USA

Requirement analysis is one of the most important phases in a software development process. Existing requirement methodologies are limited in specifying requirements that are usually vague and imprecise, and in supporting tradeoff analysis between the conflicting requirements. In this paper, the elasticity of imprecise requirements is captured using fuzzy logic to facilitate tradeoffs between conflicting requirements. Based on the marginal rate of substitution in decision science, we have developed a systematic approach to elicit the structures and the parameters of imprecise requirements, to validate the scheme for aggregating requirements, and to assess relative priorities of conflicting requirements.

关键词： Fuzzy logic Formal specifications Intelligent robots Computer science Elasticity Intelligent systems programming Cost function Bridges

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Writing fuzzy rules directly in a C++ source code

Writing fuzzy rules directly in a C++ source code

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： M. Costa de Oliveira M.A. Rocha Facury Analogica Instrumentacaoe Control Limited Belo Horizonte Minas Gerais Brazil Center of Research and Development in Electrical Engineering Federal University of Minas Gerais Belo Horizonte Minas Gerais Brazil

this paper presents the development of a library of C++ classes to create fuzzy logic algorithms to control MIMO systems. this library makes possible to write fuzzy rules directly in a C++ source code, using a natural language form. Rules like "If TEMPERATURE is HOT and PRESSURE is HIGH then POWER should be LOW" can be directly inserted into the source code of a fuzzy controller algorithm. the use of this library on a C++ programming environment is proposed as an excellent tool for developing fuzzy algorithms that have portability, simplicity, reusability, flexibility, low development cost and principally, capability to be embedded into a real control application.

关键词： Writing Libraries Fuzzy control Fuzzy logic Control systems MIMO Natural languages Pressure control Temperature control programming environments

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Evolving fuzzy neural networks for extracting rules

Evolving fuzzy neural networks for extracting rules

引用

IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： Susu Yao Chenjian Wei Zhenya He Department of Radio Engineering South-East University Nanjing China

ISBN: (纸本)0780336453

Two fuzzy neural network architectures are presented to realize knowledge extracting from input-output samples. the network parameters including the necessary membership functions of the input variables and the consequent parameters are tuned and identified using evolutionary programming. the trained networks are then pruned so that the general rules can be extracted and explained. the experimental results have shown that the similar classification rules can be obtained in comparison to that of other fuzzy neural approaches with less number of rules and membership functions.

关键词： Fuzzy neural networks Artificial neural networks Fuzzy logic Fuzzy systems Neural networks Pattern recognition Management training Inference algorithms Helium Input variables

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the structure of rules for general-purpose fuzzy reasoning

The structure of rules for general-purpose fuzzy reasoning

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： W. Siler J.J. Buckley Kemp-Carraway Heart Institute Birmingham AL USA Mathematics Department University of Alabama Birmingham Birmingham AL USA

the structure desirable for rules in rule-based systems for fuzzy reasoning, as distinct from fuzzy control, is elaborated. We point out that the formal structure of rules for fuzzy control, while adequate and economical for most fuzzy control applications, is both too complex and too restrictive for optimal use in fuzzy reasoning systems; in particular, the difficulty faced in handling fuzzy sets of categories in attempting to answer questions of the "what is it?" type when using fuzzy control rules is noted. Fuzzy reasoning rules should be able to employ discrete fuzzy sets of linguistic values, with members such as "Slow" and "Large", and also discrete fuzzy sets of categories, with members such as "Jeep" and "Quartz". the importance in multistep logic of considering prior data values is mentioned, together with a way of handling prior information based on monotonic fuzzy reasoning.

关键词： Fuzzy reasoning Fuzzy control Fuzzy sets Hybrid intelligent systems Fuzzy systems programming profession Heart Mathematics Knowledge based systems logic

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Fuzzy Q-learning for generalization of reinforcement learning

Fuzzy Q-learning for generalization of reinforcement learnin...

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： H.R. Berenji Div. of Comput. Sci. NASA Ames Res. Center Mountain View CA USA

Fuzzy Q-learning, introduced earlier by the author, is an extension of Q-learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental dynamic programming using a society of intelligent agents which are controlled at the top level by fuzzy Q-learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of fuzzy Q-learning through generalization of input space by using fuzzy rules and bridges the gap between Q-learning and rule based intelligent systems.

关键词： Fuzzy systems Fuzzy logic Fuzzy control Robots State estimation Application software Machine learning Machine learning algorithms Digital arithmetic Force control

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