| 基于粗糙集神经网络的收割机需求评价方法 |
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| 引用本文： | 孙健敏,吴昊,李书琴.基于粗糙集神经网络的收割机需求评价方法[J].农机化研究,2009,31(10). |
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| 作者姓名： | 孙健敏 吴昊 李书琴 |
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| 作者单位： | 西北农林科技大学,信息工程学院,陕西,杨凌712100 |
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| 基金项目： | 西北农林科技大学人才资金资助项目，国家高技术研究发展计划项目 |
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| 摘 要： | 结合粗糙集理论和神经网络在信息处理方面的优势,构建了基于粗糙集理论和人工神经网络相结合的收割机需求评价方法的模型,并对陕西省多款收割机进行评价,建立数学模型.实例表明,约简后的知识系统可以获得原知识系统的分类结果,但分类指标却减少了77%,大大减少了信息需求量,可以计算每个属性在评价收割机方面的重要性,给收割机生产厂家提供一份可供参考的指标.
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| 关 键 词： | 收割机 评价 粗糙集理论 神经网络 |
Evaluation Methods of Reaper Requirement Based on the Rough Set Theory and Neural Network |
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| Sun Jianmin,Wu Hao,Li Shuqin.Evaluation Methods of Reaper Requirement Based on the Rough Set Theory and Neural Network[J].Journal of Agricultural Mechanization Research,2009,31(10). |
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| Authors: | Sun Jianmin Wu Hao Li Shuqin |
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| Institution: | College of Information Engineering of Northwest A&F University;Yangling 712100;China |
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| Abstract: | Considering the advantages of Rough Set Theory and Neural Network in information disposal,the paper constructs the model of evaluating methods of reaper requirement based on Rough Set Theory and Artificial Neural Network.Evaluate many reapers in Shaanxi Province by constituting mathematics model.The results reveal that the knowledge system after reduction can acquire the same classification result as the former one.But the classification index reduces by 77%,which decreases the amount of information require... |
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| Keywords: | reaper evaluation rough set theory neural network |
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