Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes: Supplementary material
Published: 15 October 2017| Version 1 | DOI: 10.17632/fjr8244m35.1
Supplementary material for the paper entitled "Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes"
National Technical University of Athens - Zografou Campus
Statistics, Hydrology, Machine Learning, Machine Learning Algorithm, Support Vector Machine, Time Series Prediction, Forecasting, Process Simulation, Exploratory Analysis, Time Series, Generalisation, Stochastic Modeling, Statistical Analysis, Autoregressive Integrated Moving Average Model, Autoregressive Moving Average Model, Forecasting Model, Neural Networks, Box-Jenkins Method, Time Series Forecasting, Stationary Process, Comparative Research