Application of wavelet analysis and a particle swarm-optimized support vector machine to predict the displacement of the Shuping landslide in the Three Gorges, China
出版年份 2014 全文链接
标题
Application of wavelet analysis and a particle swarm-optimized support vector machine to predict the displacement of the Shuping landslide in the Three Gorges, China
作者
关键词
Landslides, Displacement prediction, Wavelet analysis, Particle swarm-optimized support vector machine (PSO-SVM), Three Gorges
出版物
Environmental Earth Sciences
Volume 73, Issue 8, Pages 4791-4804
出版商
Springer Nature
发表日期
2014-10-13
DOI
10.1007/s12665-014-3764-x
参考文献
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- Drought–flood variation and its correlation with runoff in three headstreams of Tarim River, Xinjiang, China
- (2013) Yuan Bai et al. Environmental Earth Sciences
- Deformation and mechanism of landslide influenced by the effects of reservoir water and rainfall, Three Gorges, China
- (2013) Min XIA et al. NATURAL HAZARDS
- Prediction of Landslide Displacement Using Grey and Artificial Neural Network Theories
- (2012) Lv Yiqing et al.
- Automatic detection of erythemato-squamous diseases using PSO–SVM based on association rules
- (2012) Mohammad Javad Abdi et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Soil moisture retrieving using hyperspectral data with the application of wavelet analysis
- (2012) Jian Peng et al. Environmental Earth Sciences
- A genetic algorithm–support vector machine method with parameter optimization for selecting the tag SNPs
- (2012) İlhan İlhan et al. JOURNAL OF BIOMEDICAL INFORMATICS
- Displacement prediction in colluvial landslides, Three Gorges Reservoir, China
- (2012) Juan Du et al. Landslides
- Deformation Prediction of Landslide Based on Improved Back-propagation Neural Network
- (2012) Huangqiong Chen et al. Cognitive Computation
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- (2011) Biswajeet Pradhan et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Landslide displacement prediction based on combining method with optimal weight
- (2011) Xiuzhen Li et al. NATURAL HAZARDS
- A particle swarm-optimized support vector machine for reliability prediction
- (2011) Isis Didier Lins et al. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
- Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia
- (2010) Biswajeet Pradhan ADVANCES IN SPACE RESEARCH
- A new practical method for prediction of geomechanical failure-time
- (2010) A. Mufundirwa et al. INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
- Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches
- (2010) B. Pradhan Journal of the Indian Society of Remote Sensing
- Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area
- (2010) Biswajeet Pradhan et al. Geomatics Natural Hazards & Risk
- Landslide prediction based on wavelet analysis and cusp catastrophe
- (2009) Changdong Li et al. Journal of Earth Science
- Partially linear support vector machines applied to the prediction of mine slope movements
- (2009) J.M. Matías et al. MATHEMATICAL AND COMPUTER MODELLING
- Movement of the Shuping landslide in the first four years after the initial impoundment of the Three Gorges Dam Reservoir, China
- (2008) Fawu Wang et al. Landslides
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