Hybrid particle swarm optimization and group method of data handling for short-term prediction of natural daily streamflows

New double decomposition deep learning methods for river water level forecasting

(2022) A.A. Masrur Ahmed et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Hybrid machine learning models for estimating total organic carbon from mineral constituents in core samples of shale gas fields

(2022) C.M. Saporetti et al.   MARINE AND PETROLEUM GEOLOGY

On the Investigation of Monthly River Flow Generation Complexity Using the Applicability of Machine Learning Models

(2021) Ma Shaofu et al.   COMPLEXITY

Comparing linear and non-linear data-driven approaches in monthly river flow prediction, based on the models SARIMA, LSSVM, ANFIS, and GMDH

(2021) Hedieh Khodakhah et al.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Modeling monthly streamflow in mountainous basin by MARS, GMDH-NN and DENFIS using hydroclimatic data

(2020) Rana Muhammad Adnan et al.   NEURAL COMPUTING & APPLICATIONS

A deep learning approach for hydrological time-series prediction: A case study of Gilgit river basin

(2020) Dostdar Hussain et al.   Earth Science Informatics

Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting

(2019) Le et al.   Water

An Overview of Hydropower Reservoirs in Brazil: Current Situation, Future Perspectives and Impacts of Climate Change

(2018) Viviane de Souza Dias et al.   Water

Short-Term Load Forecasting Based on Elastic Net Improved GMDH and Difference Degree Weighting Optimization

(2018) Wei Liu et al.   Applied Sciences-Basel

An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction

(2018) Zaher Mundher Yaseen et al.   JOURNAL OF HYDROLOGY

Development of a Hybrid Wavelet Packet- Group Method of Data Handling (WPGMDH) Model for Runoff Forecasting

(2016) Vahid Moosavi et al.   WATER RESOURCES MANAGEMENT

High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

(2015) Anton Akusok et al.   IEEE Access

The vulnerability of hydropower production in the Zambezi River Basin to the impacts of climate change and irrigation development

(2014) Randall Spalding-Fecher et al.   Mitigation and Adaptation Strategies for Global Change

An artificial neural network (p,d,q) model for timeseries forecasting

(2009) Mehdi Khashei et al.   EXPERT SYSTEMS WITH APPLICATIONS

Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling

(2009) Hoshin V. Gupta et al.   JOURNAL OF HYDROLOGY