Forecast of General Aviation Flying Hours Based on BP Neural Network

被引：0

作者：

Wen Jun ^{[1
]}

Zhang Qiaoyan ^{[1
]}

Tan Zhaoyang ^{[1
]}

Zhang Shuo ^{[1
]}

机构：

[1] Civil Aviat Flight Univ China, Coll Aviat Transportat Management, Guanghan 618307, Sichuan, Peoples R China

来源：

2012 2ND INTERNATIONAL CONFERENCE ON APPLIED ROBOTICS FOR THE POWER INDUSTRY (CARPI) | 2012年

关键词：

general aviation; flying hours; BP neural network; forecast; SOFT SENSORS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Basing on statistic data of general aviation flying hours of the year 1990-2009, using BP neural network to forecast general aviation flying hours. Analysis BP neural network's principle and normalize the data, establish neural network forecast model of general aviation flying hours time-series data, design the network parameters, and learn an train the history data of the year 1990-2007, test data of the year 2008 and 2009 and judge its accuracy.

引用

页码：1102 / 1105

页数：4

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