[HTML][HTML] A brief review of random forests for water scientists and practitioners and their recent history in water resources

H Tyralis, G Papacharalampous, A Langousis - Water, 2019 - mdpi.com
Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …

[HTML][HTML] Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China

J Fan, L Wu, F Zhang, H Cai, W Zeng, X Wang… - … and Sustainable Energy …, 2019 - Elsevier
Accurate estimation of global solar radiation (R s) is essential to the design and assessment
of solar energy utilization systems. Existing empirical and machine learning models for …

Modeling daily reference evapotranspiration via a novel approach based on support vector regression coupled with whale optimization algorithm

B Mohammadi, S Mehdizadeh - Agricultural Water Management, 2020 - Elsevier
In achieving water resource management goals such as irrigation scheduling, an accurate
estimate of reference evapotranspiration (ET 0) is critical. Support vector regression (SVR) …

Comparison of Support Vector Machine and Extreme Gradient Boosting for predicting daily global solar radiation using temperature and precipitation in humid …

J Fan, X Wang, L Wu, H Zhou, F Zhang, X Yu… - Energy conversion and …, 2018 - Elsevier
The knowledge of global solar radiation (H) is a prerequisite for the use of renewable solar
energy, but H measurements are always not available due to high costs and technical …

Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates …

J Fan, W Yue, L Wu, F Zhang, H Cai, X Wang… - Agricultural and forest …, 2018 - Elsevier
Accurate estimation of reference evapotranspiration (ET 0) is of great importance for the
regional water resources planning and irrigation scheduling design. The FAO-56 Penman …

[HTML][HTML] Exploiting IoT and its enabled technologies for irrigation needs in agriculture

V Ramachandran, R Ramalakshmi, BP Kavin… - Water, 2022 - mdpi.com
The increase in population growth and demand is rapidly depleting natural resources.
Irrigation plays a vital role in the productivity and growth of agriculture, consuming no less …

Light Gradient Boosting Machine: An efficient soft computing model for estimating daily reference evapotranspiration with local and external meteorological data

J Fan, X Ma, L Wu, F Zhang, X Yu, W Zeng - Agricultural water management, 2019 - Elsevier
Accurate estimation of reference evapotranspiration (ETo) is required in many fields, eg
irrigation scheduling design, agricultural water management, crop growth modeling and …

Evaluation of stacking and blending ensemble learning methods for estimating daily reference evapotranspiration

T Wu, W Zhang, X Jiao, W Guo, YA Hamoud - Computers and Electronics in …, 2021 - Elsevier
Precise reference evapotranspiration (ETo) estimation and prediction are the first steps to
realize efficient agricultural water resources management. As machine learning methods are …

Machine learning regression-CFD models for the nanofluid heat transfer of a microchannel heat sink with double synthetic jets

J Mohammadpour, S Husain, F Salehi, A Lee - … Communications in Heat …, 2022 - Elsevier
A comprehensive analysis consisting of computational fluid dynamics (CFD) and machine
learning algorithms (MLAs) is conducted to study the effect of geometrical and operational …

Reference evapotranspiration estimation and modeling of the Punjab Northern India using deep learning

MK Saggi, S Jain - Computers and Electronics in Agriculture, 2019 - Elsevier
Over the last decade, the combination of both big data and machine learning research
area's receiving considerable attention and expedite the prospect of the agricultural industry …