Study on forest pests and diseases forecast based on the rough set theory

被引：0
|
作者：
机构：
[1] Zhang, Hong Han
[2] Zhang, Yan Rong
来源：
Zhang, Hong Han | 1600年 / Science and Engineering Research Support Society卷 / 07期
关键词：
Forecasting - Timber - Expert systems - Forestry;
D O I：
10.14257/ijunnesst.2014.7.4.7
中图分类号：
学科分类号：
摘要：
This paper applies the rough set theory and artificial intelligence technology into the field of forestry diseases and pests. It proposed the model of forestry diseases and pests forecasting in the demonstration. Through the model validation and accuracy analysis, the accuracy of the result is high, and forecast results with the actual situation are match.. In addition, it proposed an improvement attribute reduction algorithm based on discernibility matrix. Reduced conditional attribute set of forestry diseases and pests forecasting based on the algorithm. Through the extraction and reduction of generation rules, obtained a new f forestry diseases and pests forecasting model based on rough set theory. By verifying, the model has achieved a good result. © 2014 SERSC.
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