کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1513807 994515 2012 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Design of GIS-based Monitoring and Early-warning System of Landslide Hazard in Diao Zhongba
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
پیش نمایش صفحه اول مقاله
Design of GIS-based Monitoring and Early-warning System of Landslide Hazard in Diao Zhongba
چکیده انگلیسی

To ensure the safety of village called Diao Zhongba, reduce the capital investment and prevent geological disasters, it is necessary to design a monitoring and warning system for it. GIS software ---MAPGIS is selected to be the base platform, whose basic functions are applied to manage the engineering geological information in Diao Zhongba, coupled with the research on the secondary development library based on MAPGIS, thus achieving the early-warning of landslide. This warning system conducts detailed analysis on various aspects, such as system requirements, system design, system environment selection, specific database design, warning function module design, etc. In this system, a total of 16 kinds of models are designed, which can be divided into three categories, long-term prediction, short-term prediction, critical-sliding prediction. Long-term prediction model includes the limit analysis method, golden section method, and dynamic fractal dimension model. Medium-range forecast model includes biological growth model, cusp catastrophic model, nonlinear regression analysis model, the gray GM (1, 1) model, BP neural network model, exponential smoothing, Kalman filtering method. Critical-sliding prediction model includes Zhaitengdixiao model, Su aijun model, sliding deformation power model, gray displacement vector angle method, collaborative model. The automation and information processing for landslide hazards in this system can provide basis for early warning of landslide in Diao Zhongba.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy Procedia - Volume 16, Part B, 2012, Pages 1174-1179