An insight into machine learning models era in simulating soil, water bodies and adsorption heavy metals: Review, challenges and solutions

ZM Yaseen - Chemosphere, 2021 - Elsevier
The development of computer aid models for heavy metals (HMs) simulation has been
remarkably advanced over the past two decades. Several machine learning (ML) models …

A review of global precipitation data sets: Data sources, estimation, and intercomparisons

Q Sun, C Miao, Q Duan, H Ashouri… - Reviews of …, 2018 - Wiley Online Library
In this paper, we present a comprehensive review of the data sources and estimation
methods of 30 currently available global precipitation data sets, including gauge‐based …

The community earth system model version 2 (CESM2)

G Danabasoglu, JF Lamarque… - Journal of Advances …, 2020 - Wiley Online Library
An overview of the Community Earth System Model Version 2 (CESM2) is provided,
including a discussion of the challenges encountered during its development and how they …

Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks

S Ghimire, ZM Yaseen, AA Farooque, RC Deo… - Scientific Reports, 2021 - nature.com
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …

Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets

G Tang, MP Clark, SM Papalexiou, Z Ma… - Remote sensing of …, 2020 - Elsevier
Abstract The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement
(IMERG) produces the latest generation of satellite precipitation estimates and has been …

CMIP6 evaluation and projection of temperature and precipitation over China

X Yang, B Zhou, Y Xu, Z Han - Advances in Atmospheric Sciences, 2021 - Springer
This article evaluates the performance of 20 Coupled Model Intercomparison Project phase
6 (CMIP6) models in simulating temperature and precipitation over China through …

River water quality index prediction and uncertainty analysis: A comparative study of machine learning models

SBHS Asadollah, A Sharafati, D Motta… - Journal of environmental …, 2021 - Elsevier
Abstract The Water Quality Index (WQI) is the most common indicator to characterize surface
water quality. This study introduces a new ensemble machine learning model called Extra …

[HTML][HTML] Contribution of the world's main dust source regions to the global cycle of desert dust

JF Kok, AA Adebiyi, S Albani… - Atmospheric …, 2021 - acp.copernicus.org
Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, the
relative contributions of the world's major source regions to the global dust cycle remain …

The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studies

F Cabitza, A Campagner - International Journal of Medical Informatics, 2021 - Elsevier
This editorial aims to contribute to the current debate about the quality of studies that apply
machine learning (ML) methodologies to medical data to extract value from them and …

Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer

EM Golafshani, A Behnood, M Arashpour - Construction and Building …, 2020 - Elsevier
Achieving a reliable model for predicting the compressive strength (CS) of concrete can
save in time, energy, and cost and also provide information about scheduling for …