| 贝叶斯理论在室内空气质量等级识别中的应用 |
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| 引用本文： | 王明芳,谭骏珊,朱明娥.贝叶斯理论在室内空气质量等级识别中的应用[J].中国环境监测,2010,26(2):63-67. |
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| 作者姓名： | 王明芳 谭骏珊 朱明娥 |
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| 作者单位： | 中南林业科技大学计算机与信息工程学院,湖南,长沙,410004 |
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| 基金项目： | 国家自然科学基金项目(50878078) |
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| 摘 要： | 利用贝叶斯理论在不确定性的表示、推理方面的优势,结合多传感器数据融合技术,以新装修居室的空气为研究对象,构建基于贝叶斯理论的室内空气质量等级的数据融合模型,并借助JAVA语言实现基于贝叶斯理论的室内空气质量等级方法。实验证明该方法正确可行,其计算结果稳定准确。
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| 关 键 词： | 贝叶斯理论 室内空气质量 等级识别 |
| 收稿时间： | 2009/4/21 0:00:00 |
| 修稿时间： | 2009/12/18 0:00:00 |
Application of Bayesian Theory to Indoor Air Quality Grade Diagnosis |
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| WANG Ming-fang.Application of Bayesian Theory to Indoor Air Quality Grade Diagnosis[J].Environmental Monitoring in China,2010,26(2):63-67. |
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| Authors: | WANG Ming-fang |
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| Institution: | Computer and Information Engineering School, Central South University of Forestry & Technology, Changsha 410004, China |
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| Abstract: | In this article, the indoor air quality grade identification methodology based on Bayesian is proven to be practical by using the advantages of Bayesian Theory in the uncertainty of expression and combining the multi-sensor data fusion technology, taking the newly decorated indoor air as the research object, constructing data fusion model of indoor air quality grade recognition based on Bayesian theory, and utilizing JAVA language. Experiments show that this methodology is feasible and correct, and the calculating result of this method is stable and accurate. |
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| Keywords: | Bayesian theory Indoor air quality Grade identify |
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