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-  2016 

基于改进的基因表达式编程在重金属形态获取中的应用
AN HEAVY METALS MORPHOLOGY ACQUIRED METHOD BASED ON IMPROVED GEP

Keywords: 基因表达式编程 重金属形态预测建模 跳跃基因表达式编程 信息熵 知识获取
gene expression programming JM-GEP heavy metals prediction model Shannon information entropy knowledge acquisition

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Abstract:

本文研究了基因表达式编程在重金属形态获取中的应用问题. 利用改进的基因表达式编程和Shannon 信息熵方法, 验证了算法的高效性, 获得了重金属形态预测模型并从该模型中获取了重金属的形态知识的结果. 该新模型方法还可广泛用于其他时间序列预测问题的研究.
In this paper, we use the gene expression programming application in heavy metal form questions. By using an improved gene expression programming and Shannon entropy, we demonstrate the efficiency of the algorithm, and get heavy metal form prediction model and obtain the result of the heavy metal forms of knowledge from the model. The new model also can be widely used in other time series prediction problems

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