[HTML][HTML] Artificial intelligence and machine learning for the optimization of pharmaceutical wastewater treatment systems: a review
V Ganthavee, AP Trzcinski - Environmental Chemistry Letters, 2024 - Springer
The access to clean and drinkable water is becoming one of the major health issues
because most natural waters are now polluted in the context of rapid industrialization and …
because most natural waters are now polluted in the context of rapid industrialization and …
A Deep Learning-Based Data Management Scheme for Intelligent Control of Wastewater Treatment Processes Under Resource-Constrained IoT Systems
Y Shen, X Zhu, Z Guo, K Yu, O Alfarraj… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Effective data management schemes have always been the major demand in universal
industrial Internet of Things (IoT) systems, especially in resource-constrained scenarios. In …
industrial Internet of Things (IoT) systems, especially in resource-constrained scenarios. In …
[HTML][HTML] Simulating imprecise data: sine–cosine and convolution methods with neutrosophic normal distribution
M Aslam - Journal of Big Data, 2023 - Springer
Objective The primary aim of this research paper is to introduce and demonstrate the
application of the sine–cosine method and the convolution method for simulating data by …
application of the sine–cosine method and the convolution method for simulating data by …
A new approach to optimizing aeration using XGB-Bi-LSTM via the online monitoring of oxygen transfer efficiency and oxygen uptake rate
Z Ao, H Li, J Chen, J Yuan, Z Xia, J Zhang… - Environmental …, 2023 - Elsevier
In wastewater treatment plants (WWTPs), aeration is vital for microbial oxygen needs. To
achieve carbon neutrality, optimizing aeration for energy and emissions reduction is …
achieve carbon neutrality, optimizing aeration for energy and emissions reduction is …