基于LSSVM-MODE的水煤浆生产优化控制

水煤浆（CWM）制造过程中，存在着生产成本和水煤浆性能两者矛盾的问题。利用最小二乘支持向量机（LSSVM）对球磨机电流和水煤浆浓度进行多目标建模，并采用基于Pareto最优概念的多目标微分进化（MODE）算法，对运行工况进行寻优，然后根据模糊集理论在Pareto解集中求得满意解，获得水煤浆浓度的优化调整方式和提高水煤浆生产效益的策略，用以指导水煤浆优化生产。

Optimization control on preparation of coal water mixture Based on LSSVM-MODE

There are the inconsistency between the production cost and performance of coal water mixture (CWM) during the production process. The LSSVM (Least Square Support Vector Machines) was proposed to construct multi-objective optimization model for CWM concentration and ball mill electric current. MODE (multi-objective differential evolution) based on Pareto optimal concept is used to perform a search for determining the optimum solutions, from which the optimum adjustment mode that could heighten concentration and production benefit of CWM is obtained based on fuzzy theory.