所蔵: Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting

Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting

The deterministic approach, which utilizes the gradient information in the search process, is prone to trapping at local minima, primarily due to the presence of saddle points and local minima in the non-convex objective function of an artificial neural network (ANN). This study investigated the eff...

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書誌詳細
主要な著者:	Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.
その他の著者:	58169750800
フォーマット:	論文
出版事項:	Korean Society of Civil Engineers 2024
主題:	Machine learning Meta-heuristic algorithms Optimization Statistical tests Time series forecasting Wavelet transform Design of experiments Forecasting Heuristic algorithms Heuristic methods Neural networks Statistics Stochastic models Stochastic systems Stream flow Wavelet transforms Deterministic approach Gradient based Local minimums Machine-learning Meta-heuristics algorithms Optimisations Performance Streamflow forecasting Wavelets transform
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Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting

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