| 基于贝叶斯分类器的煤与瓦斯突出强度预测研究 |
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| 引用本文： | 边平勇,石永奎,张序萍.基于贝叶斯分类器的煤与瓦斯突出强度预测研究[J].佳木斯工学院学报,2013(6):890-894. |
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| 作者姓名： | 边平勇 石永奎 张序萍 |
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| 作者单位： | [1]山东科技大学基础课部,山东泰安271019 [2]山东科技大学资源与环境工程学院,山东青岛266510 |
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| 摘 要： | 摘。要：选取了影响煤与瓦斯突出的5个因素作为属性条件，把突出强度作为目标变量，利用训练样本对朴素贝叶斯分类器模型进行了学习训练，对测试样本进行了预测，从结果来看精确度较高．因此朴素贝叶斯分类器模型预测煤与瓦斯突出强度是有效的．
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| 关 键 词： | 朴素贝叶斯分类器 煤与瓦斯突出 预测 |
Research of Coal and Gas Outburst Prediction Based on Naive Bayes Classifier |
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| Affiliation: | BIAN Ping - yong, Sill Yong - kui, ZHANG Xu -ping (1. Basic Cotwse Departmmt, SUST, Taian 271019, China;2.. College of Resources and Environmental Eng., SUST, Qingdao 266510,China) |
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| Abstract: | Five factors affecting coal and gas outburst were selected as condition attributes, and coal and gas outburst intensity as the target variable. The naive Bayes classifier model was trained using the training sam- pies. The coal and gas outburst intensity was forecasted using the test samples. And the prediction results showed that the prediction accuracy of the NB model is higher. So the NB method is effective for coal and gas outburst intensity prediction. |
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| Keywords: | naive Bayes classifier coal and gas outburst forecast |
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