| 基于粗糙集和D-S证据理论的信息融合技术应用研究 |
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| 引用本文： | 付华,聂小芳.基于粗糙集和D-S证据理论的信息融合技术应用研究[J].传感器与微系统,2010,29(6). |
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| 作者姓名： | 付华 聂小芳 |
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| 作者单位： | 辽宁工程技术大学,电气与控制工程学院,辽宁,葫芦岛,125105 |
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| 基金项目： | 国家自然科学基金资助项目(50874059); 辽宁省重大科技计划资助项目(2007231003); 辽宁省优秀人才基金资助项目(2007R24); 辽宁省创新团队基金资助项目(2007T071) |
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| 摘 要： | 针对井下信息量大、噪声多、参数多、动态等特征,提出了一种基于粗糙集数据挖掘和D-S证据理论优化信息融合技术的矿井环境监测方法。采用粗糙集对井下信息进行预处理;利用径向基函数(RBF)神经网络建立了井下环境识别模型;利用D-S证据理论进行两级融合决策,并对井下安全状况进行判断。仿真结果表明:该方法提高了井下信息的识别和决策效果,极大地降低了不确定性。
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| 关 键 词： | 粗糙集 RBF神经网络 信息融合 D-S证据理论 矿井环境监测 |
Application research on information fusion technology based on rough set and D-S evidence theory |
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| FU Hua,NIE Xiao-fang.Application research on information fusion technology based on rough set and D-S evidence theory[J].Transducer and Microsystem Technology,2010,29(6). |
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| Authors: | FU Hua NIE Xiao-fang |
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| Affiliation: | FU Hua,NIE Xiao-fang (School of Electrical , Control Engineering,Liaoning Technical University,Huludao 125105,China) |
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| Abstract: | Aimed at the characteristics of coal mine such as large quantity of information,much noises,many parameters and dynamic characteristics,etc.A coal mine environmental monitoring method of information fusion technology optimized by rough set data mining and D-S evidence theory are conducted.The rough set was carried out to deal with the information of coal mine.Distinguishing model of coal mine environment was established by using the radial basic function(RBF)neural network.Two-graded fusion decision was con... |
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| Keywords: | rough set(RS) radial basic function(RBF)neural network information fusion D-S evidence theory coal mine environmental monitoring |
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