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
收藏
页码：1102 / 1105
页数：4
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