基于改进KELM的电子侦察卫星效能评估方法  

Effectiveness Evaluation Method of Electronic Reconnaissance Satellite Based on Improved KELM Algorithm

作　　者：饶世钧[1] 陈涛 洪俊[1] RAO Shijun;CHEN Tao;HONG Jun(Dept.of Information System of Dalian Navy Academy,Dalian 116018,China)

机构地区：[1]海军大连舰艇学院信息系统系,辽宁大连116018

出　　处：《火力与指挥控制》2022年第11期71-75,共5页Fire Control & Command Control

摘　　要：针对水面舰艇编队对海作战背景下军用电子侦察卫星效能评估方法不完善不合理的问题,在分析电子侦察卫星支援舰艇编队对海作战流程的基础上,根据指标体系构建原则,建立了电子侦察卫星效能评估指标体系,在核极限学习机(KELM)算法中融入萤火虫麻雀算法(FASSA),优化了KELM算法的核参数G和正则化系数C,改进了基于KELM的电子侦察卫星效能评估方法,提出了FASSA-KELM效能评估模型,并通过具体实例仿真验证了效能评估模型的有效性和准确性。仿真结果表明,所构建的效能评估方法能够为电子侦察卫星效能评估提供理论支撑和方法借鉴。As the effective ness evaluation method of military electronic reconnaissance satellite is imperfect and unreasonable under the background of anti-sea peration of formation,on the base of analysis of the anti-sea operation flow of support vessel formation of the electronic reconnaissance satellite,according to the principle of index system construction,the author constructs the electronic reconnaissance satellite operation effectiveness evaluation index system is constructed. The KELM algorithm’s nuclear parameter "G" and the regularization coefficient "C" are optimized and the electronic reconnaissance satellite operation effectiveness evaluation method based on KELM is improved by incorporating the Firefly Sparrow Algorithm(FASSA)into the Kernel Extreme Learning Machine(KELM)algorithm. The FASSA-KELM effectiveness evaluation model is proposed and the effectiveness and accuracy of the model is verified it through specific example simulation. The simulation result shows that the constructed effectiveness evaluation method can provide theoretical support and method reference for the effectiveness evaluation of electronic reconnaissance satellites.

关 键 词：电子侦察卫星 效能评估 核极限学习机 萤火虫算法 麻雀算法 

分 类 号：E953[军事—军事工程] E917