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首页> 外文期刊>European Journal of Soil Biology >Performance investigation of the dam intake physical hydraulic model using Support Vector Machine with a discrete wavelet transform algorithm
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Performance investigation of the dam intake physical hydraulic model using Support Vector Machine with a discrete wavelet transform algorithm

机译：具有离散小波变换算法的支持向量机水坝摄入物理液压模型的性能调查

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In the present study hydraulic scaled model was conducted to evaluate an intake structure and checking its safety hydraulic performance. An investigation on the structural and mechanical equipment performance was performed by testing a scaled model to determine discharge capacity and head losses. In addition, the novel method established on Support Vector Machines (SVM) coupled through discrete wavelet transform was designed and adapted to estimate head loss at inlet and outlet section of the horizontal intake structure. Estimation and prediction results of SVM-WAVELET model was compared with genetic programming (GP) and artificial neural networks (ANNs) models. The model test results of SVM WAVELET approach reveal more accuracy in prediction and also attain improved generalization capabilities than GP and ANN. Furthermore, results specified that advanced SVM-WAVELET model can be applied confidently for auxiliary research to formulate predictive model for head loss at inlet and outlet section. Consequently, it was found that using of SVM-WAVELET is principally encouraging as an alternate strategy to predict the head loss as a representative of inner pressure head at intake structure. (C) 2017 Elsevier B.V. All rights reserved.
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