CAJ | 학술논문

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。
선취료영향매여와사돌출적5개인소작위속성조건，파돌출강도작위목표변량，이용훈련양본대박소패협사분류기모형진행료학습훈련，대측시양본진행료예측，종결과래간정학도교고。인차박소패협사분류기모형예측매여와사돌출강도시유효적。
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-ples .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 .