Abstract
This paper proposes a Switching PSO (SW-PSO) based on entropy of swarm and switch mode. Further, a hybrid method based on SW-PSO and Back Propagation (BP) neural network algorithm has been presented for diesel engine optimization. BP was used to construct prediction model for chemical combustion in engine cylinders, and SW-PSO was employed to optimize engine parameters that achieve higher fuel efficiency and fewer exhausts. SW-PSO proved to be superior in convergence performance, and the hybrid method also showed advantages in dealing with practical engine optimization problem.
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