基于粗糙集理论的板栗病害诊断研究

Diseases Diagnosis for Chestnut Based on Rough Set Theory

粗糙集理论可以处理不确定性数据,特别在处理农业领域的不完备数据方面具有优势。论述了采用粗糙集方法获取板栗病害的诊断规则以及进行诊断推理的详细过程和方法,主要包括数据预处理、属性约简、规则获取和诊断推理等。通过实验验证,该方法可以用于板栗的病害诊断,并且能够得到准确的诊断推理结果。

Rough sets theory can be used to process uncertainty data, especially to process incomplete data in agricultural section. In this paper, we presented our approach for diagnostic reasoning and rule acquiring for chestnut diseases based on rough set theory, including data preprocessing, attribute reduction, rule acquisition, diagnostic reasoning, and so on. The experiment results showed that rough set theory could be used for disease diagnosis for chestnut with excellent results.