Comparative Analysis of Methods for Determining Number of Hidden Neurons in Artificial Neural Network

被引：0
|
作者：
Vujicic, Tijana [1 ]
Matijevic, Tripo [1 ]
Ljucovic, Jelena [1 ]
Balota, Adis [1 ]
Sevarac, Zoran [2 ]
机构：
[1] Univ Mediterranean, Fac Informat Technol, Vaka Durovica Bb, Podgorica 81000, Montenegro
[2] Univ Belgrade, Fac Org Sci, Jove Ilica 154, Belgrade 11000, Serbia
来源：
CENTRAL EUROPEAN CONFERENCE ON INFORMATION AND INTELLIGENT SYSTEMS (CECIIS 2016) | 2016年
关键词：
artificial neural networks; hidden neurons; methods; test error; comparison;
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：
Neurons in an artificial neural network are grouped in three layers: input, output and hidden layer. Determination of an optimal number of neurons in hidden layer is one of the major difficulties in the process of creating artificial neural network topology. The main goal of this paper is to explore and compare existing methods for determining number of hidden neurons. The research is conducted on two separate datasets with different number of input values and different number of training pairs.
引用
收藏
页码：219 / 223
页数：5
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