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Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Conventional technology only considers one factor,which cannot achieve the same precision of gas outburst zone as multi-factor prediction methods.Taking an area as an example,the support vector machine (SVM) network based on genetic algorithm was used to predict the gas content.The porosity was used as the discriminant factor of tectonic coal.Distribution of tectonic coal was obtained by probabilistic neural network (PNN).The quasi-density inversion method based on natural gamma curve was in-troduced to obtain the lithology of coal seam roof.Characteristics of gas content,tectonic coal distribution and coal seam roof lithology was comprehensively considered to establish the gas outburst risk area comprehensive fore-casting method,which provided a theoretical basis to determine the gas outburst danger zone.The prediction results were consistent with actual prominent positions,which proved that this comprehensive forecasting method had high accuracy in this study area. [ABSTRACT FROM AUTHOR]