Application of Particle Swarm Optimization Based on Neural Network for Artillery Range Prediction
學年 103
學期 1
出版（發表）日期 2014-11-30
作品名稱 Application of Particle Swarm Optimization Based on Neural Network for Artillery Range Prediction
作品名稱（其他語言）
著者 Yi-Wei Chen, Yung-Lung Lee, Chien-Chun Kung
單位
出版者
著錄名稱、卷期、頁數 16(4), 73-80.
摘要 The firepower of artillery is one of main factors to influence the war effectiveness. Traditionally, the army utilizes the firing table to modify the artillery range, but the fabrication of firing table of artillery costs a lot of time and ammunition. In this study, some firing data of artillery are utilized to train the back-propagation neural network for artillery range prediction. Particle swarm optimization is utilized to increase the training speed of neural network and avoid getting stuck in local extreme. Besides, the orthogonal array is used to decrease the requirement of firing data and the proposed method is compared with the traditional back-propagation neural networks. Simulation results verify that the proposed method can not only increase the training speed of neural network but also have the satisfied performance of range prediction, and the mean absolute percentage error can approach to 1.173%. The proposed method in this paper is usable for artillery range prediction and feasible for application in the army.
關鍵字 Neural network, particle swarm optimization, artillery, orthogonal array.
語言 en
ISSN 1454-8658
期刊性質 國外
收錄於 SSCI
產學合作
通訊作者 Yi-Wei Chen
審稿制度 1
國別 ROU
公開徵稿
出版型式 ,電子版