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基于改进的基因表达式编程在重金属形态获取中的应用
引用本文:李俊霞,刘富军,张智攀. 基于改进的基因表达式编程在重金属形态获取中的应用[J]. 数学杂志, 2016, 36(4): 831-840
作者姓名:李俊霞  刘富军  张智攀
作者单位:河北工程大学信息与电气工程学院, 河北 邯郸 056038,河北工程大学信息与电气工程学院, 河北 邯郸 056038,河北工程大学信息与电气工程学院, 河北 邯郸 056038
基金项目:国家自然科学基金资助(41373101).
摘    要: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.

关 键 词: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
收稿时间:2014-07-29
修稿时间:2014-11-04

AN HEAVY METALS MORPHOLOGY ACQUIRED METHOD BASED ON IMPROVED GEP
LI Jun-xi,LIU Fu-jun and ZHANG Zhi-pan. AN HEAVY METALS MORPHOLOGY ACQUIRED METHOD BASED ON IMPROVED GEP[J]. Journal of Mathematics, 2016, 36(4): 831-840
Authors:LI Jun-xi  LIU Fu-jun  ZHANG Zhi-pan
Affiliation:School of Information and Electric Engineering, Hebei University of Engineering, Handan 056038, China,School of Information and Electric Engineering, Hebei University of Engineering, Handan 056038, China and School of Information and Electric Engineering, Hebei University of Engineering, Handan 056038, China
Abstract: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.
Keywords:gene expression programming  JM-GEP  heavy metals prediction model  Shannon information entropy  knowledge acquisition
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