Abstract
This paper presents a clustering method of combining grid and genetic algorithm (GA) based on grid and global optimization in wireless sensor networks (WSN). The algorithm first partitions grid based on node’s location, then computes clustering center of grid using membership degree of GA, and then introduces dimensionality reduction pretreatment of the high-dimensional samples mapping into the two-dimensional space and optimum maintaining strategy. Simulation results show that the method in this paper can reduce iteration times and clustering accuracy is higher.
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© 2013 Springer-Verlag London
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Zeng, J. (2013). A Clustering Method of Combining Grid and Genetic Algorithm in Wireless Sensor Networks. In: Zhong, Z. (eds) Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012. Lecture Notes in Electrical Engineering, vol 218. Springer, London. https://doi.org/10.1007/978-1-4471-4847-0_95
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DOI: https://doi.org/10.1007/978-1-4471-4847-0_95
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