基于BP神经网络的机电产品绿色度评价方法

An Evaluation Method for Green Degree of Mechanical and Electrical Products Based on BP Neural Network

绿色度评价直接影响着机电产品的设计、制造、管理及发展。从机电产品制造的能源、资源、环境、经济和技术等属性进行分析,运用层次分析法(AHP)确定机电产品绿色度评价指标体系及其权重,建立机电产品绿色度BP神经网络评价模型,通过粒子群-人工蜂群(PSO-ABC)算法优化训练BP神经网络结构参数。仿真实验表明,该方法评价速度快、准确率高,对于指导机电产品绿色制造具有较好的参考价值。

Green degree evaluation directly affects design, manufacture, management and development of the mechanical and electronic products. By analyzing the energy, resources, environment, economy, technology, etc. of the mechanical and electrical product manufacturing, and applying analytic hierarchy process （AHP） to determine the green degree evaluation indicator of the mechanical and electrical products and its weight, the research establishes a green degree evaluation model of BP neural network, and optimizes the BP network structure parameters via the particle swarm by artificial swarm algorithm （PSO-ABC） algorithm. Simulation data and experimental results show that this method of evaluation reveals high speed and high accuracy, and is valuable to the green manufacturing of the mechanical and electrical products.