AIMC Topic: Industrial Waste
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Application of fuzzy neural networks for modeling of biodegradation and biogas production in a full-scale internal circulation anaerobic reactor.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Sep 9, 2016
This paper presents the development and evaluation of three fuzzy neural network (FNN) models for a full-scale anaerobic digestion system treating paper-mill wastewater. The aim was the investigation of feasibility of the approach-based control syste...
Application of the removal of pollutants from textile industry wastewater in constructed wetlands using fuzzy logic.
Environmental technology
Jun 24, 2016
There are more than a hundred textile industries in Turkey that discharge large quantities of dye-rich wastewater, resulting in water pollution. Such effluents must be treated to meet discharge limits imposed by the Water Framework Directive in Turke...
A fuzzy-logic-based controller for methane production in anaerobic fixed-film reactors.
Environmental technology
May 13, 2016
The main objective of this work was to develop a controller for biogas production in continuous anaerobic fixed-bed reactors, which used effluent total volatile fatty acids (VFA) concentration as control input in order to prevent process acidificatio...
Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.
Environmental science and pollution research international
Jul 11, 2015
Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and developmen...
Hidden threats beneath: uncovering the bio-accessible hazards of chromite-asbestos mine waste and their impacts on rice components via multi-machine learning algorithm.
Environmental geochemistry and health
May 17, 2025
The chromite-asbestos mining leaves behind tonnes of toxic waste, contaminating nearby agricultural fields with potentially toxic elements (PTEs). Over time, wind and water erosion spread these pollutants, severely impacting the ecosystem, food chain...
Prediction of total phosphorus removal in hybrid constructed wetlands: a machine learning approach for rice mill wastewater treatment.
Water environment research : a research publication of the Water Environment Federation
May 1, 2025
Efficient prediction of pollutant concentrations in constructed wetlands is critical for optimizing treatment performance, yet existing methodologies often fail to account for the influence of meteorological conditions and flow rate variations in rea...
Phytoremediation of palm oil mill secondary effluent (POMSE) by Chrysopogon zizanioides (L.) using artificial neural networks.
International journal of phytoremediation
May 4, 2017
Artificial neural networks (ANNs) have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the nonlinear relationships between variables in complex systems. In this study, ANN was applied...
Applications of response surface methodology and artificial neural network for decolorization of distillery spent wash by using activated Piper nigrum.
Journal of environmental biology
Nov 1, 2016
Ethanol production from sugarcane molasses yields large volume of highly colored spent wash as effluent. This color is imparted by the recalcitrant melanoidin pigment produced due to the Maillard reaction. In the present work, decolourization of mela...
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