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中文摘要：
针对某决策方案，提出了一种基于聚类算法、且能面向较大规模群体、考虑成员学习进化能力并有效收敛群体意见的群体一致性修正方法。首先设计了群体成员学习进化决策程序；接着，借助一种能够处理大数据量聚类的C-均值类型聚类算法，通过梯度下降法逐渐修正群体一致性来避免因个别．成员意见偏离太大而引起的群决策失误；最后通过计算机仿真和实验对比分析验证了该方法的正确、有效性。
英文摘要：
According to a certain decision project, a group-consistency amendment method based on a kind of optimized c means clustering algorithm, aiming at lager scale group, and considering the ability of evolution by learning is presented. First, the evolutionary program of the group member is given. Then, a gradual decision method of amendment group-consistency by optimizing attributes ＇ weight is presented to avoid the fault caused by individual idea divergence. Lastly, the velidity of this method is proved by the computer simulation and comparing analysis.
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