Adaptive-neuron neural network to estimate rainfall

被引：0

作者：

Zhang, M ^{[1
]}

Xu, SX ^{[1
]}

Fulcher, J ^{[1
]}

机构：

[1] Christopher Newport Univ, PCSE, Newport News, VA 23606 USA

来源：

PROCEEDINGS OF THE 7TH JOINT CONFERENCE ON INFORMATION SCIENCES | 2003年

关键词：

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：

A new neural network model-called Adaptive-Neuron artificial neural Network (NAN)-is developed. An empirical justification of the neuron-adaptive activation function is given. A learning algorithm is derived to tune both the free parameters in the activation function and the connection weights between neurons. Based on the NAN model, a neuron-Adaptive artificial Neural network System for Estimating Rainfall (ANSER) using satellite data has been developed. Empirical results show that the NAN model performs about 1.8% better than the artificial Neural Network Group (NNG) model, and about 16.4% better than an ANN when using the rainfall estimate experimental database.

引用

页码：1581 / 1584

页数：4

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