| 煤矿瓦斯预测知识获取模型的应用研究 |
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| 引用本文： | 孙林嘉,李茹,屈元子.煤矿瓦斯预测知识获取模型的应用研究[J].计算机工程,2009,35(12):169-171. |
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| 作者姓名： | 孙林嘉 李茹 屈元子 |
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| 作者单位： | 1. 山西大学计算机与信息技术学院,太原,030006
2. 山西大学计算机与信息技术学院,太原,030006;山西大学计算机智能与中文信息处理省部共建教育部重点实验室,太原,030006 |
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| 基金项目： | 山西省高校拔尖人才基金，太原市科技明星专项基金，山西大学大学生科研训练基金 |
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| 摘 要： | 将粗糙集与神经网络结合,提出由样本更新、粗糙集预处理、神经网络训练、规则提取4个模块组成的煤矿瓦斯预测知识获取模型,将其应用于实时数据进行实验,结果表明,该模型实时性好、可靠性及精度高,可以较好地解决煤矿瓦斯预测知识获取困难的问题,为煤矿瓦斯预测专家系统知识库的建立奠定基础。
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| 关 键 词： | 知识获取 煤矿瓦斯预测 粗糙集 神经网络 |
| 修稿时间： | |
Application Research of Knowledge Acquisition Model for Colliery Gas Forecast |
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| SUN Lin-jia,LI Ru,QU Yuan-zi.Application Research of Knowledge Acquisition Model for Colliery Gas Forecast[J].Computer Engineering,2009,35(12):169-171. |
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| Authors: | SUN Lin-jia LI Ru QU Yuan-zi |
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| Affiliation: | 1.School of Computer & Information Technology;Shanxi University;Taiyuan 030006;2.Computer Intelligent and Chinese Information Processing of the Ministry Education Key Laboratory Built Together by Province and Department;Taiyuan 030006 |
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| Abstract: | By combining rough sets and neural networks,this paper develops a knowledge acquisition model for colliery gas forecast,which consists of four modules:sample refreshment,rough sets preprocessing,neural network training and rules extraction.It is applied in the real-time data,whose results show that it solves the problem of the knowledge acquisition difficulty of colliery gas forecast,and has good real-time characteristic,high reliability and perfect precision.The model provides foundation for establishing k... |
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| Keywords: | knowledge acquisition colliery gas forecast rough sets neural networks |
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