Combining statistical machine learning models with ARIMA for water level forecasting: The case of the Red river-Reference-Cited by-同舟云学术

Combining statistical machine learning models with ARIMA for water level forecasting: The case of the Red river

Published:2020-08 Issue: Volume:142 Page:103656
ISSN:0309-1708
Container-title:Advances in Water Resources
language:en
Short-container-title:Advances in Water Resources

Author:

Phan Thi-Thu-Hong,Nguyen Xuan Hoai

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference73 articles.

1. Stream flow forecasting of poorly gauged mountainous watershed by least square support vector machine, fuzzy genetic algorithm and M5 model tree using climatic data from nearby station;Adnan;Water Resour. Manage.,2018

2. Model selection for ecologists: the worldviews of AIC and BIC;Aho;Ecology,2014

3. An introduction to kernel and nearest-neighbor nonparametric regression;Altman;Am. Stat.,1992

4. Forecasting with prediction intervals for periodic autoregressive moving average models: FORECASTING WITH PREDICTION INTERVALS FOR PARMA MODELS;Anderson;J. Time Ser. Anal.,2013

5. Applicability of -support vector machine and artificial neural network for flood forecasting in humid, semi-humid and semi-arid basins in china;Bafitlhile;Water (Basel),2019

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