基于粗糙集与神经网络的农机化发展水平评估方法

Evaluating Methods of Agricultural Mechanization Based on the Rough Set Theory and Neural Network Technology

在分析现有农业机械化发展水平评价方法的基础上 ,提出了粗糙集理论与人工神经网络技术相结合的农业机械化发展水平评价指标简化体系和评价方法。实例表明 ,约简后的指标体系可以获得原有指标体系的分类结果 ,但比原有模型少了 6 0 %的指标 ,大大减少了信息的需求量 ,为农机化水平评价提供了一种新的途径。

The evaluation of developing level of agricultural mechanization should be improved to reinforce the function of agricultural mechanization. By analyzing an existing method of evaluating the level of agricultural mechanization, this paper presented a new simplified evaluating method on basis of the rough set theory and neural network technology. The method could educe the same evaluating result as the existing method, and could reduce about 60% information requirements as the previous method.