基于人工神经网络的滑坡概率预测

A. Roy, Md Mominul Islam
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引用次数: 4

摘要

滑坡是一种自然现象。但山体滑坡也有人为原因。既然这是自然现象,人类无法阻止。但是,通过有效的预测,可以减轻损失和财产损失。本研究试图预测孟加拉国滑坡的发生,研究区域为吉大港市公司区和考克斯巴扎尔。造成山体滑坡的原因有很多。在这种情况下,考虑了五个参数来预测滑坡。这些是降雨数据,前五天的降雨数据,海拔,坡度,土壤类型。高程和坡度数据来源于吉大港市区和考克斯巴扎尔的DEM。来自天气预报的降雨数据。建立了人工神经网络模型。首先假设一个权重,然后使用反向传播算法调整权重,以获得更好的预测结果。使用训练数据集训练模型,使用测试数据集评估模型。使用该模型,准确率达到最高的93.87%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting the Probability of Landslide using Artificial Neural Network
Landslide is a natural occurrence. But there are also some manmade reason for landslides. As is it is a natural occurrence, man can’t prevent this. But the damages can be mitigated and loss of properties lives by an efficient prediction of this. This study tries to predict the occurrence of landslides in Bangladesh and study area was Chittagong City Corporation area and Cox’s bazar. There are many reason for landslides. In the case of five parameters are considered for predicting landslides. These are rainfall data, rain data for previous five days, elevation, slope, soil type. Elevation and slope are collected from DEM of Chittagong City Corporation area and Cox’s bazar. Rain data from weather forecast. An artificial neural network model is developed. Initially a weight is assumed then adjust the weight using back-propagation algorithm for getting better prediction result. Train the model using train dataset and evaluate the model using test dataset. The accuracy become highest 93.87% using this model.
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