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References
1
Ahmad G, Alanazi S, Alruwaili M, et al. Intelligent ammunition detection and classification system using convolutional neural network. Comput Mater Continua 2021;67(2):2585–600.
2
Voskuijl M. Performance analysis and design of loitering munitions: A comprehensive technical survey of recent developments. Def Technol 2022;18(3):325–43.
3
Jiang F, Chaofei H. The Russian army KUB-BLA loitering munitions accurately hit the Ukrainian infantry squad, and only one person of the Ukrainian army survived [Internet]. Heilongjiang: Baijiahao public platforms;2022 [cited 2022 Dec 9]. Available from: https://baijiahao.baidu.com/s?id=1734488826006318503&wfr=spider&for=pc.
4
Liu DW, Lee MC, Wu D. A node-to-node location verification method. IEEE Trans Ind Electron 2010;57(5):1526–37.
5
Lee JY, Scholtz RA. Ranging in a dense multipath environment using an UWB radio link. IEEE J Sel Areas Commun 2006;20(9):1677–83.
6
Zhang Y, Chen YH, Liu Y. Towards unique and anchor-free localization for wireless sensor networks. Wirel Pers Commun Int J 2012;63(1):261–78.
7
Gui LQ, Val T, Wei A, et al. Improvement of range-free localization technology by a novel DV-hop protocol in wireless sensor networks. Ad Hoc Netw 2015;24:55–73.
8
Gui LQ, Xiao F, Zhou Y, et al. Connectivity based DV-hop localization for Internet of Things. IEEE Trans Veh Technol 2020;69(8):8949–58.
9
Liu JP, Liu M, Du XJ, et al. An improved DV-Hop algorithm for wireless sensor networks based on neural dynamics. Neurocomputing 2022;491(C):172–85.
10
Rajakumar R, Amudhavel J, Dhavachelvan P, et al. GWO-LPWSN: Grey wolf optimization algorithm for node localization problem in wireless sensor networks. J Comput Netw Commun 2017;2017:1–10.
11
Wan YT, Zhong YF, Ma AL, et al. An accurate UAV 3-D path planning method for disaster emergency response based on an improved multiobjective swarm intelligence algorithm. IEEE Trans Cybern 2023;53(4):2658–71.
12
Fernandez-Martinez JL, Garcia-Gonzalo E. Stochastic stability analysis of the linear continuous and discrete PSO models. IEEE Trans Evol Comput 2011;15(3):405–23.
13
Seyyedabbasi A, Kiani F. I-GWO and Ex-GWO: Improved algorithms of the Grey Wolf Optimizer to solve global optimization problems. Eng Comput 2021;37(1):509–32.
14
Thom de Souza RC, de Macedo CA, dos Santos CL, et al. Binary coyote optimization algorithm for feature selection. Pattern Recognit 2020;107:107470.
15
Pierezan J, Maidl G, Massashi Yamao E, et al. Cultural coyote optimization algorithm applied to a heavy duty gas turbine operation. Energy Convers Manag 2019;199:111932.
16
Fouad MM, Hafez AI, Hassanien AE. Optimizing topologies in wireless sensor networks: A comparative analysis between the Grey Wolves and the Chicken Swarm Optimization algorithms. Comput Netw 2019;163:106882.
17
Lim WH, Mat Isa NA. Two-layer particle swarm optimization with intelligent division of labor. Eng Appl Artif Intell 2013;26(10):2327–48.
18
Eldosouky A, Ferdowsi A, Saad W. Drones in distress: A game-theoretic countermeasure for protecting UAVs against GPS spoofing. IEEE Internet Things J 2020;7(4):2840–54.
19
Mirjalili S, Mirjalili SM, Lewis A. Grey wolf optimizer. Adv Eng Softw 2014;69:46–61.
20
Zhang XM, Wang X, Kang Q. Hybrid grey wolf optimizer with artificial bee colony and its application to clustering optimization. Acta Electronica Sinica 2018;46(10):2430–42 [Chinese].
21
Zhang XM, Kang Q, Cheng JF, et al. A novel hybrid algorithm based on biogeography-based optimization and grey wolf optimizer. Appl Soft Comput 2018;67:197–214.
22
Teng ZJ, Lv JL, Guo LW. An improved hybrid grey wolf optimization algorithm. Soft Comput A Fusion Found Methodol Appl 2019;23(15):6617–31.
23
Arora S, Singh H, Sharma M, et al. A new hybrid algorithm based on grey wolf optimization and crow search algorithm for unconstrained function optimization and feature selection. IEEE Access 2019;7:26343–61.
24
Purushothaman R, Rajagopalan SP, Dhandapani G. Hybridizing Gray Wolf Optimization (GWO) with Grasshopper Optimization Algorithm (GOA) for text feature selection and clustering. Appl Soft Comput 2020;96:106651.
25
Pierezan J, Dos Santos Coelho L. Coyote optimization algorithm: a new metaheuristic for global optimization problems. 2018 IEEE congress on evolutionary computation (CEC); 2018 Jul 8-13; Rio de Janeiro, Brazil. Piscataway: IEEE Press; 2018 . p. 1 – 8 .
26
Wen T, Zhang B, Hu YP, et al. Research on MDS-MAP location algorithm based on floyd’s shortest path. 2020 Chinese automation congress (CAC); 2020 Nov 6-8; Shanghai, China. Piscataway: IEEE Press; 2021. p. 5057–60.
27
Jiang FB, Dong L, Dai QW. Designing a mixed multilayer wavelet neural network for solving ERI inversion problem with massive amounts of data: A hybrid STGWO-GD learning approach. IEEE Trans Cybern 2022;52(2):925–36.
28
Wu SM, Jiang JD, Yan YH, et al. Improved coyote algorithm and application to optimal load forecasting model. Alex Eng J 2022;61(10):7811–22.
29
Shi N, Luo X. A novel cluster-based location-aided routing protocol for UAV fleet networks. Int J Digit Content Technol Appl 2012;6(18):376–83.
30
Hauert S, Winkler L, Zufferey JC, et al. Ant-based swarming with positionless micro air vehicles for communication relay. Swarm Intell 2008;2(2):167–88.
31
Aadil F, Raza A, Khan MF, et al. Energy aware cluster-based routing in flying ad-hoc networks. Sensors (Base 2018;18(5):1413.
32
Cheng Z, Sun Y, Liu YL. Path planning based on immune genetic algorithm for UAV. 2011 international conference on electric information and control Engineering; 2011 Apr 15-17; Wuhan, China. Piscataway: IEEE Press; 2011. p. 590–3.
33
Khan A, Aftab F, Zhang ZS. Self-organization based clustering scheme for FANETs using Glowworm Swarm Optimization. Phys Commun 2019;36:100769.
34
Fan YS, Qi XG, Li B, et al. Fast clustering-based multidimensional scaling for mobile networks localisation. IET Commun 2020;14(1):135–43.
35
Ding L, Bai YL, Fan MH, et al. Serial-parallel dynamic echo state network: A hybrid dynamic model based on a chaotic coyote optimization algorithm for wind speed prediction. Expert Syst Appi 2021;212:118789.
36
Heinzelman WB, Chandrakasan AP, Balakrishnan HB. An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wireless Commin 2002;1(4):660–70.
37
Omran MGH, Mahdavi M. Global-best harmony search. Appl Math Comput 2008;198(2):643–56.
38
Cheng M, Aziz MRK. DOA-based 3D tracking with factor graph technique for a multi-sensor system. IEEE Sens J 2021;21(22):25853–61.
39
Haiyang J, Jie L, Yang W. Key technology analysis and design verification of the high-speed test system for missile flying. Sci Technol Eng 2019;19(3):6–13.
40
Zhang WB, Han GJ, Wang X, et al. A node location algorithm based on node movement prediction in underwater acoustic sensor networks. IEEE Trans Veh Technol 2020;69(3):3166–78.
41
Ni JC, Cheng W, Fan W, et al. ComClus: A self-grouping framework for multi-network clustering. IEEE Trans Knowl Data Eng 2018;30(3):435–48.
42
Ruping Z, Jing S, David L. Research on the key technology of intelligent munitions cluster cooperative operation. Tactical Missile Technol 2020;12:135–43.
43
He YC, Wang XZ, Liu KQ, et al. Convergent analysis and algorithmic improvement of differential evolution. J Softw 2010;21(5):875–85.
44
Li MQ, Kou JS, Lin D. The foundational theory and application of genetic algorithms. Beijing: Science Press; 2003. p. 115–9 [Chinese].
