基于支持向量机的海战伤减员预测研究  

Research on Prediction of Manpower Loss Due to Naval War Injury Based on SVR

作　　者：任东彦 刘文宝 张凯丽 REN Dongyan;LIU Wenbao;ZHANG Kaili(Naval Training Base of Health Service,Navy Military Medical University,Shanghai 200433;Faculty of Health Service,Navy Military Medical University,Shanghai 200433)

机构地区：[1]海军军医大学海军卫勤训练基地,上海200433 [2]海军军医大学卫生勤务学系,上海200433

出　　处：《计算机与数字工程》2025年第1期84-89,95,共7页Computer & Digital Engineering

摘　　要：论文分析了影响海战伤减员的主要影响因素并对其进行量化,通过对二战以来64场海战相关数据进行训练,建立了基于SVR的海战伤减员预测模型;仿真结果对比分析表明:在解决海战伤减员小样本、非线性以及高维模式识别问题中,SVR具有更高的预测精度;结合军事背景,输入现有作战估计条件,采用训练好的SVR模型,即可对海战伤减员做出预测,从而为海战伤减员预测提供了一种新的计算方法。This paper analyzes and quantifies the main influencing factors of naval war injury,and establishes the predicted model based on SVR by training the data of 64 sea battles since World War II.The simulation results show that SVR has higher pre⁃dicted accuracy in solving the problems of small sample,non-linear and high-dimensional pattern recognition,combined with mili⁃tary background,by inputting the existing estimated conditions and using the model of SVR,manpower loss can be predicted,which provides a new method for manpower loss due to naval war injury.

关 键 词：支持向量机 海战 减员 预测 

分 类 号：U674[交通运输工程—船舶及航道工程]