ARTIFICIAL NEURAL NETWORK FOR ANALYSIS OF THE TRAFFIC FLOW

被引：0

作者：

Zenina, Nadezhda ^{[1
]}

Borisov, Arkady ^{[1
]}

机构：

[1] Riga Tech Univ, Fac Comp Sci & Informat Technol, LV-1658 Riga, Latvia

来源：

16TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MENDEL 2010 | 2010年

关键词：

forecasting; neural networks; sensitivity analysis; weight connections analysis; weights analysis;

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：

Traffic flow intensity forecasting is an integral part of the transport planning of the city An efficient flow forecast enables obtaining a more reliable prospect of the future. This paper describes the predictor of the traffic flow on the basis of the artificial neural network There is shown a practical example of the forecast based on existing data, collected in the city of Riga. An analysis of the solution sensitivity and of weight connections was performed for evaluation of the accuracy and truthfulness of the model. The testing of the predictor on one week data has demonstrated satisfactory quality of the forecast.

引用

页码：161 / 165

页数：5

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