摘要
为了提高预测的准确性,结合基于突变算子的基因表达式和一种基于群体搜索技术的演化算法,提出了改进的GEP方法,并用其对数据进行演化建模。实例测试的结果表明,使用改进的GEP方法得到的模型要优于GP和单纯的GEP方法得到的模型,本方法具有良好的拟合度和预测精度。
To improve the veracity of forecasting, a hybrid GEP algorithm was presented, which combined GEP based on mutation operator and evolutionary algorithm based on colony-search strategy. The new GEP algorithm was applied to establish models with testing data. The applications show that the models set up by the new GEP algorithm are superior to the models set up by GP and simple GEP. The new algorithm has high-blooded forecasting accuracy.
出处
《计算机应用》
CSCD
北大核心
2005年第12期2783-2786,共4页
journal of Computer Applications
基金
湖北省自然科学基金资助项目(2003ABA043)
湖北省人文基地资助项目(2004B0011)
关键词
基因表达式程序设计
遗传算法
突变算子
演化建模
Gene Expression Programming(GEP)
Genetic Algorithms(GA)
mutation operator
evolutionary modeling