The Effective Clustering Partition Algorithm Based on the Genetic Evolution

To the problem that it is hard to determine the clustering number and the abnormal points by using the clustering validity function, an effective clustering partition model based on the genetic algorithm is built in this paper. The solution to the problem is formed by the combination of the clustering partition and the encoding samples, and the fitness function is defined by the distances among and within clusters. The clustering number and the samples in each cluster are determined and the abnormal points are distinguished by implementing the triple random crossover operator and the mutation. Based on the known sample data, the results of the novel method and the clustering validity function are compared. Numerical experiments are given and the results show that the novel method is more effective.     

表面活性剂强化铜矿石浸出

为了解决铜矿石浸出速度慢、浸出率低的问题,在浸出液中加入表面活性剂进行摇瓶试验.通过测量浸出前后溶液表面张力以及铜浸出率,考察了三种不同类型的表面活性剂对铜矿石浸出的影响.研究发现溶液表面张力对矿石浸出影响较大,阴离子表面活性剂的强化浸出作用最为明显,铜浸出率达62.5%.在柱浸试验中,添加阴离子表面活性剂使铜浸出率提高了近10%.利用物理化学和渗流力学对表面活性剂强化浸出机理的分析表明,溶液表面张力和表面活性剂在矿石表面的吸附对矿石表面润湿作用影响较大,表面活性剂在浸出液的持久性也是影响浸出的因素之一.     

表面活性剂强化铜矿石浸出

为了解决铜矿石浸出速度慢、浸出率低的问题,在浸出液中加入表面活性剂进行摇瓶试验.通过测量浸出前后溶液表面张力以及铜浸出率,考察了三种不同类型的表面活性剂对铜矿石浸出的影响.研究发现溶液表面张力对矿石浸出影响较大,阴离子表面活性剂的强化浸出作用最为明显,铜浸出率达62.5%.在柱浸试验中,添加阴离子表面活性剂使铜浸出率提高了近10%.利用物理化学和渗流力学对表面活性剂强化浸出机理的分析表明,溶液表面张力和表面活性剂在矿石表面的吸附对矿石表面润湿作用影响较大,表面活性剂在浸出液的持久性也是影响浸出的因素之一.