会议专题

Research on Rough Set and Decision Tree Method Application in Evaluation of Soil Fertility Level

Clustering, rough sets and decision tree theory were applied to the evaluation of soil fertility levels, and provided new ideas and methods among the spatial data mining and knowledge discovery. In the experiment, the rough sets-decision tree evaluation model establish by 1400 study samples, the accu-racy rate is 92% of the test. The results show :model has good generalization ability; using the clustering method can effectively extract the typical samples and reducing the training sample space; the use of rough sets attribute reduc-tion, can remove redundant attributes, can reduce the size of decision tree decision-making model, reduce the decision-making rules and improving the decision-making accuracy, using the combination of rough set and decision tree decision-making method to infer the level of a large number of unknown samples.

rough set decision tree clustering data mining soil evaluation productivity grade

Guifen Chen Li Ma

College of Information and Technology Science, Jilin Agricultural University,Chang Chun, Jilin, China

国际会议

The 4th IFIP International on Computer and Computing Technologies in Agriculture and the 4th Symposium on Development of Rural Information(第四届国际计算机及计算机技术在农业中的应用研讨会暨第四届中国农业信息化发展论坛 CCTA 2010)

南昌

英文

408-414

2010-10-22(万方平台首次上网日期,不代表论文的发表时间)