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

R. Garcia, M. Sadiku
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引用次数: 1

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.
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拉普拉斯方程的两部分解:后端为马尔可夫链的自适应模糊系统前端
只提供摘要形式。本文阐述了模糊推理系统与蒙特卡罗方法的结合来求解拉普拉斯方程。模糊推理系统在控制系统领域有着广泛的应用。一般来说,模糊系统应用可能发生在专家知识可以转化为一组认知规则的地方。该方法与采用马尔可夫链的蒙特卡罗方法一起被认为是边值问题全域计算的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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