基于GA-SVM的舰船装备临修经费需求预测模型
发布时间：2018-12-07 18:15
【摘要】：针对舰船装备临修经费需求预测得不到满意解的问题,运用遗传算法将SVM相应的参数进行优化,建立了基于GA-SVM的舰船装备临修经费预测模型.通过将GA-SVM模型与BP神经网络模型的预测结果进行对比分析,结果表明:GASVM的预测效果更优异,对舰船装备临修经费需求预测有更好的参考意义.
[Abstract]:In order to solve the problem that the demand prediction of warship equipment temporary repair expenses can not be satisfactorily solved, the genetic algorithm is used to optimize the corresponding parameters of SVM, and a prediction model of warship equipment temporary repair expenses based on GA-SVM is established. By comparing the prediction results of GA-SVM model and BP neural network model, the results show that the prediction effect of GASVM is more excellent, and it has better reference significance for forecasting the demand of warship equipment temporary repair expenses.
【作者单位】： 海军工程大学装备经济管理系;
【基金】：国防科研重点研究项目资助
【分类号】：O212.1;TP18
本文编号：2367620
[Abstract]:In order to solve the problem that the demand prediction of warship equipment temporary repair expenses can not be satisfactorily solved, the genetic algorithm is used to optimize the corresponding parameters of SVM, and a prediction model of warship equipment temporary repair expenses based on GA-SVM is established. By comparing the prediction results of GA-SVM model and BP neural network model, the results show that the prediction effect of GASVM is more excellent, and it has better reference significance for forecasting the demand of warship equipment temporary repair expenses.
【作者单位】： 海军工程大学装备经济管理系;
【基金】：国防科研重点研究项目资助
【分类号】：O212.1;TP18
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