欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对锌湿法冶炼除钴过程存在非线性和大时滞的特点,提出一种基于支持向量机和混沌粒子群算法的工艺指标（钴离子浓度）预测方法。为提高粒子群算法的搜索性能,提出一种基于非优胜粒子混沌变异和全局最优值小范围扰动的混沌变异粒子群算法。采用混沌粒子群算法优化模型参数,采用二进制粒子群算法选择输入属性,以减少模型的复杂度,提高模型的预测精度。研究结果表明：所提出的模型精度满足当溶液杂质离子质量浓度在小于1 mg/L时绝对误差小于0.1 mg/L的现场工艺标准。
英文摘要：
Considering the characteristics of strong non-linearity and large time delay in cobalt removal process of zinc hydrometallurgy,a prediction method of technical index（cobalt concentration） combining the least square support vector machine（LS-SVM） and chaotic particle swarm optimization（CPSO） was proposed.CPSO used the mutation of the non-winner particles by chaotic search and mutation of the global best position by using small extent of disturbance to improve its search performance.The model parameters were optimized by CPSO and the input attributes were selected by binary PSO,which reduces the complexity and improves the prediction accuracy.The results show that prediction accuracy of the proposed model meets the technology requirements that the absolute error will be less than 0.1 mg/L when the solution concentration is less than 1 mg/L.
同期刊论文项目
同项目期刊论文
期刊信息
位置：