Training Neurofuzzy Networks with Participatory Learning

被引：0

作者：

Hell, Michel ^{[1
]}

Ballini, Rosangela ^{[2
]}

Costa, Pyramo, Jr. ^{[3
]}

Gomide, Fernando ^{[1
]}

机构：

[1] Univ Estadual Campinas, FEEC, DCA, BR-13083970 Campinas, SP, Brazil

[2] Univ Estadual Campinas, IE, DTE, BR-13083970 Campinas, SP, Brazil

[3] PPGEE, MG, PUC, BR-30535610 Belo Horizonte, MG, Brazil

来源：

NEW DIMENSIONS IN FUZZY LOGIC AND RELATED TECHNOLOGIES, VOL II, PROCEEDINGS | 2007年

基金：

巴西圣保罗研究基金会;

关键词：

Participatory Learning; Fuzzy Systems; Neurofuzzy Networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a new approach to adjust a class of neurofuzzy networks based on the idea of participatory learning. Participatory learning is a mean to learn and revise beliefs based on what is already known or believed. The performance of the approach is verified with the Box and Jenkins gas furnace modeling problem, and with a short-term load forecasting problem using actual data. Comparisons with alternative training procedures suggested in the literature are included to shown the effectiveness of participatory learning to train neurofuzzy networks.

引用

页码：231 / +

页数：2

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