海军航空工程学院学报Issue(3)：235-238,256,5.DOI:10.7682/j.issn.1673-1522.2014.03.008
基于数据挖掘和小波神经网络的航材消耗预测方法
Prediction Method of Air Material Consumption Based on Data Mining and WNN
摘要
Abstract
In this paper, the correlation analysis on historical data of air material consumption was presented by using data mining technology, filting out the important material consumption data on the protection of aircraft flight, greatly reducing the amount of air material needed to forecast, and the influence between consumption materials relationship was quanti-fied. The principle of artificial fish swarm algorithm was analyzed, and the setting method of step parameter and visual field parameter was improved on the basis of it. The example results showed that the method of wavelet neural network could greatly reduce the prediction error of air material consumption, illustrated the effectiveness, feasibility and practicali-ty of the method.关键词
数据挖掘/小波神经网络/消耗预测Key words
data mining/wavelet neural network/consumption forecast分类
航空航天引用本文复制引用
孙臣良,郑伟,赵涛,陈洪光..基于数据挖掘和小波神经网络的航材消耗预测方法[J].海军航空工程学院学报,2014,(3):235-238,256,5.基金项目
国家部委技术基础基金资助项目 （）
