Streamflow Prediction Based on Artificial Intelligence Techniques

Daily streamflow forecasting in Sobradinho Reservoir using machine learning models coupled with wavelet transform and bootstrapping

(2021) Samuel Vitor Saraiva et al.   APPLIED SOFT COMPUTING

A comparative study between dynamic and soft computing models for sediment forecasting

(2021) Sarita Gajbhiye Meshram et al.   SOFT COMPUTING

Application of artificial intelligence algorithms for hourly river level forecast: A case study of Muda River, Malaysia

(2021) Muhamad Nur Adli Zakaria et al.   Alexandria Engineering Journal

Development and evaluation of the cascade correlation neural network and the random forest models for river stage and river flow prediction in Australia

(2020) Mohammad Ali Ghorbani et al.   SOFT COMPUTING

A framework for ‘Inclusive Multiple Modelling’ with critical views on modelling practices – Applications to modelling water levels of Caspian Sea and Lakes Urmia and Van

(2020) R. Khatibi et al.   JOURNAL OF HYDROLOGY

New Approach for Sediment Yield Forecasting with a Two-Phase Feedforward Neuron Network-Particle Swarm Optimization Model Integrated with the Gravitational Search Algorithm

(2019) Sarita Gajbhiye Meshram et al.   WATER RESOURCES MANAGEMENT

Analysis of the use of discrete wavelet transforms coupled with ANN for short-term streamflow forecasting

(2019) Paula Karenina de Macedo Machado Freire et al.   APPLIED SOFT COMPUTING

River flow prediction using hybrid PSOGSA algorithm based on feed-forward neural network

(2018) Sarita Gajbhiye Meshram et al.   SOFT COMPUTING

Hybrid Wavelet Neural Network Approach for Daily Inflow Forecasting Using Tropical Rainfall Measuring Mission Data

(2018) Celso A. G. Santos et al.   JOURNAL OF HYDROLOGIC ENGINEERING

Daily streamflow forecasting using a wavelet transform and artificial neural network hybrid models

(2013) Celso Augusto Guimarães Santos et al.   HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES

Streamflow prediction using linear genetic programming in comparison with a neuro-wavelet technique

(2013) Ali Danandeh Mehr et al.   JOURNAL OF HYDROLOGY

Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques

(2012) A.K. Lohani et al.   JOURNAL OF HYDROLOGY

Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir

(2012) Mohammad Valipour et al.   JOURNAL OF HYDROLOGY

Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting

(2012) Robert J. Abrahart et al.   PROGRESS IN PHYSICAL GEOGRAPHY

Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules

(2012) A. R. Senthil kumar et al.   WATER RESOURCES MANAGEMENT

Hybrid Wavelet–Genetic Programming Approach to Optimize ANN Modeling of Rainfall–Runoff Process

(2011) Vahid Nourani et al.   JOURNAL OF HYDROLOGIC ENGINEERING

Daily streamflow forecasting by machine learning methods with weather and climate inputs

(2011) Kabir Rasouli et al.   JOURNAL OF HYDROLOGY

Coupled simulation-optimization model for coastal aquifer management using genetic programming-based ensemble surrogate models and multiple-realization optimization

(2011) J. Sreekanth et al.   WATER RESOURCES RESEARCH

Comment on ‘Sivapragasam C, Maheswaran R, Venkatesh V. 2008. Genetic programming approach for flood routing in natural channels. Hydrological Processes 22: 623-628’

(2010) A. H. Alavi et al.   HYDROLOGICAL PROCESSES

Comparison of data-driven modelling techniques for river flow forecasting

(2010) Shreenivas Londhe et al.   HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES

Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model

(2010) Jalal Shiri et al.   JOURNAL OF HYDROLOGY

Linear genetic programming for time-series modelling of daily flow rate

(2009) Aytac Guven   Journal of Earth System Science

A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

(2009) Wen-Chuan Wang et al.   JOURNAL OF HYDROLOGY