不确定NNSB-OPTICS聚类算法在滑坡危险性预测中的研究与应用

Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》

毛伊敏 陈华彬 李忠利 张灿龙

Abstract： Since the rainfall and other uncertainties are difficult to obtain and effectively deal with in landslide hazard prediction, and the existence of setting density threshold and high time complexity in the OPTICS-PLUS algorithms, in order to improve the prediction accuracy, this paper proposed an uncertainty NNSB-OPTICS clustering algorithm and applied to landslide prediction. Firstly, the expansion strategy of OPTICS-PLUS algorithm is optimized, which avoids the manual setting of density threshold and improves the efficiency of the algorithm. Then, according to the distribution characteristics of rainfall data, combined with EW distance formula and cloud model theory, this paper puts forward EC distance formula, can deal with the uncertain rainfall data effectively. Finally, the uncertain NNSB-OPTICS clustering algorithm is applied to predict landslide hazard in Baota district of Yan’an city and the landslide prediction accuracy reaches into 87.9%. The experimental results show that this method can effectively improve the accuracy of landslide prediction and has high feasibility.

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