城市地质Issue(z1)：37-41,5.
基于粗糙集理论与遗传规划的地表下沉系数预测研究
Subsidence Coefifcient Prediction Based on Rough Set Theory and Genetic Programming
摘要
Abstract
Taking the advantages of rough set theory, such as dealing with large quantities of data and eliminating redundant information, significance of main influencing factors of subsidence coefficient was calculated, training sample data of genetic programming were reduced, and the prediction model of subsidence coefifcient combining rough set and genetic programming is established. The prediction results of the proposed model are compared with those of BP. The ifnal result shows that the proposed model possesses characteristic of high accuracy and rapid convergence, is feasible to be used to predict the subsidence coefifcient.关键词
粗糙集/属性约简/遗传规划/下沉系数Key words
Rough set/Attribution reduction/Genetic programming/Subsidence coefifcient分类
矿业与冶金引用本文复制引用
翟淑花,丁桂伶,张亮..基于粗糙集理论与遗传规划的地表下沉系数预测研究[J].城市地质,2015,(z1):37-41,5.
