Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting

• Main Authors: Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.
• Other Authors: 58169750800
• Format: Article
• Published: Korean Society of Civil Engineers 2024
• Subjects: 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

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...