Experiments and ANFIS modelling for the biodegradation of penicillin-G wastewater using anaerobic hybrid reactor

Mullai, P.; Subramanian, Arulselvi; Ngo, Huu Hao; Sabarathinam, P. L.

doi:10.1016/j.biortech.2011.01.085

Cited by 49 publications

(14 citation statements)

References 30 publications

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“…NF models have been used for various prediction tasks including modelling of thermal power plant (Liu et al, ) and modelling for the biodegradation of penicillin‐G waste water using anaerobic hybrid reactor (Mullai et al, ). Based on the data obtained from the field‐scale investigation, methane content in biogas recovered from the landfill is predicted using EF‐NF and other similar models.…”

Section: Resultsmentioning

confidence: 99%

Comparative analysis on the application of neuro‐fuzzy models for complex engineered systems: Case study from a landfill and a boiler

Meher

Behera²,

Rene

et al. 2017

Expert Systems

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This work aims at developing an explicit neuro‐fuzzy (NF) model to characterize complex engineered systems associated with high nonlinearity, uncertainties, and multivariable couplings. The NF model synergistically exploits the advantages of fuzzy belongingness of each input variable to all output variables and learning ability of neural networks. Owing to the inherent complexities associated with 2 complex engineered systems, a landfill and a boiler were selected to develop models that provide intelligent decisions for optimizing the operational parameters. Data compiled from field‐scale investigation/real plant operation involving various operating scenarios were used to develop the models. Predicting capability of the developed models was evaluated through the correlation coefficient and mean absolute percentage error values. Superiority of the proposed NF model to other similar models has been justified and demonstrated.

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Section: Resultsmentioning

confidence: 99%

Comparative analysis on the application of neuro‐fuzzy models for complex engineered systems: Case study from a landfill and a boiler

Meher

Behera²,

Rene

et al. 2017

Expert Systems

View full text Add to dashboard Cite

show abstract

“…In the search for generic, simple, and applicable models, artificial intelligence (AI) tools have been demonstrated to be very useful and capable of reproducing human characteristics such as flexibility, uncertainty tolerance, ability to consider imprecision or data voids, and facilitation of result interpretation (Jang and Sun, 1995). Currently, there is a wide variety of studies in the environmental field that have employed the characteristics of this tool (Afshar-Kazemi et al, 2011;Erdirencelebi and Yalpir, 2011;Mullai et al, 2011;Waewsak Nopharatana, and Chaiprasert, 2010;Noori et al 2009). When attempting to estimate the methane generation rate, several reports have been made that employ fuzzy logic (Abdallah et al, 2009;Garg, Achari, and Joshi, 2006), neural networks (Ogwueleka and Ogwueleka, 2010;Jalili and Noori, 2008;Ozkaya, Demir, and Bilgili, 2007), and genetic algorithms (Kurtulus Ozcan et al, 2008); however, only a much smaller number of studies use combinations of these techniques (Abdallah et al, 2011;Abu Qdais, BaninHani, and Shatnawi, 2009;Cakmakci, 2007;Nath and Das, 2011).…”

Section: Introductionmentioning

confidence: 97%

Estimation of Solid Waste Biomethanization: Development of Novel Methodology and Anfis Models

Mañón-Salas¹,

Moreno-Goytia

Hernández-Berriel

et al. 2012

Applied Artificial Intelligence

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& This article presents the application of a technique of artificial intelligence (AI) that explores the possibility of using a model to estimate the biomethanization of municipal solid waste (MSW). The model uses data from an experiment in which MSW is anaerobically digested under three different moisture regimes by leachate recycling. A method utilizing a neurofuzzy inference system is used because AI systems have a high capacity for empiric learning.Considering the importance of finding an effective selection of the most valuable variables for the model, this methodology includes the following techniques: Exhaustive Search (or brute-force search); Stepwise, a step-by-step regression method; and the use of Expert Knowledge. With the use of the fuzzy logic toolbox (MATLAB 1 ), nine models were generated. However, when a case study is used to detail the method, the proposed methodology can also be used with any other system with a set of input and output data.

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“…The wastewater generated from pharmaceutical industries, mainly antibiotic and synthetic drug based industries contain significant level of aliphatic organic solvents which contribute alarmingly for the BOD/COD content of the wastewater [1,2]. The most common method of treating pharmaceutical wastewater involves biomethanation in anaerobic digesters [3].…”

Section: Introductionmentioning

confidence: 99%

Post treatment of antibiotic wastewater by adsorption on activated carbon

Mullai¹,

Rajesh²

2018

AIP Conference Proceedings

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Abstract.The most common method of treating industrial wastewater involves biomethanation in anaerobic digesters. This biological treatment process is ineffective in color removal and it requires post-treatment methods. The color is the first contaminant in wastewater which affects the water bodies in several ways. As the anaerobically digested antibiotic wastewater was found with color, an attempt was made to remove color using granulated activated carbon as an adsorbent. Experiments were carried out in batch reactors to find out the color removal efficiency of the wastewater at four different dosages such as 25, 50, 75 and 100 mg of adsorbent material at each of the four different initial concentrations of effluent like 1956, 1450, 1251 and 1040 mg COD/L. The steady state values of color removal efficiencies were 96.6, 97.64, 98.64 and 99.63%, respectively, using 100 mg of activated carbon under shaking condition at the end of the 120 th min. The effect of contact time on the percentage of color removal was also studied. It was observed that the adsorption of effluent obtained equilibrium at 120 minutes. The equilibrium data fitted well with the Langmuir and Freundlich isotherms.

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Experiments and ANFIS modelling for the biodegradation of penicillin-G wastewater using anaerobic hybrid reactor

Cited by 49 publications

References 30 publications

Comparative analysis on the application of neuro‐fuzzy models for complex engineered systems: Case study from a landfill and a boiler

Comparative analysis on the application of neuro‐fuzzy models for complex engineered systems: Case study from a landfill and a boiler

Estimation of Solid Waste Biomethanization: Development of Novel Methodology and Anfis Models

Post treatment of antibiotic wastewater by adsorption on activated carbon

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