Jiang Li, Jiutao Zhao, Qinhui Liu*, Laizheng Zhu, Jinyi Guo, Weijiu Zhang
CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 223-244, 2023, DOI:10.32604/cmc.2023.042429
Abstract Cutting parameters have a significant impact on the machining effect. In order to reduce the machining time and improve the machining quality, this paper proposes an optimization algorithm based on Bp neural network-Improved Multi-Objective Particle Swarm (Bp-DWMOPSO). Firstly, this paper analyzes the existing problems in the traditional multi-objective particle swarm algorithm. Secondly, the Bp neural network model and the dynamic weight multi-objective particle swarm algorithm model are established. Finally, the Bp-DWMOPSO algorithm is designed based on the established models. In order to verify the effectiveness of the algorithm, this paper obtains the required data through equal probability orthogonal experiments on… More >
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