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, this paper proposed an uncertainty NNSB-OPTICS clustering and applied to landslide prediction in order to improve the prediction accuracy. Firstly, this algorithm optimized the expansion strategy of OPTICS-PLUS algorithm, which avoided the manual setting of density threshold and improved 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 put forward EC distance formula, which could deal with the uncertain rainfall data effectively. Finally, this paper applied the uncertain NNSB-OPTICS clustering algorithm to predict landslide hazard in Baota district of Yan'an city and the landslide prediction accuracy reached into 87.9%. The experimental results show that this method can effectively improve the accuracy of landslide prediction and has high feasibility.

[2019-01-05] Printed Article /doc/2017.06.0653/v2