AIMC Topic: Sewage

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Electrochemical activation of alum sludge for the adsorption of lead (Pb(II)) and arsenic (As): Mechanistic insights and machine learning (ML) analysis.

Bioresource technology
Alum sludge (AlS) has emerged as an effective adsorbent for anionic contaminants, with traditional activation methods like acid/base treatments and calcination employed to enhance its adsorption capacity. However, these approaches encounter significa...

An analytic hierarchy process combined with artificial neural network model to evaluate sustainable sludge treatment scenarios.

Waste management (New York, N.Y.)
Sludge management in China faces critical environmental, economic, and technical challenges, necessitating urgent optimal management strategy selection. Given the limited number of comprehensive studies on sludge management, quantitative decision-mak...

Recognizing the state of aerobic granular sludge over its life-cycle in a continuous-flow membrane bioreactor with an artificial intelligence approach.

Journal of environmental management
The continuous-flow aerobic granular sludge-membrane bioreactor (AGS-MBR) system represents an efficient and sustainable technology for wastewater treatment. AGS, a spherical or ellipsoidal granular sludge formed through microbial self-aggregation un...

Machine learning-assisted prediction and identification of key factors affecting nitrogen metabolism for aerobic granular sludge.

Environmental research
To achieve higher denitrification efficiency with reduced energy consumption in aerobic granular sludge (AGS) system, a systematic evaluation of the carbon and nitrogen metabolism process for AGS under different stage is essential. Herein, this study...

Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia).

Water science and technology : a journal of the International Association on Water Pollution Research
Fuzzy methods using linguistic expressions and fuzzy numbers can provide a more accurate examination of manufacturing systems where data is not clear. Researchers expanded fuzzy control charts (CCs) using fuzzy linguistic statements and investigated ...

Energy saving for air supply in a real WWTP: application of a fuzzy logic controller.

Water science and technology : a journal of the International Association on Water Pollution Research
An unconventional cascade control system, for the regulation of air supply in activated sludge wastewater treatment plants (WWTPs), was tested. The dissolved oxygen (DO) set point in the aeration tank was dynamically calculated based on effluent ammo...

Prediction of effluent quality in ICEAS-sequential batch reactor using feedforward artificial neural network.

Water science and technology : a journal of the International Association on Water Pollution Research
It is highly essential that municipal wastewater is treated before its discharge and reuse in order to meet the standard requirements for safe marine life and for farming and industries. It is beneficial to use reclaimed water, since availability of ...

Research on a soft measurement model of sewage treatment based on a case-based reasoning approach.

Water science and technology : a journal of the International Association on Water Pollution Research
In this paper, the measurement of biochemical oxygen demand (BOD) in a wastewater treatment process is analyzed and an intelligent integrated prediction method based on case-based reasoning (CBR) is proposed in order to overcome difficulties. Due to ...

Artificial intelligence based model for optimization of COD removal efficiency of an up-flow anaerobic sludge blanket reactor in the saline wastewater treatment.

Water science and technology : a journal of the International Association on Water Pollution Research
The complex non-linear behavior presented in the biological treatment of wastewater requires an accurate model to predict the system performance. This study evaluates the effectiveness of an artificial intelligence (AI) model, based on the combinatio...

An expert system with radial basis function neural network based on decision trees for predicting sediment transport in sewers.

Water science and technology : a journal of the International Association on Water Pollution Research
In this study, an expert system with a radial basis function neural network (RBF-NN) based on decision trees (DT) is designed to predict sediment transport in sewer pipes at the limit of deposition. First, sensitivity analysis is carried out to inves...