A review of computational modeling in wastewater treatment processes
Wastewater treatment companies are facing several challenges related to the optimization of
energy efficiency, meeting more restricted water quality standards, and resource recovery …
energy efficiency, meeting more restricted water quality standards, and resource recovery …
Predicting the carbon dioxide emission caused by road transport using a Random Forest (RF) model combined by Meta-Heuristic Algorithms
Carbon dioxide is one of the most important pollutants in urban areas. Since the relationship
between the factors of road transport and CO 2 emission is often complex, using methods …
between the factors of road transport and CO 2 emission is often complex, using methods …
Water and wastewater quality prediction: current trends and challenges in the implementation of artificial neural network
Traditional freshwater supplies have been over-abstracted in the current global problem of
water scarcity. Through the analysis of complex experimental and real-time data, to improve …
water scarcity. Through the analysis of complex experimental and real-time data, to improve …
Wastewater treatment with technical intervention inclination towards smart cities
At this time, efforts are being made on a worldwide scale to accomplish sustainable
development objectives. It has, thus, now become essential to investigate the part of …
development objectives. It has, thus, now become essential to investigate the part of …
Ultrasound-enhanced catalytic degradation of simulated dye wastewater using waste printed circuit boards: catalytic performance and artificial neuron network-based …
Recent developments of heterogeneous advanced oxidation for refractory organic
contaminants and catalysts made of solid waste have attracted much attention. In this work …
contaminants and catalysts made of solid waste have attracted much attention. In this work …
A deep learning feed-forward neural network framework for the solutions to singularly perturbed delay differential equations
SM Mallikarjunaiah - Applied Soft Computing, 2023 - Elsevier
In this paper, we explore a deep learning feedforward artificial neural network (ANN)
framework as a numerical tool for approximating the solutions to singularly perturbed delay …
framework as a numerical tool for approximating the solutions to singularly perturbed delay …
[HTML][HTML] The optimization of biodiesel production from waste cooking oil catalyzed by ostrich-eggshell derived CaO through various machine learning approaches
The continuous increase in demand for fossil-based fuel has led to the requirement for an
alternative source that must be renewable. Biodiesel is gaining global acceptance as a …
alternative source that must be renewable. Biodiesel is gaining global acceptance as a …
Artificial neural network based models for predicting the effluent quality of a combined upflow anaerobic sludge blanket and facultative pond: Performance evaluation …
The main objective of this work was to test different artificial neural network (ANN) based
models, ie the ANN feed forward back propagation (ANN-FFBP), deep feed forward …
models, ie the ANN feed forward back propagation (ANN-FFBP), deep feed forward …
Development of local and global wastewater biochemical oxygen demand real-time prediction models using supervised machine learning algorithms
AS Qambar, MMM Al Khalidy - Engineering Applications of Artificial …, 2023 - Elsevier
This study aims to shed light on a new understanding of global machine-learning (ML)
prediction models for wastewater treatment plants (WWTPs). The paper evaluates the …
prediction models for wastewater treatment plants (WWTPs). The paper evaluates the …
[HTML][HTML] Microalgal cultures for the remediation of wastewaters with different nitrogen to phosphorus ratios: Process modelling using artificial neural networks
EM Salgado, AF Esteves, AL Gonçalves… - Environmental …, 2023 - Elsevier
Microalgae have remarkable potential for wastewater bioremediation since they can
efficiently uptake nitrogen and phosphorus in a sustainable and environmentally friendly …
efficiently uptake nitrogen and phosphorus in a sustainable and environmentally friendly …