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Dissolved oxygen prediction using a new ensemble method

Environmental science and pollution research international, 2020-03, Vol.27 (9), p.9589-9603

2020

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Modelling reference evapotranspiration by combining neuro-fuzzy and evolutionary strategies

Acta geophysica, 2020-08, Vol.68 (4), p.1113-1126

2020

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Drought modelling by standard precipitation index (SPI) in a semi-arid climate using deep learning method: long short-term memory

Neural computing & applications, 2022-02, Vol.34 (3), p.2425-2442

2022

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Advanced machine learning model for better prediction accuracy of soil temperature at different depths

PloS one, 2020-04, Vol.15 (4), p.e0231055-e0231055

2020

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Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction

Environmental science and pollution research international, 2021, Vol.28 (2), p.1596-1611

2021

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Designing a reliable machine learning system for accurately estimating the ultimate condition of FRP-confined concrete

Scientific reports, 2024-09, Vol.14 (1), p.20466-26, Article 20466

2024

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Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model

The Artificial intelligence review, 2021-04, Vol.54 (4), p.2863-2890

2021

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Modelling reference evapotranspiration using a new wavelet conjunction heuristic method: Wavelet extreme learning machine vs wavelet neural networks

Agricultural and forest meteorology, 2018-12, Vol.263, p.41-48

2018

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Sugarcane growth prediction based on meteorological parameters using extreme learning machine and artificial neural network

Engineering applications of computational fluid mechanics, 2018-01, Vol.12 (1), p.738-749

2018

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Using SVM-RSM and ELM-RSM Approaches for Optimizing the Production Process of Methyl and Ethyl Esters

Energies (Basel), 2018-11, Vol.11 (11), p.2889

2018

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Assessment of the total organic carbon employing the different nature-inspired approaches in the Nakdong River, South Korea

Environmental monitoring and assessment, 2021-07, Vol.193 (7), p.445-445, Article 445

2021

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A novel method for lake level prediction: deep echo state network

Arabian journal of geosciences, 2020-09, Vol.13 (18), Article 956

2020

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Concrete corrosion in wastewater systems: Prediction and sensitivity analysis using advanced extreme learning machine

Frontiers of Structural and Civil Engineering, 2021-04, Vol.15 (2), p.444-460

2021

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Investigating Landfill Leachate and Groundwater Quality Prediction Using a Robust Integrated Artificial Intelligence Model: Grey Wolf Metaheuristic Optimization Algorithm and Extreme Learning Machine

Water (Basel), 2023-07, Vol.15 (13), p.2453

2023

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A machine learning approach for predicting the relationship between energy resources and economic development

Physica A, 2018-04, Vol.495, p.211-214

2018

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Prediction of daily chlorophyll-a concentration in rivers by water quality parameters using an efficient data-driven model: online sequential extreme learning machine

Acta geophysica, 2021-12, Vol.69 (6), p.2339-2361

2021

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Predicting arsenic and heavy metals contamination in groundwater resources of Ghahavand plain based on an artificial neural network optimized by imperialist competitive algorithm

Environmental health engineering and management, 2017-10, Vol.4 (4), p.225-231

2017

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Machine Learning and Water Economy: a New Approach to Predicting Dams Water Sales Revenue

Water resources management, 2020-04, Vol.34 (6), p.1893-1911

2020

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Kernel Extreme Learning Machine: An Efficient Model for Estimating Daily Dew Point Temperature Using Weather Data

Water (Basel), 2020-09, Vol.12 (9), p.2600

2020

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Estimating the incubated river water quality indicator based on machine learning and deep learning paradigms: BOD5 Prediction

Mathematical biosciences and engineering : MBE, 2022-09, Vol.19 (12), p.12744-12773

2022

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A comparative study of several machine learning based non-linear regression methods in estimating solar radiation: Case studies of the USA and Turkey regions

Energy (Oxford), 2020-04, Vol.197, p.117239, Article 117239

2020

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A Comparison of Performance of Artificial Neural Networks for Prediction of Heavy Metals Concentration in Groundwater Resources of Toyserkan Plain

Avicenna journal of environmental health engineering, 2017-06, Vol.4 (1), p.11792-11792

2017

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Modelling long-term groundwater fluctuations by extreme learning machine using hydro-climatic data

Hydrological sciences journal, 2018-01, Vol.63 (1), p.63-73

2018

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On the implementation of a novel data-intelligence model based on extreme learning machine optimized by bat algorithm for estimating daily chlorophyll-a concentration: Case studies of river and lake in USA

Journal of cleaner production, 2021-02, Vol.285, p.124868, Article 124868

2021

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Modeling groundwater fluctuations by three different evolutionary neural network techniques using hydroclimatic data

Natural hazards (Dordrecht), 2017-05, Vol.87 (1), p.367-381

2017

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Dissolved oxygen prediction using a new ensemble method

Modelling reference evapotranspiration by combining neuro-fuzzy and evolutionary strategies

Drought modelling by standard precipitation index (SPI) in a semi-arid climate using deep learning method: long short-term memory

Advanced machine learning model for better prediction accuracy of soil temperature at different depths

Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction

Designing a reliable machine learning system for accurately estimating the ultimate condition of FRP-confined concrete

Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model

Modelling reference evapotranspiration using a new wavelet conjunction heuristic method: Wavelet extreme learning machine vs wavelet neural networks

Sugarcane growth prediction based on meteorological parameters using extreme learning machine and artificial neural network

Using SVM-RSM and ELM-RSM Approaches for Optimizing the Production Process of Methyl and Ethyl Esters

Assessment of the total organic carbon employing the different nature-inspired approaches in the Nakdong River, South Korea

A novel method for lake level prediction: deep echo state network

Concrete corrosion in wastewater systems: Prediction and sensitivity analysis using advanced extreme learning machine

Investigating Landfill Leachate and Groundwater Quality Prediction Using a Robust Integrated Artificial Intelligence Model: Grey Wolf Metaheuristic Optimization Algorithm and Extreme Learning Machine

A machine learning approach for predicting the relationship between energy resources and economic development

Prediction of daily chlorophyll-a concentration in rivers by water quality parameters using an efficient data-driven model: online sequential extreme learning machine

Predicting arsenic and heavy metals contamination in groundwater resources of Ghahavand plain based on an artificial neural network optimized by imperialist competitive algorithm

Machine Learning and Water Economy: a New Approach to Predicting Dams Water Sales Revenue

Kernel Extreme Learning Machine: An Efficient Model for Estimating Daily Dew Point Temperature Using Weather Data

Estimating the incubated river water quality indicator based on machine learning and deep learning paradigms: BOD5 Prediction

A comparative study of several machine learning based non-linear regression methods in estimating solar radiation: Case studies of the USA and Turkey regions

A Comparison of Performance of Artificial Neural Networks for Prediction of Heavy Metals Concentration in Groundwater Resources of Toyserkan Plain

Modelling long-term groundwater fluctuations by extreme learning machine using hydro-climatic data

On the implementation of a novel data-intelligence model based on extreme learning machine optimized by bat algorithm for estimating daily chlorophyll-a concentration: Case studies of river and lake in USA

Modeling groundwater fluctuations by three different evolutionary neural network techniques using hydroclimatic data

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