CAI Anjiang1, WANG Yi1, GUO Shihong2, PAN Wei3
（1. School of Mechanical and Electrical Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China;2. School of Civil Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China； 3. Dezhou Haitian Electromechanical Technology Co., Ltd., Dezhou 253000, China）
Abstract： For the purpose of service composition optimization of knowledge resources for complex parts in cloud manufacturing environment, a service composition optimization model with quality of service (QoS) as optimization objective is established. Firstly, gray relational analysis is used to preprocess manufacturing resources, reduce search range of knowledge resources and reduce search cost. Then, the improved ant colony algorithm is used to optimize the knowledge resources globally to improve matching speed. Finally, the ant colony back-propagation (BP) neural network algorithm is used to improve the learning efficiency and accuracy of knowledge service composition by optimizing the optimal solution in solution space again. The experimental results show that the usage of gray relational analysis, improved ant colony algorithm, and BP neural network can reduce the search time of knowledge service, improve the matching accuracy, and effectively solve the problem of knowledge service composition optimization.
Key words： diesel engine; cloud manufacturing; gray relation analysis (GRA); ant colony back-propagation (BP) network; knowledge service composition optimization
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蚁群BP神经网络在云制造知识服务组合优化中的应用
蔡安江1， 王艺1， 郭师虹2， 潘伟3
（1. 西安建筑科技大学 机电学院， 陕西 西安 710055； 2. 西安建筑科技大学 土木工程学院， 陕西 西安 710055； 3. 德州海天机电科技有限公司， 山东 德州 253000）
摘要：为实现针对复杂零件在云制造环境下知识资源的服务组合优化， 建立了以QoS服务需求为优化目标的服务组合优化模型。 首先， 利用灰色关联分析对制造资源进行预处理以减小知识资源搜索范围， 降低搜索成本。 其次， 利用改进的蚁群算法对知识资源进行全局优化分析， 以提高匹配速度。 最后， 利用蚁群BP神经网络算法对解空间中最优解进行再次优化以提高知识服务组合的学习效率和学习精度。 实验结果表明， 灰色关联分析、改进的蚁群算法以及BP神经网络的使用， 可缩短知识服务的搜索时间， 提高匹配精确度， 有效解决知识服务组合优化问题。
关键词：柴油机； 云制造； 灰色关联分析； 蚁群BP网络； 知识服务组合优化
引用格式：CAI Anjiang, WANG Yi, GUO Shihong， et al． Application of ant colony BP network in composition optimization of cloud manufacturing knowledge service． Journal of Measurement Science and Instrumentation， 2023， 14（1）： 74-84. DOI： 10．3969／j．issn．1674-8042．2023．01．009
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