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粗糙集理论在农业机械故障诊断中的应用
Application for Agricultural Mechanical Fault Diagnosis with Rough Set Theory
【摘要】 粗糙集理论是一种处理模糊和不确定知识的工具,它能够有效地确定哪些知识是冗余的,哪些知识是有用的,有效地减少训练时间,从而很好地弥补了人工智能的不足。因此,基于传统人工智能的机械故障诊断技术已开始转向以粗糙集理论为代表的计算智能领域。以某型农业机械故障诊断为例,选择运用粗糙集理论,通过对故障诊断原始数据的分析处理和属性约简后,得到了简明的故障诊断规则,取得了良好地故障诊断效果。
【Abstract】 Rough set theory is a tool for dealing with fuzzy and uncertain knowledge.It can point out effectively what knowledge is redundant and what knowledge is useful,and it can reduce the training period effectively,thus to make up the deficiency of artificial intelligence.Therefore,the mechanical fault diagnosis based on traditional artificial intelligence has turned into the computational intelligence based on rough set theory.In this paper,taking an example of a type of agricultural mechanical fault diagnosis,it simplifies the fault diagnosis rules and achieves good effect to fault diagnosis with rough sets theory through the original data analysis and attribute reduction.
【Key words】 agricultural machine; fault diagnosis; rough set; attribute reduction;
- 【文献出处】 农机化研究 ,Journal of Agricultural Mechanization Research , 编辑部邮箱 ,2013年04期
- 【分类号】S232.7
- 【被引频次】5
- 【下载频次】114