Ensemble machine learning paradigms in hydrology: A review
Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
A review on machine learning, artificial intelligence, and smart technology in water treatment and monitoring
Artificial-intelligence methods and machine-learning models have demonstrated their ability
to optimize, model, and automate critical water-and wastewater-treatment applications …
to optimize, model, and automate critical water-and wastewater-treatment applications …
A multi-model data fusion methodology for reservoir water quality based on machine learning algorithms and bayesian maximum entropy
A major concern in the management of reservoirs is water quality because of the negative
consequences it has on both environment and human life. Artificial Intelligence (AI) concept …
consequences it has on both environment and human life. Artificial Intelligence (AI) concept …
Implementation of hybrid neuro-fuzzy and self-turning predictive model for the prediction of concrete carbonation depth: A soft computing technique
Carbonation is one of the critical problems that affects the durability of reinforced concrete; it
is a reaction between CO 2 gas and Ca (OH) 2 when H 2 O is available, which forms …
is a reaction between CO 2 gas and Ca (OH) 2 when H 2 O is available, which forms …
Cloud-based multiclass anomaly detection and categorization using ensemble learning
The world of the Internet and networking is exposed to many cyber-attacks and threats. Over
the years, machine learning models have progressed to be integrated into many scenarios …
the years, machine learning models have progressed to be integrated into many scenarios …
New generation neurocomputing learning coupled with a hybrid neuro-fuzzy model for quantifying water quality index variable: A case study from Saudi Arabia
Ensuring availability in terms of quality and quantity and sustainable management of safe,
affordable drinking water is one of the integral parts of envisioning the 2030 Sustainable …
affordable drinking water is one of the integral parts of envisioning the 2030 Sustainable …
Groundwater level forecasting in Northern Bangladesh using nonlinear autoregressive exogenous (NARX) and extreme learning machine (ELM) neural networks
DN Fabio, SI Abba, BQ Pham… - Arabian Journal of …, 2022 - Springer
Groundwater resources (GWR) are vital to agricultural crop production, everyday life, and
economic development. As a result, accurate groundwater level (GWL) prediction would aid …
economic development. As a result, accurate groundwater level (GWL) prediction would aid …
A machine learning approach for the estimation of total dissolved solids concentration in lake mead using electrical conductivity and temperature
Total dissolved solids (TDS) concentration determination in water bodies is sophisticated,
time-consuming, and involves expensive field sampling and laboratory processes. TDS …
time-consuming, and involves expensive field sampling and laboratory processes. TDS …
Interpretation the influence of hydrometeorological variables on soil temperature prediction using the potential of deep learning model
S Elsayed, M Gupta… - Knowledge …, 2023 - … journals.publicknowledgeproject.org
The importance of soil temperature (ST) quantification can contribute to diverse ecological
modelling processes as well as for agricultural activities. Over the literature, it was evident …
modelling processes as well as for agricultural activities. Over the literature, it was evident …
[HTML][HTML] Multi-regional modeling of cumulative COVID-19 cases integrated with environmental forest knowledge estimation: A deep learning ensemble approach
Reliable modeling of novel commutative cases of COVID-19 (CCC) is essential for
determining hospitalization needs and providing the benchmark for health-related policies …
determining hospitalization needs and providing the benchmark for health-related policies …