中南大学学报（自然科学版）2012，Vol.43Issue(12)：4788-4795,8.
基于进化支持向量机的滑坡地下水位动态预测
Prediction of ground water level in landslides based on genetic-support vector machine
摘要
Abstract
Prediction of ground water level is ignificant in evaluation of landslide stability. The evolution process of the ground water level in landslides is a nonlinear dynamic system which is controlled by the hydrogeology condition and to suffers from comprehensive effects by multiple influential factors such as rainfall, reservoir water level, temperature and so on. There is the nonlinear response between ground water level and its influencing factors. According to ground water level data of Baijiabao landslide in the Three Gorges reservoir area, the response relationship between influential factors and ground water level variation was analysed, and the characteristics of ground water level in the landslide were discussed. Using a nonlinear genetic algorithm and support vector regression (GA-SVR) model, the values of ground water level in landslides is predicted. Predicted values of the GA-SVR model are consistent with the measured values. The mean squared error of the GA-SVR model is only 0.013, which is less than those of radial basis function artificial neural network (RBF-ANN) model by 154%. And the squared correlation coefficient of the GA-SVR model reaches 0.929, which is more than those of RBF-ANN model by 10%. It is indicated that the GA-SVR model has a great fitting and generalization ability. It is an effective method for prediction of ground water level in landslides.关键词
地下水位/预测/滑坡/支持向量机/遗传算法Key words
ground water level/ prediction/ landslides/ support vector machine/ genetic algorithm分类
天文与地球科学引用本文复制引用
彭令,牛瑞卿,叶润青,赵艳南..基于进化支持向量机的滑坡地下水位动态预测[J].中南大学学报（自然科学版）,2012,43(12):4788-4795,8.基金项目
国家重点基础研究发展计划("973"计划)项目(2011CB710601) （"973"计划）
国家高技术研究发展计划("863"计划)项目(2012AA121303) （"863"计划）
国土资源部三峡库区三期地质灾害防治重大科学研究项目(SXKY3-6-2) （SXKY3-6-2）
