基于SPSS的工作面点面结合预测指标研究
Study of integration point and sphere predictor based on SPSS
选取重庆三汇一矿、三矿有代表意义的21201综采工作面运输巷掘进工作面和6402运输巷掘进工作面进行突出指标考察。研究了不同突出征兆对应突出风险度的大小，并采用归一法得出了各种不同突出预兆对应的突出后果严重度，在此基础上利用SPSS软件Logistic回归分析法，拟合得出了点面结合的预测新指标Logistic回归方程。研究结果表明，点面结合的Logistic回归预测指标不仅能实现突出危险性大小的定量化（突出概率），而且能够提高预测不突出准确率和预测突出准确率。
Selecting the typical representative locations such as 21201 fully mechanized working face and 6402 Transport Lane advancing face in Sanhui NO1 and No3 coal mines of Chongqing Tianfu Mining Company, outburst index and the level of risk with different outburst foretoken were researched. With the method of normalization, the severity of outburst consequence corresponding to kinds of outburst foretoken was obtained. And using SPSS(Statistical Package for the Social Science)\\\'s Logistic regression analysis，the Logistic regression equation for predicting new index with combination of \\\"point\\\" and\\\"sphere\\\" was gained. The research results showed ， Logistic regression equation for predicting new index with combination of \\\"point\\\" and \\\"sphere\\\" does not only to realize outburst severity probability quantitatively，but also can improve the forecast accuracy rate whether it will have outburst or not.
赵延旭、孙鑫、杨威、林柏泉、翟成
矿山安全、矿山劳动保护矿山开采
煤与瓦斯突出突出预测点面结合SPSS软件预测准确率
coal and gas outburstoutburst forecastintegration point and sphereSPSSpredict accuracy.
赵延旭,孙鑫,杨威,林柏泉,翟成.基于SPSS的工作面点面结合预测指标研究[EB/OL].(2010-06-02)[2025-08-16].http://www.paper.edu.cn/releasepaper/content/201006-53.点此复制
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