خوارزمية بحث الوقواق المحسنة لزيادة نطاق التغطية لشبكات الاستشعار اللاسلكية

Elhabyan R, Shi W, St-Hilaire M. Coverage protocols for wireless sensor networks: Review and future directions. J.Commn.Net. 2019 Feb;21(1):45-60.https://doi.org/10.1169/JCN.2019.000005

Saeedi ID, Al-Qurabat AK. Perceptually important points-based data aggregation method for wireless sensor networks. Baghdad Sci. J. 2022 Aug 1;19(4):0875.https://doi.org/10.21123/bsj.2022.19.4.0875

Maheshwari A, Chand N. A survey on wireless sensor networks coverage problems. InProceedings of 2nd International Conference on Communication, Computing and Networking: ICCCN 2018, NITTTR Chandigarh, India .2019; (pp. 153-164). Springer Singapore. https://doi.org/10.1007/978-981-13-1217-5_16

Yasear SA, Ku-Mahamud KR. Taxonomy of memory usage in swarm intelligence-based metaheuristics. Baghdad Sci. J. 2019;16(2):0445.http://dx.doi.org/10.21123/bsj.2019.16.2(SI).0445

Singh A, Sharma S, Singh J. Nature-inspired algorithms for wireless sensor networks: A comprehensive survey. Comput. Sci. Rev. . 2021 Feb 1;39:100342.https://doi.org/10.1016/j.cosrev.2020.100342

Duan J, Yao AN, Wang ZT, Yu L. An Improved Sparrow Search Algorithm Optimizes Coverage in Wireless Sensor Networks. Eng. Technol. Ed. . [cited 2023 Feb 21];1–11. http://kns.cnki.net/kcms/detail/22.1341.T.20220726.1034.003.html.

Mottaki NA, Motameni H, Mohamadi H. An effective hybrid genetic algorithm and tabu search for maximizing network lifetime using coverage sets scheduling in wireless sensor networks. J. Supercomput. 2023 Feb;79(3):3277-97.https://doi.org/10.1007/s11227-022-04710-1

He Q, Lan Z, Zhang D, Yang L, Luo S. Improved marine predator algorithm for wireless sensor network coverage optimization problem. Sustainability. 2022 Aug 11;14(16):9944.https://doi.org/10.3390/su14169944

Musa JA, Romli R, Yusoff N. An analysis on the applicability of meta-heuristic searching techniques for automated test data generation in automatic programming assessment. Open Access Baghdad Sci J. . 2019;16(SI):515-33.https://doi.org/10.21123/bsj.2019.16.2(SI).0515

Yang XS, Deb S. Engineering optimisation by cuckoo search. IJMMNO. 2010 Jan 1;1(4):330-43.https://doi.org/10.1504/IJMMNO.2010.03543

Mohamad AB, Zain AM, Nazira Bazin NE. Cuckoo search algorithm for optimization problems—a literature review and its applications. Appl. Artif. Intell. . 2014 May 28;28(5):419-48.https://doi.org/10.1080/08839514.2014.904599

Ye SQ, Wang FL, Ou Y, Zhang CX, Zhou KQ. An improved cuckoo search combing artificial bee colony operator with opposition-based learning. In2021 China Automation Congress (CAC).2021 Oct 22; pp. 1199-1204. IEEE.https://doi.org/10.1109/CAC53003.2021.9727912

Zhang CX, Zhou KQ, Ye SQ, Zain AM. An improved cuckoo search algorithm utilizing nonlinear inertia weight and differential evolution for function optimization problem. IEEE Access. 2021 Nov 25;9:161352-73.https://doi.org/10.1109/ACCESS.2021.3130640

Li PC, Zhang XY, Zain AM, Zhou KQ. An Improved Cuckoo Search Algorithm Using Elite Opposition-Based Learning and Golden Sine Operator. InInternational Conference on Adaptive and Intelligent Systems. Cham: Springer International Publishing. 2022 Jul 4 ;(pp. 276-288).https://doi.org/10.1007/978-3-031-06794-5_23

Yang XS, Deb S. Cuckoo search via Lévy flights.NaBIC.2009 Dec 9; pp. 210-214. Ieee.https://doi.org/10.1109/NABIC.2009.5393690

Iqbal Z, Ilyas R, Chan HY, Ahmed N. Effective Solution of University Course Timetabling using Particle Swarm Optimizer based Hyper Heuristic approach. Baghdad Sci. J. . 2021 Dec 20;18(4 (Suppl.)):1465-.https://doi.org/10.21123/bsj.2021.18.4(Suppl.).1465

Tizhoosh HR. Opposition-based learning: a new scheme for machine intelligence. InInternational conference on computational intelligence for modelling, control and automation and international conference on intelligent agents, web technologies and internet commerce (CIMCA-IAWTIC'06). 2005 Nov 28; Vol. 1: pp. 695-701). IEEE.https://doi.org/10.1109/CIMCA.2005.1631345

Kamaruzaman AF, Zain AM, Yusuf SM, Udin A. Levy flight algorithm for optimization problems-a literature review. Appl. Mech. Mater. . 2013 Dec 12;421:496-501.https://doi.org/10.4028/www.scientific.net/AMM.421.496

Zhang ZZ, He XS, Yu QL, Yang XS. Cuckoo Algorithm for Multi-stage Dynamic Disturbance and Dynamic Inertia Weight. Comput. Appl. Eng. Educ. . 2021 Apr 29;58(01):79–88.https://doi.org/10.3778/j.issn.1002-8331.2012-0281

Sun M, Wei H. An improved adaptive inertial weight Cuckoo algorithm. Journal of Yangtze University(Natural Science Edition). 2019 Jul 17;16(07):81-87.https://doi.org/10.16772/j.cnki.1673-1409.2019.07.016

Zheng HQ, Feng WJ. An improved Cuckoo Search algorithm for Constrained Optimization Problems. Chinese Journal of Engineering Mathematics. 2023 Feb 15;40(01);135-146.https://doi.org/10.3969/j.issn.1005-3085.2023.01.010