Calculation of carbon emissions in wastewater treatment and its neutralization measures: A review

Z Liu, Z Xu, X Zhu, L Yin, Z Yin, X Li, W Zheng - Science of The Total …, 2023 - Elsevier
As the pursuit of “carbon neutrality” gains momentum, the emphasis on low-carbon
solutions, emphasizing energy conservation and resource reuse, has introduced fresh …

Artificial intelligence and machine learning-based monitoring and design of biological wastewater treatment systems

NK Singh, M Yadav, V Singh, H Padhiyar, V Kumar… - Bioresource …, 2023 - Elsevier
Artificial intelligence (AI) and machine learning (ML) are currently used in several areas. The
applications of AI and ML based models are also reported for monitoring and design of …

Data to intelligence: The role of data-driven models in wastewater treatment

M Bahramian, RK Dereli, W Zhao, M Giberti… - Expert Systems with …, 2023 - Elsevier
Increasing energy efficiency in wastewater treatment plants (WWTPs) is becoming more
important. An emerging approach to addressing this issue is to exploit development in data …

Predictive modelling and optimization of an airlift bioreactor for selenite removal from wastewater using artificial neural networks and particle swarm optimization

BB Negi, M Aliveli, SK Behera, R Das, A Sinharoy… - Environmental …, 2023 - Elsevier
Abstract Selenite (Se 4+) is the most toxic of all the oxyanion forms of selenium. In this study,
a feed forward back propagation (BP) based artificial neural network (ANN) model was …

A supervised functional Bayesian inference model with transfer-learning for performance enhancement of monitoring target batches with limited data

J Liu, GY Hou, W Shao, J Chen - Process Safety and Environmental …, 2023 - Elsevier
To increase the monitoring performance of the batch process with serious nonlinearity,
uneven-length, and limited-data issues, a supervised transfer-learning based functional …

A novel experimental and machine learning model to remove COD in a batch reactor equipped with microalgae

AE Jery, A Noreen, M Isam, JL Arias-Gonzáles… - Applied Water …, 2023 - Springer
By using microorganisms and the microalgae Chlorella vulgaris in conjunction with
sequencing batch reactors (SBRs), the performance of a wastewater treatment facility was …

A machine learning and data analytics approach for predicting evacuation and identifying contributing factors during hazardous materials incidents on railways

H Ebrahimi, F Sattari, L Lefsrud, R Macciotta - Safety science, 2023 - Elsevier
An emergency evacuation order might be issued in response to a railway incident involving
hazardous materials (hazmat), such as the February 2023 derailment at Palestine, Ohio …

The impact of artificial intelligence on waste management for climate change

H Alshater, YS Moemen, IET El-Sayed - The Power of Data: Driving …, 2023 - Springer
The paceof waste creationincreases in direct proportion to the number of people inhabiting a
certain area. Waste disposal methods like landfills and open dumping are problematic …

Artificial neural network modeling on trichloroethylene biodegradation in a packed-bed biofilm reactor and its comparison with response surface modeling approach

F Yu, G Bobashev, PR Bienkowski, GS Sayler - Biochemical Engineering …, 2023 - Elsevier
An artificial neural network (ANN) model was developed for predicting trichloroethylene
(TCE) biodegradation via co-metabolism in a packed-bed biofilm reactor using …

Assessment of Machine Learning Algorithms for Predicting Air Entrainment Rates in a Confined Plunging Liquid Jet Reactor

A Alazmi, BS Al-Anzi - Sustainability, 2023 - mdpi.com
A confined plunging liquid jet reactor (CPLJR) is an unconventional efficient and feasible
aerator, mixer and brine dispenser that operates under many operating conditions. Such …