The International Journal of Swarm Intelligence Research (IJSIR) serves as a vehicle to facilitate and promote the knowledge sharing among swarm intelligence researchers in the field, ranging from algorithm developments to real-world applications. DOI: https://doi.org/10.1155/2021/6622231. 55, pp. DOI: https://doi.org/10.1016/j.asoc.2018.06.014. Neurocomputing, vol. L. C. Lu, T. W. Yue. B. T. Chen, L. Q. Wang, X. M. Jiang, H. B. Yao. DOI: https://doi.org/10.1109/TEVC.2019.2944180. DOI: https://doi.org/10.1109/SSCI44817.2019.9002754. Macrotask crowdsourcing: An integrated definition. Co-evolution based mixed-variable multi-objective particle swarm optimization for UAV cooperative multi-task allocation problem. Multifactorial evolution: Toward evolutionary multitasking. DOI: https://doi.org/10.5555/2969033.2969105. 16521665, 2017. X. F. Liu, Z. H. Zhan, Y. Gao, J. Zhang, S. Kwong, J. Zhang. 1423, 2016. Semantic-based automatic service composition with functional and non-functional requirements in design time: A genetic algorithm approach. IEEE Transactions on Cybernetics, vol. Differential evolution algorithm with strategy adaptation and knowledge-based control parameters. In Proceedings of the 9th International Conference on Software and Information Engineering, ACM, Cairo, Egypt, pp. X. L. Ma, X. D. Li, Q. F. Zhang, K. Tang, Z. P. Liang, W. X. Xie, Z. X. Zhu. Z. Y. Yang, H. B. Duan, Y. M. Fan, Y. M. Deng. 26, no. IEEE Transactions on Intelligent Transportation Systems, vol. Chinese Journal of Computers, vol. DOI: https://doi.org/10.1016/j.swevo.2018.07.002. Simultaneous instance and feature selection and weighting using evolutionary computation: Proposal and study. 294, pp. SCA2: Novel efficient swarm clustering algorithm. Multiobjective multifactorial optimization in evolutionary multitasking. 20, no. R. Cheng, Y. C. Jin. Memory-based ant colony system approach for multi-source data associated dynamic electric vehicle dispatch optimization. X. L. Zhang, X. F. Chen, Z. J. Information and Software Technology, vol. Quality-assured synchronized task assignment in crowdsourcing. K. R. Opara, J. Arabas. G. Y. Wang. 57, no. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 12, no. 12, no. 17, pp. G. H. Wu, R. Mallipeddi, P. N. Suganthan, R. Wang, H. K. Chen. The Swarm Intelligence market size, estimations, and forecasts are provided in terms of and revenue (USD millions), considering 2023 as the base year, with history and forecast data for the. 689702, 2019. S. Das, A. Abraham, U. K. Chakraborty, A. Konar. W. W. Hu, Y. Tan. DOI: https://doi.org/10.1109/SERVICES48979.2020.00040. Quality assurance method of collective intelligence system. 3, pp. DOI: https://doi.org/10.5555/645512.657265. Swarm intelligence has become a hot research field of artificial intelligence. (in Chinese). HZ2021008). Multi-swarm competitive swarm optimizer for large-scale optimization by entropy-assisted diversity measurement and management. Neurocomputing, vol. 57, no. Q. Q. Swarm intelligence (SI), an integral part in the field of artificial intelligence, is gradually gaining prominence, as more and more high complexity problems require solutions which may be. Article Information Sciences, vol. Google Scholar, Y. Jiang, W. Zhang, P. Wang, X. Y. Zhang, H. Mei. 4, pp. together and then reaching the optimized solution for a given problem. DOI: https://doi.org/10.1007/s00265-012-1423-3. According to HTF Market Intelligence, the Global Swarm Intelligence market to witness a CAGR of 15% during forecast period of 2023-2028. (in Chinese), Z. M. Shi. DOI: https://doi.org/10.11896/jsjkx.200300072. 48, no. Pattern Recognition Letters, vol. 842857, 2019. 10, no. Lvy flight based pigeon-inspired optimization for control parameters optimization in automatic carrier landing system. 43, no. In Proceedings of CHI Conference Extended Abstracts on Human Factors in Computing Systems, ACM, San Jose, USA, pp. MathSciNet In a deeper sense, we discuss the research using a three-layer hierarchy: in the first layer, we divide the research of swarm intelligence into bio-inspired swarm intelligence and human-machine hybrid swarm intelligence; in the second layer, the bio-inspired swarm intelligence is divided into single-population swarm intelligence and multi-population swarm intelligence; and in the third layer, we review single-population, multi-population and human-machine hybrid models from different perspectives. Chapter Genetic algorithm: Theory, literature review, and application in image reconstruction. IEEE Transactions on Evolutionary Computation, vol. X. Zhang, Z. H. Zhan, W. Fang, P. J. Qian, J. Zhang. J. Zhao, X. L. Wang, M. Li. Knowledge-based Systems, vol. Dual differential grouping: A more general decomposition method for large-scale optimization. A survey on evolutionary computation for complex continuous optimization. DOI: https://doi.org/10.1109/SOSE.2015.46. DOI: https://doi.org/10.1007/978-3-540-88051-6_4. 708719, 2020. International Journal of Pattern Recognition and Artificial Intelligence, vol. In Proceedings of the 4th AAAI Conference on Artificial Intelligence, Austin, USA, pp.247250, 1984. J. R. Jian, Z. G. Chen, Z. H. Zhan, J. Zhang. 27192731, 2016. 25022510, 2008. DOI: https://doi.org/10.1007/s10489-018-1258-3. A multi-objective feature selection method using Newtons law based PSO with GWO. His research interests include rough sets, granular computing, knowledge technology, data mining, neural networks, and cognitive computing. 37, no. DOI: https://doi.org/10.1016/j.infsof.2013.12.001. Soft Computing, vol. DOI: https://doi.org/10.1016/j.ins.2011.09.001. DOI: https://doi.org/10.1016/j.ins.2016.01.090. In Proceedings of the 27th International Conference on Neural Information Processing Systems, ACM, Montreal, Canada, pp.24922500, 2014. Z. Lin, W. F. Gao. DOI: https://doi.org/10.1109/TITS.2020.3025796. DOI: https://doi.org/10.1145/3231934. 51, no. A model of new workers accurate acceptance of tasks using capable sensing. King, K. S. Leung. DOI: https://doi.org/10.1016/j.asoc.2020.106798. 833839, 2001. Aerospace Control, vol. Multipopulation ant colony system with knowledge-based local searches for multiobjective supply chain configuration. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Portland, USA, pp. An adaptive multi-population artificial bee colony algorithm for dynamic optimisation problems. A reputation-based multi-user task selection incentive mechanism for crowdsensing. Single-population swarm intelligence is inspired by biological intelligence. DOI: https://doi.org/10.1016/j.swevo.2018.04.011. DOI: https://doi.org/10.1016/j.asoc.2020.106560. Journal of Computer Applications, vol. 8083, 2011. Swarm and Evolutionary Computation, vol. W. Z. Li, W. A. Guo, Y. M. Li, L. Wang, Q. D. Wu. DOI: https://doi.org/10.1016/j.eswa.2010.03.067. DOI: https://doi.org/10.1016/j.neucom.2020.12.065. 348, pp. 41, no. 2226, 2012. Bi-space Interactive Cooperative Coevolutionary algorithm for large scale blackbox optimization. 44, pp. A similarity-based cooperative co-evolutionary algorithm for dynamic interval multiobjective optimization problems. Big Data Analytics, vol. 4, no. 2, pp. J. Goncalves, M. Feldman, S. B. Q. Hu, V. Kostakos, A. Bernstein. M. R. Tanweer, S. Suresh, N. Sundararajan. In Proceedings of the 3rd International Conference on Genetic Algorithms, ACM, San Francisco, USA, pp. 170182, 2021. M. L. Mauldin. In Proceedings of the 3rd International Conference on Advances in Swarm Intelligence, Springer, Shenzhen, China, pp. 431442, 2017. Evolutionary computation for expensive optimization: A survey. DOI: https://doi.org/10.1109/TAES.2018.2831138. 224, Article number 120153, 2021. Engineering Optimization, vol. 393401, 2017. 14831497, 2005. Journal of Software, vol. Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification. 6, no. Advances in Engineering Software, vol. S. M. Guo, C. C. Yang. Since 1996, he has been at the Chongqing University of Posts and Telecommunications, China, where he is currently a professor, the vice president of the university, and the director of the Chongqing Key Laboratory of Computational Intelligence. DOI: https://doi.org/10.1007/s11704-019-9119-8. Article 8, no. 1552915541, 2017. Y. P. Zhou, X. S. Gu. 7, Article number 70201, 2019. Journal of the Royal Society Interface, vol. 12, pp. 5, pp. DOI: https://doi.org/10.11772/j.issn.1001-9081.2016.10.2777. Task recommendation in crowdsourcing systems. A. Prakasam, N. Savarimuthu. Journal of Chinese Computer Systems, vol. J. Y. Li, K. J. DOI: https://doi.org/10.3390/sym13091707. DOI: https://doi.org/10.1016/j.knosys.2017.07.005. 44544468, 2020. DOI: https://doi.org/10.1109/TMAG.2018.2839663. The case for a reputation system in participatory sensing. Echo state networks with orthogonal pigeon-inspired optimization for image restoration. DOI: https://doi.org/10.3969/j.issn.1001-4616.2019.02.001. Her research interests include clustering analysis, data mining and swarm intelligence. Generation-level parallelism for evolutionary computation: A pipeline-based parallel particle swarm optimization. In a broader sense, we are talking about not only bio-inspired swarm intelligence, but also human-machine hybrid swarm intelligence. 11611168, 2011. Provided by the Springer Nature SharedIt content-sharing initiative, Over 10 million scientific documents at your fingertips, Not logged in By Model Typethis market is segmented on the basis of Ant Colony. MATH 59110, 2022. 10821091, 2008. Swarm intelligence techniques are population-based stochastic methods used in combinatorial optimization problems in which the collective behaviour of relatively simple individuals arises from their local interactions with their environment to produce functional global patterns. 4, pp. 141, no. 9, pp. 97, Article number 106798, 2020. K. Mao, Y. Yang, Q. Wang, Y. Jia, M. Harman. 592600, 2011. The International Journal of Swarm Intelligence Research (IJSIR) serves as a forum for facilitating and enhancing the information sharing among swarm intelligence researchers in the field, ranging from algorithm developments to real-world applications. 1, pp. 508529, 2015. 421441, 2019. DOI: https://doi.org/10.1109/TPDS.2017.2735400. In nature, it describes how honeybees migrate, how ants form perfect trails, and how birds flock. 367374, 2013. L. Shi, Z. H. Zhan, D. Liang, J. Zhang. The company, best known for its credit card business, started out as a spin-off from a local bank, and when Donehey joined it in 1994, its IT . 142156, 2020. This field includes multiple optimization algorithms to solve NP-hard problems for which conventional methods are not effective. Grey wolf optimizer. Cooperative co-evolutionary genetic programming for high dimensional problems. The swarm intelligence algorithms are proposed to mimic the swarm intelligence behavior of biological in nature, which has become a hot of cross-discipline and research field in recent years. DOI: https://doi.org/10.1016/j.eswa.2017.07.025. BNC-PSO: Structure learning of Bayesian networks by particle swarm optimization. IEEE Transactions on Evolutionary Computation, vol. was introduced by Gerardo Beni and Jing Wang in the year 1989. Distributed differential evolution with adaptive resource allocation. Metaheuristic algorithms and probabilistic behaviour: A comprehensive analysis of ant colony optimization and its variants. 10, pp. K. Georgieva, A. P. Engelbrecht. 349374, 2021. Mar 17, 2023 (The Expresswire) -- Latest Research Report 2023-2028: "Natural Gas Distribution Market" | Survey with 90 Pages Report The Natural Gas. P. Dhal, C. Azad. DOI: https://doi.org/10.1109/4235.996017. 59, Article number 100732, 2020. 1825, 2018. To further solve complex optimization problems, researchers have made preliminary explorations in multi-population swarm intelligence. 352373, 2014. 34, no. DOI: https://doi.org/10.1007/s11277-016-3564-6. IEEE Access, vol. 12, 2021. A deep hierarchical reinforcement learner for aerial shepherding of ground swarms. 7488774900, 2020. IEEE Transactions on Cybernetics, vol. Z. Zhang, R. Z. Gao, Z. Xu, J. Yang. Search-based software engineering. DOI: https://doi.org/10.1360/SSI-2019-0150. 1344113459, 2020. DGCC: Data-driven granular cognitive computing. 94, no. X. S. Yang. King, K. S. Leung. 46, no. Frontiers of Computer Science, vol. IEEE Transactions on Cybernetics, vol. 107, Article number 107394, 2021. 7, pp. Behavioral Ecology and Sociobiology, vol. 8, Article number 7402307, 2018. DOI: https://doi.org/10.3321/j.issn:0254-4164.2008.07.003. DOI: https://doi.org/10.1109/TEVC.2013.2297160. D. F. Zhang, J. L. Zhang. Computer Science, vol. Gerardo Benny and Joon Wang introduced swarm intelligence in 1989 in the context of cellular robotics systems. 19, no. 7, pp. DOI: https://doi.org/10.1002/cpe.6126. DOI: https://doi.org/10.4109/TEVC.2013.2281535. A new metaheuristic bat-inspired algorithm. DOI: https://doi.org/10.1145/2488388.2488421. Nonetheless, in the writers' community, we are known for our strict selection process. Machine Intelligence Research, vol. 42, no. Neurocomputing, vol. . An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: Solving problems with box constraints. 2, pp. 3, pp. DOI: https://doi.org/10.1007/s00366-019-00917-8. 44, no. Self regulating particle swarm optimization algorithm. 1, Article number 14, 2016. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan. DOI: https://doi.org/10.1145/3415181. 24, no. Multi-colony ant algorithms for the dynamic travelling salesman problem. Research survey of differential evolution algorithms. SN Computer Science, vol. A. Gupta, Y. S. Ong, L. Feng. 37, no. IEEE Access, vol. DOI: https://doi.org/10.1145/2348283.2348387. 29, 1989. 5988, 2004. M. Harman, B. F. Jones. 6, pp. A new hybrid algorithm for continuous optimization problem. Cooperative coevolutionary bare-bones particle swarm optimization with function independent decomposition for large-scale supply chain network design with uncertainties. DOI: https://doi.org/10.1109/TEVC.2019.2893447. DOI: https://doi.org/10.1109/TETCI.2020.2992778. 23, no. DOI: https://doi.org/10.1016/j.ast.2019.03.054. Swarm intelligence algorithms are a subset of the . 233, pp. IEEE Transactions on Cybernetics, vol. Pigeon-inspired optimization: A new swarm intelligence optimizer for air robot path planning. A fast and elitist multiobjective genetic algorithm: NSGA-II. 6, pp. Survey of task assignment for crowd-based cooperative computing. 27772783, 2016. 487512, 2020. 49, no. 4, pp. 7, pp. Multi-objective Task Recommendation Method Based on Different Task Characteristics for Crowdsourcing, Master dissertation, School of Mathematics, China University of Mining and Technology, China, 2019. 8, pp. 7, no. J. Y. Tu, P. Cheng, L. Chen. DOI: https://doi.org/10.1109/TCYB.2016.2554622. Knowledge-based Systems, vol. 271279, 2015. 79, pp. A novel gate resource allocation method using improved PSO-based QEA. 24872497, 2017. Enhancing differential evolution utilizing eigenvector-based crossover operator. A meta-knowledge tranfeer-based differential evolution for multitask optimization. Expert Systems with Applications, vol. 29122926, 2019. H. P. Ma, S. G. Shen, M. Yu, Z. L. Yang, M. R. Fei, H. Y. Zhou. 577601, 2014. King, K. S. Leung. 24132425, 2016. Bat algorithm with principal component analysis. 307317, 2020. M. R. Chen, Y. Y. Huang, G. Q. Zeng, K. D. Lu, L. Q. Yang. 219, Article number 106894, 2021. A survey on cooperative co-evolutionary algorithms. 3, pp. An enhanced whale optimization algorithm for large scale optimization problems. H. B. Duan, X. H. Wang. Z. X. Zheng, J. Guo, E. Gill. What's Swarm Intelligence. Song. He was the president of the International Rough Set Society (IRSS) from 2014 to 2017, and is currently a vice president of the Chinese Association for Artificial Intelligence (CAAI) and a council member of the China Computer Federation (CCF). 3, pp. Reputation model of crowdsourcing workers based on active degree. 185, no. 1, pp. 168, pp. DOI: https://doi.org/10.1016/j.jss.2016.09.015. Transp. DOI: https://doi.org/10.1016/j.apm.2017.10.001. 14, no. 6, pp. 69, pp. Neural Computing and Applications, vol. DOI: https://doi.org/10.1016/j.asoc.2020.106680. IEEE Transactions on Cybernetics, vol. DOI: https://doi.org/10.11897/SP.J.1016.2021.01967. (in Chinese), MathSciNet S. L. Zhang, J. L. Huang, J. Hanan, L. Qin. DOI: https://doi.org/10.1109/TCYB.2019.2944873. IEEE Transactions on Evolutionary Computation, vol. 2034, 2019. S. Shadravan, H. R. Naji, V. K. Bardsiri. 10231031, 2017. IEEE Transactions on Evolutionary Computation, vol. IEEE Transactions on Evolutionary Computation, vol. Optimal scheduling of microgrid considering the interruptible load shifting based on improved biogeography-based optimization algorithm. J. Y. Li, Z. H. Zhan, K. C. Tan, J. Zhang. 13, no. J. M. Lien, S. Rodriguez, J. P. Malric, N. M. Amato. Journal of Computer Applications, vol. (in Chinese). 5167, 2016. Review and prospect of cooperative combat of manned/unmanned aerial vehicle hybrid formation. A simple yet fully adaptive PSO algorithm for global peak tracking of photovoltaic array under partial shading conditions. D. degree in computer organization and system structure from Xian Jiaotong University, China in 1996. Multimedia Tools and Applications, vol. 481509, 2020. In Proceedings of EEE International Conference on Neural Networks, Perth, Australia, pp. Many-objective job-shop scheduling: A multiple populations for multiple objectives-based genetic algorithm approach. G. Syswerda. F. Wang, H. Zhang, M. C. Han, L. N. Xing. A NOVEL SWARM INTELLIGENCE OPTIMIZED SPECTRUM SENSING APPROACH FOR COGNITIVE RADIO NETWORK 143 Jhajj, H. K., Garg, R., & Saluja, N. Implementation of Particle Swarm Optimization . Guo-Yin Wang received the B. Sc. DOI: https://doi.org/10.5555/3104482.3104628. K. H. Han, J. H. Kim. Chinese Journal of Computers, vol. Triple archives particle swarm optimization. 34, no. Acta Electronica Sinica, vol. 15, no. Applied Soft Computing, vol. However, it is difficult for bio-inspired swarm intelligence to realize dynamic cognitive intelligent behavior that meets the needs of human cognition. 43, no. 24, no. Energy, vol. M. C. Yuen, I. SI systems are typically made up of a population of simple agents interacting locally with one another and with their environment. Dual role model for question recommendation in community question answering. Information Sciences, vol. DOI: https://doi.org/10.1007/s11432-018-9752-9. DOI: https://doi.org/10.5555/2908698.2908712. 4, pp. DOI: https://doi.org/10.1109/TEVC.2013.2281528. Crowdsourcing quality evaluation algorithm based on sliding task window. W. Q. Xu, C. Chen, S. X. Ding, P. M. Pardalos. 28, no. IEEE Transactions on Evolutionary Computation, vol. Swarm intelligence is an emerging field of biologically-inspired artificial intelligence based on the behavioral models of social insects such as ants, bees, wasps, termites etc. Communications of CCF, vol. Swarm intelligence is a discipline that deals with natural and artificial systems composed of many individuals who coordinate their activities using decentralized control and self-organization [182]. 4, pp. CEPT: Collaborative editing tool for non-native authors. Differential evolution using a neighborhood-based mutation operator. Chinese Journal of Computers, vol. Swarm and Evolutionary Computation, vol. Two-step classification method based on genetic algorithm for bankruptcy forecasting. Cooperative communication based on swarm intelligence: Vision, model, and key technology. 5, no. As a new journal in the field of evolutionary computation, IJSIR has built its reputation from its first two years of existence. Engineering with Computers, vol. In general, swarm intelligence algorithms are nature-inspired algorithms developed based on the interactions between living organisms such as flocks of birds, ants, and fish. 23, no. 17371745, 2022. 18, no. 12, pp. 229246, 2018. He, Q. H. Fang, Y. Dai, D. H. Jiang. (in Chinese), L. X. Xu, H. Y. Wu. X. M. Zhang, X. Wang, H. Y. Chen, D. D. Wang, Z. H. Fu. DOI: https://doi.org/10.1109/ACCESS.2020.2989406. Book Wireless Personal Communications, vol. X. F. Yuan, X. S. Dai, J. Y. Zhao, Q. Artificial Intelligence Review, vol. Information Sciences, vol. DOI: https://doi.org/10.1007/s11042-019-07976-5. Google Scholar. Study on the relationship between population diversity and learning parameters in particle swarm optimization. X. Yao, G. L. Chen, H. M, X U, Y. Liu. Network Control & Optimization Applied Intelligence, vol. Journal of Systems and Software, vol. Global genetic learning particle swarm optimization with diversity enhancement by ring topology. A competitive mechanism integrated multi-objective whale optimization algorithm with differential evolution. X. W. Xia, L. Gui, F. Yu, H. R. Wu, B. Wei, Y. L. Zhang, Z. H. Zhan. D. W. Gong, B. Xu, Y. Zhang, Y. N. Guo, S. X. Yang. T. Q. Chang, D. P. Kong, N. Hao, K. H. Xu, G. Z. Yang. Proceedings of the National Academy of Sciences of the United States of America, vol. Research on the performance of multi-population genetic algorithms with different complex network structures. "Swarm" means a group of objects (people, insects, etc. 6782, 2018. Artificial Intelligence Review, vol. DOI: https://doi.org/10.1007/978-3-642-30976-2_50. Finally, we discuss future research directions and key issues to be studied in swarm intelligence. Google Scholar. X. Q. Shi, W. Long, Y. Y. Li, D. S. Deng, Y. L. Wei. Control and Instruments in Chemical Industry, vol. Swarm Intelligence. 512526, 2022. 51, no. Deadline-constrained cost optimization approaches for workflow scheduling in clouds. DOI: https://doi.org/10.1109/TEVC.2002.804320. K. Chen, B. Xue, M. J. Zhang, F. Y. Zhou. Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining. 9, pp. Y. H. Liu. DOI: https://doi.org/10.1016/j.knosys.2017.12.031. 11, pp. DOI: https://doi.org/10.1016/j.knosys.2021.106894. DOI: https://doi.org/10.7544/issn1000-1239.2020.20190626. Concurrency and Computation: Practice and Experience, vol. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, Ann Arbor, USA: University of Michigan Press, 1975. K. Deb, H. Jain. 12731277, 2020. Maintaining diversity in genetic search. 11751188, 2021. 6, no. J. Y. Li, Z. H. Zhan, J. Zhang. DOI: https://doi.org/10.1016/j.ins.2014.08.039. 175, Article number 114812, 2021. F. Q. Zhao, L. X. Zhao, L. Wang, H. B. 28, no. Ant colony algorithm and density peaks clustering for medical image segmentation. N. K. Long, K. Sammut, D. Sgarioto, M. Garratt, H. A. Abbass. C. Su, T. Hou. Sunilkumar S. Manvi, in Recent Trends in Computational Intelligence Enabled Research, 2021. DOI: https://doi.org/10.3969/j.issn.1000-1220.2017.09.038. Y. Yan, R. Rosales, G. Fung, J. G. Dy. 5, Article number 2055011, 2020. DOI: https://doi.org/10.1016/j.advengsoft.2013.12.007. In Proceedings of IEEE Congress on Evolutionary Computation, Cancun, Mexico, pp. X. 431451, 2010. 3, pp. We are an interdisciplinary research lab that studies the mechanisms underlying the coordination of large animal groups, such as ant colonies or human crowds, and their applications to complex problems such the organization of pedestrian traffic or the control of robotic swarms. 48484859, 2021. Swarm Intelligence publishes original research contributions in the arena of Machine Learning & Artificial intelligence. Cervical cytology classification using PCA and GWO enhanced deep features selection. Fine-grained recommendation mechanism to curb astroturfing in crowdsourcing systems. DOI: https://doi.org/10.1186/s41044-016-0012-2. 272289, 2016. 17: 4803. https://doi.org . 1, pp. 37, pp. Abstract:Swarm intelligence is the discipline deals with artificial and natural systems that consists various individuals coordinated using self-organization and decentralized control. Proceedings of IEEE World Congress on Services, Beijing, China, pp. 5155, 2020. 3, pp. Z. G. Chen, Z. H. Zhan, Y. Lin, Y. J. Gong, T. L. Gu, F. Zhao, H. Q. Yuan, X. F. Chen, Q. Li, J. Zhang. A. 249257, 1994. He is a fellow of IRSS, CAAI and CCF. Expert Systems with Applications, vol. 104107, 2019. For large-sized journals the figures should be 84 mm (for double-column text areas), or 174 mm (for single-column text areas) wide and not higher than 234 mm. DOI: https://doi.org/10.1109/TCYB.2022.3153964. 2023 Springer Nature Switzerland AG. N. Y. Zeng, D. D. Song, H. Li, Y. C. You, Y. R. Liu, F. E. Alsaadi. B. Xu, Y. M. Deng. DOI: https://doi.org/10.1109/TEVC.2018.2875430. 2, pp. DOI: https://doi.org/10.1007/978-3-030-58115-2_4. Computing and Informatics, vol. 23, no. Adaptive granularity learning distributed particle swarm optimization for large-scale optimization. R. Kumar, Jyotishree. A multistage evolutionary algorithm for many-objective optimization. DOI: https://doi.org/10.1109/TCYB.2015.2487318. DOI: https://doi.org/10.1109/TETCI.2019.2961190. 901916, 2011. De Jong. The main aim of preparing this paper is to lead the way for the researchers in the field of wireless networks to recognize the role of swarm intelligence in optimizing the network features. 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