郑州大学学报（理学版）2024，Vol.56Issue(1)：9-15,7.DOI:10.13705/j.issn.1671-6841.2022299
基于改进混合密度网络的毁伤效应预测方法
Prediction Method of Damage Effects Based on Improved Mixture Density Network
摘要
Abstract
A damage effect prediction method based on an improved mixture density neural network was proposed.The method aimed to solve the problem that current intelligent damage effect prediction meth-ods could only output point prediction results,but fail to quantify the uncertainty of damage effect predic-tion results.A more robust t distribution as a mixture component and a mixture density network was used to generate a probability density function that reflects the uncertainty in the prediction of damage effects.Interval prediction results could be obtained according to a given confidence level.Simulation experi-ments demonstrated that the probability density function obtained by the proposed method could more ac-curately fit Monte Carlo simulation results and better guide combat planning than existing damage effect prediction methods.关键词
混合密度网络/毁伤效应预测/t Location-Scale分布/区间预测Key words
mixture density network/damage effect prediction/t Location-Scale distribution/interval prediction分类
信息技术与安全科学引用本文复制引用
佘维,张人中,田钊,刘炜,孔德锋..基于改进混合密度网络的毁伤效应预测方法[J].郑州大学学报（理学版）,2024,56(1):9-15,7.基金项目
河南省重点研发与推广专项(212102310039,202102310554) （212102310039,202102310554）
河南省高等学校重点科研项目(20A520035). （20A520035）
