Dangerous Degree Evaluation System of Mine Debris Flow Based on IGA-BP
Автор: Xicheng Xue, Jisong Bi, Lingling Chen, Yan Chen
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 3 vol.3, 2011 года.
Бесплатный доступ
Taking the western Qinling Mountain, in the southern Shaanxi Province of china, as an example, based upon comprehensive analysis of geological data for 20 debris flow gullies, the author has put forward a series of indices system and has developed one evaluation system called “dangerous degree evaluation system of mine debris flow based on IGA-BP”. This system adopts Visual Basic 6.0 and Access technology to manage database, adopts immune genetic algorithm to optimize the hidden layer structure and network parameters of BP neural network and adopts sample model of mine debris flow whose dangerous degree has been known to realize the BP neural network evaluation of the debris flow risk which to be determined. The calculating results show that this evaluation method has high reliability and simplicity of operation, and it can make comprehensive evaluation precisely. The evaluation results have important guiding significance in the prevention and reduction mine debris flow.
Qinling, mine debris flow, dangerous degree evaluation system, immune genetic algorithm, artificial neural network
Короткий адрес: https://sciup.org/15010190
IDR: 15010190
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