Evaluating deep learning and machine learning algorithms for forecasting daily pan evaporation during COVID-19 pandemic
- 19 June 2023
- journal article
- research article
- Published by Springer Nature in Environment, Development and Sustainability
- Vol. 26 (5) , 11729-11742
Abstract
No abstract availableKeywords
This publication has 20 references indexed in Scilit:
- Accuracy enhancement for monthly evaporation predicting model utilizing evolutionary machine learning methodsInternational Journal of Environmental Science and Technology, 2020
- Modeling Pan Evaporation Using Gaussian Process Regression K-Nearest Neighbors Random Forest and Support Vector Machines; Comparative AnalysisAtmosphere, 2020
- Prediction of evaporation in arid and semi-arid regions: a comparative study using different machine learning modelsEngineering Applications of Computational Fluid Mechanics, 2019
- Reservoir Evaporation Prediction Modeling Based on Artificial Intelligence MethodsWater, 2019
- Improved prediction of daily pan evaporation using Deep-LSTM modelNeural Computing and Applications, 2019
- Evaluation of a neuro‐fuzzy technique in estimating pan evaporation values in low‐altitude locationsMeteorological Applications, 2018
- Forecasting pan evaporation with an integrated artificial neural network quantum-behaved particle swarm optimization model: a case study in Talesh, Northern IranEngineering Applications of Computational Fluid Mechanics, 2018
- Daily pan evaporation modeling using chi-squared automatic interaction detector, neural networks, classification and regression treeComputers and Electronics in Agriculture, 2016
- Does privatisation drive innovation? Business model innovation through stakeholder viewpoints: the case of Sydney Airport 10 years post-privatisationJournal of Management & Organization, 2014
- Long Short-Term MemoryNeural Computation, 1997