Optimization of 3DDV-Hop node localization using multi-strategy improved dung beetle search algorithm
In order to improve the positioning accuracy and stability of the traditional 3DDV-Hop algorithm,this study pro-poses an MIDBO-3DDV-Hop algorithm.This algorithm utilizes multiple strategies to improve the localization accuracy of the 3DDV-Hop algorithm by improving the dung beetle search algorithm(MIDBO).Firstly,the algorithm refines the hop count through the communication radius grading method,and uses weighted average hop distance to correct the hop distance error between nodes.At the same time,the MIDBO algorithm introduces cubic chaos initialization and reverse refraction mecha-nism to initialize the algorithm population,and adopts a variable helix strategy to enhance the global search ability.In addi-tion,the algorithm also incorporates Levy flight strategy and adaptive weight factors to avoid falling into local optima and balance the convergence and search diversity of the algorithm.Finally,the MIDBO algorithm is used to optimize the un-known node positions in the 3DDV Hop algorithm.The simulation results show that compared with the traditional 3DDV-Hop,IPSO-3DDV-Hop and IGA-3DDV-Hop algorithms,MIDBO-3DDV-Hop algorithm achieves the optimal level in posi-tioning accuracy,stability and rate of convergence.
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