A review of the Artificial Intelligence (AI) based techniques for estimating reference evapotranspiration: Current trends and future perspectives

P Goyal, S Kumar, R Sharda - Computers and Electronics in Agriculture, 2023 - Elsevier
Reference Evapotranspiration (ET o) is a complex, dynamic and non-linear hydrological
process. Accurate estimation of ET o has long been an eminent topic of interest in the …

Role of existing and emerging technologies in advancing climate-smart agriculture through modeling: A review

D Gupta, N Gujre, S Singha, S Mitra - Ecological Informatics, 2022 - Elsevier
Under changing climate and burgeoning food production demands, climate-smart
agriculture (CSA) practices are the need of the hour. Physically-based crop models have …

A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem

AN Ahmed, T Van Lam, ND Hung, N Van Thieu… - Applied Soft …, 2021 - Elsevier
Hydrological models play a crucial role in water planning and decision making. Machine
Learning-based models showed several drawbacks for frequent high and a wide range of …

An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment

S Shukla, MF Hassan, MK Khan, LT Jung, A Awang - PloS one, 2019 - journals.plos.org
Fog computing (FC) is an evolving computing technology that operates in a distributed
environment. FC aims to bring cloud computing features close to edge devices. The …

A novel approach of diabetic retinopathy early detection based on multifractal geometry analysis for OCTA macular images using support vector machine

MM Abdelsalam, MA Zahran - IEEE access, 2021 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) is a complication of diabetes that affects the eyes. It is caused by
blood vessel damage of the light-sensitive tissue at the back of the retina …

Enhancement of groundwater-level prediction using an integrated machine learning model optimized by whale algorithm

FB Banadkooki, M Ehteram, AN Ahmed, FY Teo… - Natural resources …, 2020 - Springer
The present study attempted to predict groundwater levels (GWL) obtained from precipitation
and temperature data based on various temporal delays. The radial basis function (RBF) …

A novel kernel extreme learning machine model coupled with K-means clustering and firefly algorithm for estimating monthly reference evapotranspiration in parallel …

L Wu, Y Peng, J Fan, Y Wang, G Huang - Agricultural Water Management, 2021 - Elsevier
Accurate and fast estimation of reference evapotranspiration (ET 0) is important in
determining crop water requirements, designing irrigation schedule, planning and managing …

Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment

SD Latif - Environmental Science and Pollution Research, 2021 - Springer
One of the most critical parameters in concrete design is compressive strength. As the
compressive strength of concrete is correctly measured, time and cost can be decreased …

Meteorological drought analysis in response to climate change conditions, based on combined four-dimensional vine copulas and data mining (VC-DM)

A Farrokhi, S Farzin, SF Mousavi - Journal of Hydrology, 2021 - Elsevier
This research provides a novel methodology for modeling multivariate dependence
structures of meteorological drought characteristics (severity, duration, peak, and interarrival …

Ensuring a generalizable machine learning model for forecasting reservoir inflow in Kurdistan region of Iraq and Australia

SD Latif, AN Ahmed - Environment, Development and Sustainability, 2024 - Springer
Correct inflow prediction is a critical non-engineering measure for ensuring flood control and
increasing water supply efficiency. In addition, accurate inflow prediction can offer reservoir …