Fuzzy Reasoning in Information, Decision and Control SystemsS.G. Tzafestas, Anastasios N. Venetsanopoulos Springer, 28 d’ag. 2007 - 568 pàgines Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is 'fuzzy control', where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as 'fuzzy expert sys tems', and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as 'fuzzy information processing', that is to bring fuzzy idea into informa tion processing systems. |
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Fuzzy Reasoning in Information, Decision and Control Systems S.G. Tzafestas,Anastasios N. Venetsanopoulos Previsualització limitada - 1994 |
Fuzzy Reasoning in Information, Decision and Control Systems S.G. Tzafestas,Anastasios N. Venetsanopoulos Previsualització no disponible - 2013 |
Fuzzy Reasoning in Information, Decision and Control Systems S. G. Tzafestas,Anastasios N. Venetsanopoulos Previsualització no disponible - 2014 |
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A₁ algorithm application of fuzzy approach approximate reasoning B₁ computed connectionist expert system considered control action control loop control variable controller output corresponding crisp defined defuzzification denotes dynamics Engineering error estimated evaluation example expert systems feature Figure FSMC fuzzy control systems fuzzy implication fuzzy inference fuzzy logic controller fuzzy network fuzzy numbers fuzzy reasoning fuzzy relation fuzzy rules fuzzy sets fuzzy subset fuzzy systems implemented Intelligent International joint knowledge base knowledge representation layer linguistic variables Mamdani matrix medium membership functions membership grades membership values multivalued neural network neuron nodes non-linear non-linear controllers obtained operations parameters pattern class Petri net PID controller problem procedure representation represented respectively rule base S.G. Tzafestas sample set sampled points Sets and Systems shown sliding mode control structure Sugeno T-norm Table torque trajectory universe of discourse vector velocity Zadeh
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Pàgina 3 - Stated informally, the essence of this principle is that as the complexity of a system increases, our ability to make precise and yet significant statements about its behavior diminishes until a threshold is reached beyond which precision and significance (or relevance) become almost mutually exclusive characteristics.
Referències a aquest llibre
A Guide to the Literature on Semirings and their Applications in Mathematics ... K. Glazek Previsualització limitada - 2002 |