AIMC Topic: Sewage

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Optimisation and Calibration of Bayesian Neural Network for Probabilistic Prediction of Biogas Performance in an Anaerobic Lagoon.

Sensors (Basel, Switzerland)
This study aims to enhance diagnostic capabilities for optimising the performance of the anaerobic sewage treatment lagoon at Melbourne Water's Western Treatment Plant (WTP) through a novel machine learning (ML)-based monitoring strategy. This strate...

Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches.

Water science and technology : a journal of the International Association on Water Pollution Research
Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer ...

Waste to resource: Mining antimicrobial peptides in sludge from metagenomes using machine learning.

Environment international
The emergence of antibiotic-resistant bacteria poses a huge threat to the treatment of infections. Antimicrobial peptides are a class of short peptides that widely exist in organisms and are considered as potential substitutes for traditional antibio...

Optimization of operational parameters using RSM, ANN, and SVM in membrane integrated with rotating biological contactor.

Chemosphere
Membrane fouling is a critical bottleneck to the widespread adoption of membrane separation processes. It diminishes the membrane permeability and results in high operational energy costs. The current study presents optimizing the operating parameter...

Maintaining innovation: How to make sewer robots and innovation policy work in Barcelona.

Social studies of science
This article explores how innovation logics infiltrate problem and value definitions in maintenance and repair, and how innovation itself depends on considerable, often invisible care work beyond the seemingly smooth entrepreneurial narratives. We bu...

An Intelligent Robot Detection System of Uncontrolled Radioactive Sources.

Computational intelligence and neuroscience
In recent years, radioactive sources have been widely used in various fields (e.g., nuclear industry, agriculture, medical industry, environmental protection, and scientific research) and successfully applied to develop scientific projects, such as n...

Intelligent Measurement and Analysis of Sewage Treatment Parameters based on Fuzzy Neural Algorithm with ARM9 Core CPU.

Computational intelligence and neuroscience
After entering the new century, the state continues to increase the construction of urban sewage treatment projects in response to the deteriorating water pollution situation. How to collect and analyze the sewage parameter variables in the sewage tr...

Deep Learning Target Detection System for Sewage Treatment.

Computational intelligence and neuroscience
Object detection is to identify objects and then find some objects of interest. With the development of computers, target detection has evolved from traditional detection methods to artificial intelligence methods, and the latter are mainly based on ...

Deep learning model based on urban multi-source data for predicting heavy metals (Cu, Zn, Ni, Cr) in industrial sewer networks.

Journal of hazardous materials
The high concentrations of heavy metals in municipal industrial sewer networks will seriously impact the microorganisms of the activated sludge in the wastewater treatment plant (WWTP), thus deteriorating the effluent quality and destroying the stabi...

Online learning-empowered smart management for AO process in sewage treatment processes.

Environmental research
Using artificial intelligence method to describe general working process is a more meaningful and widely used idea in various practical projects. At the same time, it is also an important way to realize intelligent management. Water pollution is seri...