Analogous fuzzy rule-based expert systems

Vadiee, Nader; Mohammad, R.; Akbarzadeh, T.

doi:10.1109/fuzzy.1996.552679

Cited by 6 publications

(5 citation statements)

References 2 publications

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“…The MFs used to describe linguistic knowledge are enormously subjective and context dependent (Vadiee, 1993). The input variables are assumed to be noninteractive, and the MFs for them are assigned based on the degree of similarity of a corresponding prototypical element.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy Systems Simulation

Ross¹

2010

Fuzzy Logic With Engineering Applications

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CHAPTER FUZZY SYSTEMS SIMULATIONAs 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. Lotfi Zadeh, 1973 Professor, Systems EngineeringThe real world is complex; complexity in the world generally arises from uncertainty in the form of ambiguity. Problems featuring complexity and ambiguity have been addressed subconsciously by humans since they could think; these ubiquitous features pervade most social, technical, and economic problems faced by the human race. Why then are computers, which have been designed by humans after all, not capable of addressing complex and ambiguous issues? How can humans reason about real systems, when the complete description of a real system often requires more detailed data than a human could ever hope to recognize simultaneously and assimilate with understanding? The answer is that humans have the capacity to reason approximately, a capability that computers currently do not have. In reasoning about a complex system, humans reason approximately about its behavior, thereby maintaining only a generic understanding about the problem. Fortunately, this generality and ambiguity are sufficient for human comprehension of complex systems. As the quote above from Dr Zadeh's principle of incompatibility suggests, complexity and ambiguity (imprecision) are correlated: "The closer one looks at a real-world problem, the fuzzier becomes its solution" (Zadeh, 1973).As we learn more and more about a system, its complexity decreases and our understanding increases. As complexity decreases, the precision afforded by computational Fuzzy L ogic w ith Engine e ring A pplic ations, Third EditionTimothy J. Ross

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Section: Discussionmentioning

confidence: 99%

Fuzzy Systems Simulation

Ross¹

2010

Fuzzy Logic With Engineering Applications

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“…The input fuzzy sets and output functions for navigation are shown in Figure 2 This is representative of the TSK model as described by Takagi and Sugeno in [23] and as shown by Ross in [17] and Vadiee in [24]. In Figure 2 the fuzzy sets are shown with their corresponding outputs of f 1 (x) and f 2 (x) which are used to calculate the preferences for navigation (P= [F 1 (x) F 2 (x)] = [b 1 b 2 ]).…”

Section: Determining the Prefeencesmentioning

confidence: 99%

Determining the preferences

Smith

2008

Proceedings of the 46th Annual Southeast Regional Conference on XX

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This paper discusses the process of placing a preference in a decision-making process. In a decision-making process, one may have to make a decision that will satisfy more than one objective. An important or preference may be place on an objective. Once the preference has been placed, the decision can be made. For the fuzzy logic based technique of multiobjective decision making, the same thing basically occurs. Here, one alternative or decision to be made will satisfy more than one objective to a certain degree. This research goes far beyond just using the equations of a fuzzy logic based technique in a program. It allows for calculations to occur for the objective fuzzy set and preference values. The programmer would set the equations for the objective fuzzy sets and preferences. But based on the distance an obstacle is from the robot and the width of a possible path, the values for the objectives and preferences would be calculated.

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“…Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php rule-base is known as aggregation of rules. In determining an aggregation strategy, the following two simple extreme cases exist (Vadiee (1993)):…”

Section: Aggregation Of Fuzzy Rulesmentioning

confidence: 99%