Evolving neural networks for chlorophyll-a prediction

被引：2
|
作者：
Yao, X [1 ]
Liu, Y [1 ]
机构：
[1] Univ Birmingham, Sch Comp Sci, Birmingham B15 2TT, W Midlands, England
来源：
ICCIMA 2001: FOURTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, PROCEEDINGS | 2001年
关键词：
D O I：
10.1109/ICCIMA.2001.970465
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 studies the application of evolutionary artificial neural networks to chlorophyll-a prediction in Lake Kasumigaura. Unlike previous applications of artificial neural networks in this field, the architecture of the artificial neural network is evolved automatically rather than designed manually. The evolutionary system is able to find a near optimal architecture of the artificial neural network for the prediction task. Our experimental results have shown that evolved artificial neural networks are very compact and generalise well. The evolutionary system is able to explore a large space of possible artificial neural networks and discover novel artificial neural network's for solving a problem.
引用
收藏
页码：185 / 189
页数：5
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