Two-part solution of Laplace´s equation: an adaptive fuzzy system front-end with a Markov chain back-end

Author

Garcia, Raymond C. ; Sadiku, Matthew N O

Author_Institution

Dept. of Electr. Eng., Georgia Inst. of Technol., State College, GA, USA

fYear

1998

fDate

24-26 Apr 1998

Firstpage

281

Lastpage

282

Abstract

Summary form only given. This paper illustrates the combination of a fuzzy inference system with a Monte Carlo method to solve Laplace´s equation. Fuzzy inference systems are found to be widely used in the area of control systems. As a general remark, fuzzy system applications can occur where expert knowledge can be translated into a cognitive set of rules. This tool along with a Monte Carlo method which employs Markov Chains is considered as an effective technique in whole field computation of boundary-value problems

Keywords

Laplace equations; Markov processes; Monte Carlo methods; adaptive systems; boundary-value problems; electrical engineering computing; fuzzy systems; inference mechanisms; Laplace equation; Markov chain; Monte Carlo method; adaptive fuzzy system; boundary-value problems; electrostatics; fuzzy inference system; Adaptive systems; Application software; Artificial neural networks; Boundary value problems; Control systems; Educational institutions; Fuzzy control; Fuzzy systems; Laplace equations; Potential well;

fLanguage

English

Publisher

ieee

Conference_Titel

Southeastcon '98. Proceedings. IEEE

Conference_Location

Orlando, FL

Print_ISBN

0-7803-4391-3

Type

conf

DOI

10.1109/SECON.1998.673350

Filename

673350