[1] KOOPMAN B O. The theory of search. Ⅲ. The optimum distribution of searching effort[J]. Operations Research, 1957, 5(5):613-626. [2] KRATZKE T M, STONE L D, FROST J R. Search and rescue optimal planning system[C]//Proceedings of the 201013th Conference on Information Fusion. Piscataway, NJ:IEEE, 2010:1-8. [3] BMT Cordah. Search And Rescue Information System (SARIS)[EB/OL].[2010-08-11]. http://www.bmtcordah.com/. [4] BERGER J, LO N, NOEL M. A new multi-target, multi-Agent search-and-rescue path planning approach[J]. International Journal of Computer, Information, Systems and Control Engineering, 2014, 8(6):902-912. [5] BERGER J, LO N. An innovative multi-Agent search-and-rescue path planning approach[J]. Computers and Operations Research, 2015, 53:24-31. [6] 邢胜伟.海上立体搜寻全局优化模型及仿真研究[D].大连:大连海事大学,2012:79-95. (XING S W. Research on global optimization model and simulation of joint aeronautical and maritime search[D]. Dalian:Dalian Maritime University, 2012:79-95.) [7] 郑宏喆,赵怀慈,王立勇.基于风压差翻转漂移模型的海上搜寻区域确定[J].中国航海,2016,39(4):102-107.(ZHENG H Z, ZHAO H C, WANG L Y. Determination of maritime search area based on leeway-jibing drift model[J]. Navigation of China, 2016, 39(4):102-107.) [8] 王光源,刘建东,章尧卿,等.海上遇险目标漂移与搜寻区域优化确定分析[J].舰船电子工程,2017,37(12):21-24.(WANG G Y, LIU J D, ZHANG Y Q, et al. Optimization analysis of the maritime distress target's drift and search area[J]. Ship Electronic Engineering, 2017, 37(12):21-24.) [9] 刘勇,贾庆轩,陈钢,等. 基于多目标粒子群优化算法的自由漂浮空间机器人负载最大化轨迹优化[J].机器人,2014,36(4):402-410.(LIU Y, JIA Q X, CHEN G, et al. Load maximization trajectory optimization for free-floating space robot using multi-objective particle swarm optimization algorithm[J]. Robot, 2014, 36(4):402-410.) [10] 李洁,张兆薇. 基于和声搜索算法和相关向量机的网络安全态势预测方法[J].计算机应用,2016,36(1):199-202.(LI J, ZHANG Z W. Network security situation prediction method based on harmony search algorithm and relevance vector machine[J]. Journal of Computer Applications, 2016, 36(1):199-202.) [11] LIU Z H, WEI H L, LIU K, et al. Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO[EB/OL].[2018-02-09]. http://eprints.whiterose.ac.uk/126906/1/Global%20Identification%20of%20Electrical%20Parameters%20(IEEE-TPEL%20Accepted%202018-01-23).pdf. [12] LIU Z H, WEI H L, ZHONG Q C, et al. Parameter estimation for VSI-Fed PMSM based on a dynamic PSO with learning strategies[J]. IEEE Transactions on Power Electronics, 2017, 32(4):3154-3165. [13] LIU Z H, WEI H L, ZHONG Q C, et al. GPU implementation of DPSO-RE algorithm for parameters identification of surface PMSM considering VSI nonlinearity[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2017, 5(3):1334-1345. [14] 欧阳海滨,高立群,邹德旋,等.和声搜索算法探索能力研究及其修正[J]. 控制理论与应用,2014,31(1):57-65.(OUYANG H B, GAO L Q, ZOU D X, et al. Exploration ability study of harmony search algorithm and its modification[J]. Control Theory and Applications, 2014, 31(1):57-65.) [15] 胡旺,YEN G G,张鑫. 基于Pareto熵的多目标粒子群优化算法[J]. 软件学报, 2014,25(5):1025-1050.(HU W, YEN G G, ZHANG X. Multiobjective particle swarm optimization based on Pareto entropy[J]. Journal of Software, 2014, 25(5):1025-1050.) [16] 匡芳君,徐蔚鸿,张思扬. 基于改进混沌粒子群的混合核SVM参数优化及应用[J].计算机应用研究, 2013,31(3):671-674.(KUANG F J, XU W H, ZHANG S Y. Parameter optimization and application of SVM with mixtures kernels based on improved chaotic particle swarm optimization[J]. Application Research of Computers, 2013, 31(3):671-674.) [17] FROST J R, STONE L D. Reviews of search theory:advances and applications to search and rescue decision support[R]. Washington, DC:United States Coast Guard, 2001. [18] 国际海事组织/国际民用航空组织. 国际航空和海上搜寻救助手册第二卷[M]. 北京:人民交通出版社,2002:148-154.(IMO/International Civil Aviation Organization. International Aeronautical and Maritime Search and Rescue Manual Ⅱ[M]. Beijing:China Communications Press, 2002:148-154.) [19] 陈志敏,薄煜明,吴盘龙,等.基于自适应粒子群优化的新型粒子滤波在目标跟踪中的应用[J].控制与决策,2013,28(2):193-200.(CHEN Z M, BO Y M, WU P L, et al. Novel particle filter algorithm based on adaptive particle swarm optimization and its application to radar target tracking[J]. Control and Decision, 2013, 28(2):193-200.) [20] 刘长平,叶春明.具有Lévy飞行特征的蝙蝠算法[J].智能系统学报,2013,8(3):240-246.(LIU C P, YE C M. Bat algorithm with the characteristics of Lévy flights[J]. CAAI Transactions on Intelligent Systems, 2013, 8(3):240-246.) |