Research on Application of Innovative Hybrid Algorithm in Train Attitude Measurement System
This paper proposes an innovative hybrid algorithm,PGSO,to address the challenging issue of wireless sensor network coverage optimization in the train attitude measurement system.This algorithm combines the excellent global search capability of Particle Swarm Optimization(PSO)with the local fine-grained search advantage of Glowworm Swarm Optimization(GSO),aiming to improve the coverage quality of the wireless sensor network in the train attitude measurement system.Experiments show that the PGSO algorithm converges faster,has higher coverage,and stronger global search capabilities compared to PSO and GSO.It excels in the train attitude measurement scenario,effec-tively solving the wireless sensor network coverage optimization problem.
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