A comparative study of ANN online-offline learning algorithm

被引：0

作者：

Guo, HX ^{[1
]}

Zhu, KJ ^{[1
]}

Li, CP ^{[1
]}

Chen, X ^{[1
]}

机构：

[1] China Univ Geosci, Sch Management, Wuhan 430074, Peoples R China

来源：

Proceedings of the 2005 International Conference on Management Science & Engineering (12th), Vols 1- 3 | 2005年

关键词：

BP algorithm; genetic algorithm; GA-BP algorithm; online learning; offline learning;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper focused on the analysis of characteristics of BP, GA and GA-BP-APARTING algorithms, and proposed the GA-BP-NESTING algorithm. With a simulate case, the four algorithms are studied comparatively under both online and offline ANN learning modes, with the conclusion drawn that, (1) initializing weights will affect greatly ANN training and, (2) GA-BP-NESTING algorithm is the most satisfactory for offline ANN learning.

引用

页码：239 / 245

页数：7

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