Discussion of “Time-Series Prediction of Streamflows of Malaysian Rivers Using Data-Driven Techniques” by Siraj Muhammed Pandhiani, Parveen Sihag, Ani Bin Shabri, Balraj Singh, and Quoc Bao Pham
- 1 September 2021
- journal article
- editorial
- Published by American Society of Civil Engineers (ASCE) in Journal of Irrigation and Drainage Engineering
- Vol. 147 (9), 07021014
- https://doi.org/10.1061/(asce)ir.1943-4774.0001602
Abstract
No abstract availableThis publication has 8 references indexed in Scilit:
- Discussion of “Comparative assessment of time series and artificial intelligence models to estimate monthly streamflow: A local and external data analysis approach” by Saeid Mehdizadeh, Farshad Fathian, Mir Jafar Sadegh Safari and Jan F. AdamowskiJournal of Hydrology, 2020
- Evaluation of preprocessing techniques for improving the accuracy of stochastic rainfall forecast modelsInternational Journal of Environmental Science and Technology, 2019
- Novel hybrid linear stochastic with non-linear extreme learning machine methods for forecasting monthly rainfall a tropical climateJournal of Environmental Management, 2018
- Integrated SARIMA with Neuro-Fuzzy Systems and Neural Networks for Monthly Inflow PredictionWater Resources Management, 2017
- Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approachJournal of Earth System Science, 2017
- Estimating shear stress in a rectangular channel with rough boundaries using an optimized SVM methodNeural Computing & Applications, 2017
- Design of a support vector machine with different kernel functions to predict scour depth around bridge piersNatural Hazards, 2016
- Extreme learning machine assessment for estimating sediment transport in open channelsEngineering with Computers, 2016