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出 处:《煤炭工程》2008年第5期88-91,共4页Coal Engineering
摘 要:浓度与粘度是水煤浆(CWM)的主要性能参数。现场制浆中,常需调整运行参数以获得高浓度、低粘度的水煤浆。分析运行参数对水煤浆浓度与粘度的敏感性具有重要意义。论文利用最小二乘支持向量机(LSSVM)对水煤浆浓度和粘度进行多目标建模,并采用基于Pareto最优概念的多目标微分进化(MODE)算法进行寻优,然后根据模糊集理论在Pareto解集中求得满意解,以此为基准值分析相关因素对水煤浆浓度和粘度的影响。同时对影响因素进行敏感性分析,进而得到水煤浆浓度和粘度与相关因素间的敏感度。Concentration and viscosity are themain performance parameters of coal watermixture ( CWM), For the running parameters are often adjusted to acquire high concentration and low viscosity of CWM during the production process, analyzing the sensitive in concentration and viscosity of CWM for running parameters have importantmeaning, The LSSVM (Least Square Support Vectormachines ) was proposed to constructmulti -objective optimizationmodel for CWM concentration and viscosity, mODE ( multi - objective differential evolution) based on Pareto optimal concept and fuzzy theory are used to perform a search for benchmark value. Based on the benchmark value, the variations of concentration and viscosity with the correlate factors and the sensitivity of the correlate factors for concentration and viscosity are obtained.
分 类 号:TQ531[化学工程—煤化学工程]
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