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23 results on '"Mandal, Ajit K."'

1. Fuzzy Rule Extraction Using Robust Particle Swarm Optimization

Author

Mukhopadhyay, Sumitra, Mandal, Ajit K., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wang, Jun, editor, Yi, Zhang, editor, Zurada, Jacek M., editor, Lu, Bao-Liang, editor, and Yin, Hujun, editor

Published
2006
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9. Uncertainty management in expert systems using fuzzy Petri nets

Author

Konar, Amit and Mandal, Ajit K.

Subjects
Expert systems -- Research, Fuzzy systems -- Research, Petri nets -- Research, Uncertainty (Information theory) -- Research, Business, Computers, Electronics, Electronics and electrical industries
Abstract

The paper aims at developing new techniques for uncertainty management in expert systems for two generic class of problems using fuzzy Petri net that represents logical connectivity among a set of imprecise propositions. One class of problems addressed in the paper deals with the computation of fuzzy belief of any proposition from the fuzzy beliefs of a set of independent initiating propositions in a given network. The other class of problems is concerned with the computation of steady-state fuzzy beliefs of the propositions embedded in the network, from their initial fuzzy beliefs through a process called belief-revision. During belief-revision, a fuzzy Petri net with cycles may exhibit 'limitcycle behavior' of fuzzy beliefs for some propositions in the network. No decisions can be arrived at from a fuzzy Petri net with such behavior. To circumvent this problem, techniques have been developed for the detection and elimination of limitcycles. Further, an algorithm for selecting one evidence from each set of mutually inconsistent evidences, referred to as nonmonotonic reasoning, has also been presented in connection with the problems of belief-revision. Finally, the concepts proposed for solving the problems of belief-revision have been applied successfully for tackling imprecision, uncertainty, and nonmonotonicity of evidences in an illustrative expert system for criminal investigation. Index Terms - Belief propagation, belief revision, expert systems, fuzzy belief, fuzzy Petri nets, limitcycles, nonmonotonic reasoning, reachability, stability, uncertainty management.

Published
1996

17. Fuzzy Rule Extraction Using Robust Particle Swarm Optimization.

Author

Wang, Jun, Yi, Zhang, Zurada, Jacek M., Lu, Bao-Liang, Yin, Hujun, Mukhopadhyay, Sumitra, and Mandal, Ajit K.

Abstract

Automatic fuzzy rule extraction assumes the realization of fuzzy if-then rules using a pre-assigned structure rather than an optimal one. In this paper, Particle Swarm Optimization (PSO) is used to simultaneously evolve the structure and the parameters of the fuzzy rule base. However, the existing PSO based adaptation employs randomness, which makes the rate of convergence dependent on the initial states and the end result can not be reproduced repeatedly with a pre-assigned value of iterations. The algorithm has been modified by removing the randomness in parameter learning, making it very robust. The scheme provides the flexibility in extracting the optimal set of fuzzy rules for a prescribed residual error in function approximation and prediction. Simulation studies and the comprehensive analysis demonstrate that an efficient learning technique as well as the structure development of the fuzzy system, can be achieved by the proposed approach. [ABSTRACT FROM AUTHOR]

Published
2006
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