Abstract
In this study, the task allocation mechanism in mobile swarm intelligence perception is studied and analyzed. Considering how to allocate tasks under specified time constraints and optimize for the goal, a hybrid artificial fish swarm algorithm is proposed by using swarm intelligence algorithm. The inertia index of particle swarm optimization algorithm is pulled into the typical artificial fish swarm algorithm, which is proved by simulation experiments. The hybrid artificial fish swarm algorithm greatly improves the convergence speed, avoids the shortage that the artificial fish swarm algorithm often stop when it obtains the local optimization, and this make the algorithm obtains the effect of global optimization.
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Acknowledgment
This work is partly supported by the project supported by the National Social Science Foundation(16BJY125) ,Heilongjiang philosophy and social sciences research planning project(19JYB026),Key topics in 2020 of the 13th five year plan of Educational Science in Heilongjiang Province(GJB1320276),Project supported by under-graduate teaching leading talent training program of Harbin University of Commerce(201907),Key project of teaching reform and teaching research of Harbin University of Commerce in 2020(HSDJY202005(Z)),Innovation and entrepreneurship project for college students of Harbin University of Commerce (202010240059),Swarm level scientific research project of Heilongjiang Oriental University(HDFKY200202),Key entrusted projects of higher education teaching reform in 2020(SJGZ20200138).
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Li, J., Su, F., Yang, Y., Liu, J. (2022). Research on Task Allocation Method of Mobile Swarm Intelligence Perception Based on Hybrid Artificial Fish Swarm Algorithm. In: Hassanien, A.E., Xu, Y., Zhao, Z., Mohammed, S., Fan, Z. (eds) Business Intelligence and Information Technology. BIIT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 107. Springer, Cham. https://doi.org/10.1007/978-3-030-92632-8_73
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DOI: https://doi.org/10.1007/978-3-030-92632-8_73
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