Fuzzy Systems

P. Venkata Subba Reddy ¹

Affiliations
1 Department of Computer Science and Engineering, College of Engineering, Sri Venkateswara University, Tirupati, IN

Abstract

Zadeh defined fuzzy set with membership function A=μA(x ) for the proposition of the type “x is A”. Fuzzy set with single membership function is not sufficient to deal with uncertain information. The fuzzy set with two fuzzy membership functions will give more evidence to deal with uncertainty. In this paper, fuzzy set is defined by generalized fuzzy set A={μABelief(x), μDisbelief(x)} with the two fuzzy membership functions based on Belief and Disbelief. The fuzzy inference and the fuzzy reasoning are studied with generalized fuzzy set. The fuzzy conditional inference for "if … then …" and "if … then …  else" are discussed with two fuzzy membership functions, also Fuzzy Certainty Factor is defined with difference between "Belief" and "Disbelief" membership functions to made as single fuzzy membership function. An Medical Expert System is discussed as one of the applications of Generalized fuzzy set. In EMYCIN, Belief anf Disbelief are defined with Probability. In this paper, generalized fuzzy sets are discussed for EMYCIN.

Keywords

Fuzzy Logic, Generalized Fuzzy Theory, Fuzzy Membership Functions, Fuzzy Belief, Fuzzy Disbelief, Fuzzy Inference, Fuzzy Reasoning.

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P. Venkata Subba Reddy ¹

Affiliations
1 Department of Computer science and Engineering, College of Engineering, Sri Venkateswara University, Tirpathi, IN

Abstract

Medical Expert Systems is one of the challenging area in Artificial Intelligence in Medicine. Medical Expert Systems will act as domain expert (Doctor in Medical diagnosis. Usually information available to the medical diagnosis is inexact rather than exact. Medical Expert System has to deal with inexact information. The Medical inexact information is fuzzy rather than probable (likelihood). In this paper, Fuzzy logic and Fuzzy Knowledge Represention are discussed for Medical diagnosis. Medical Expert Systems and Fuzzy Medical Expert System (FMES) are discussed for Medical diagnosis. Examples are discussed with MYCIN and Prolog for Medical diagnosis. Medical diagnosis is distributed because the Medical information has to garter from various sources. The Fuzzy Medical Expert Systems are to be co-operated and co-ordinate in distributed environment in the distributed environment. Distributed Fuzzy Medical Expert System(DFMES) is studied for Medical diagnosis.

Keywords

Medical Knowledge Representation, Fuzzy Inference, Fuzzy Reasoning, Fuzzy Medical Expert Systems, Distributed Fuzzy Medical Reasoning.

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P. Venkata Subba Reddy ¹

Affiliations
1 Department of Computer Science and Engineering, College of Engineering, Sri Venkateswara University, IN

Abstract

Indian languages have long history and Sanskrit is the first language. Panini 's was the first to define Grammar for Sanskrit language with about 4000 rules in sixth century BC. These rules are containing the uncertainty. It is not possible to process Sanskrit Language with uncertainty. The uncertainty elimination in Panini‘s Sanskrit Grammar using the fuzzy logic is studied. In this paper fuzzy reasoning is proposed for Panini‘s Sanksrit Grammar. The Sanskrit languages is processed by translating in to English character set with logic programming for fuzzy reasoning.

Keywords

Panini‘s Sanskrit Grammar, Fuzzy Logic, Fuzzy Reasoning, Sanskrit Language Processing, Logic Programming, Om Transliteration.

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