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计算机系统应用英文版:2011,20(2):49-52,156
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小生境技术在遗传规划中的应用
(山西财经大学 信息与管理学院,太原 030006)
Application of Niche Technology to Genetic Programming
(Department of Information Management, Shanxi University of Finance & Economics, Taiyuan 030006, China)
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Received:May 17, 2010    Revised:June 23, 2010
中文摘要: 为了提高遗传规划算法的性能,把遗传算法中的小生境技术运用到遗传规划中,提出了改进的遗传规划算法(NGP)。该算法首先对原始训练集进行数据拟合,然后应用小生境技术跟踪拟合函数的极值点,并根据拟合函数的维数的不同,分别计算极值点在自变量维上的欧氏距离并排序,选取欧式距离较大且数量不超过原始训练集10%的极值点,加入到原始训练集中作为新的训练集,最后用遗传规划算法处理新训练集。在符号回归实验中对NGP 的准确率进行了测试,说明了该算法的准确性和有效性。
中文关键词: 小生境  遗传规划  极值点  符号回归  效率
Abstract:To improve the performance of genetic programming algorithm, the niche technology used in genetic algorithm is applied to genetic programming. It is improvement of genetic programming algorithm, which is called NGP in the next text. First, the algorithm fits the data with the original training set. Second, it tracks the extreme points of the fitting function, and according to the dimensions of the fitting function, calculate the extreme points’ Euclidean distance in the independent variable dimension and order it. Then it selects the extreme points whose Euclidean distance is larger and does not exceed the number of the ten percent of the original training set, and added them to the original training set as new training set. Finally, it deals with new training set using genetic programming. In this paper, we use symbolic regression experiment to test the accuracy of the NGP. It illustrates the accuracy and effectiveness of the algorithm.
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基金项目:山西省高校科技研究与开发项目(20081023);山西自然基金 (2010011022-1).
引用文本:
刘国炜,常新功.小生境技术在遗传规划中的应用.计算机系统应用,2011,20(2):49-52,156
LIU Guo-Wei,CHANG Xin-Gong.Application of Niche Technology to Genetic Programming.COMPUTER SYSTEMS APPLICATIONS,2011,20(2):49-52,156