Contribution to optimize decision parameters in activated-sludge process using ANFIS model (original) (raw)

Use of fuzzy neural-net model for rule generation of activated sludge process

Rajeshwar Tyagi

Process Biochemistry, 1999

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Modeling of an activated sludge process for effluent prediction-a comparative study using ANFIS and GLM regression

Jamiu Adetayo Adeniran

Environmental monitoring and assessment, 2018

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Modelling activated sludge wastewater treatment plants using artificial intelligence techniques (fuzzy logic and neural networks)

Rabee Rustum

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Performance analysis and control of wastewater treatment plant using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multi-Linear Regression (MLR) techniques

Abba Bashir

GSC Advanced Engineering and Technology, 2022

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Dynamic performance analysis and simulation of a full scale activated sludge system treating an industrial wastewater using artificial neural network

Ali Akbar Zinatizadeh

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A SIMPLIFIED MODEL STRUCTURE FOR AN ACTIVATED SLUDGE SYSTEM

Muhammad Gaya Sani

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Enhance modelling predicting for pollution removal in wastewater treatment plants by using an adaptive neuro-fuzzy inference system

Hussein Y.H. Alnajjar

Published by Yıldız Technical University Press, İstanbul, Türkiye, 2022

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THE USE OF A NEURAL NETWORK TECHNIQUE FOR THE PREDICTION OF SLUDGE VOLUME INDEX IN MUNICIPAL WASTEWATER TREATMENT PLANT

djeddou messaoud, Bachir ACHOUR

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Amelioration of carbon removal prediction for an activated sludge process using an artificial neural network (ANN)

Sukru Dursun

CLEAN–Soil, Air, Water, 2008

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Application of the selected classification models to the analysis of the settling capacity of the activated sludge – case study

Bartosz Szeląg

E3S Web of Conferences, 2017

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Enhance modelling predicting for removal efficacy of primary and biological treatment in wastewater treatment plants by using an adaptive neuro-fuzzy inference system

osman ucuncu, Hussein Y.H. Alnajjar

Environmental Research and Technology

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System identification and real-time pattern recognition by neural networks for an activated sludge process

Manel Poch

1995

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Effects of phase vector and history extension on prediction power of adaptive-network based fuzzy inference system (ANFIS) model for a real scale anaerobic wastewater treatment plant operating under unsteady state

Serdar S . Çelebi

Bioresource Technology, 2009

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KSOM and MLP neural networks for on-line estimating the efficiency of an activated sludge process

Tien Nguyen

Chemical Engineering Journal, 2006

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Improvement of Artificial Neural Network Model for the Prediction of Wastewater Treatment Plant Performance

Iman Husain, Professor Mohammed S A E D I Jami

Environmental Management and Engineering / 731,733: Unconventional Oil, 2011

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Fuzzy model and decision of COD control for an activated sludge process

Manel Poch

Fuzzy Sets and Systems, 1998

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Sludge Bulking Prediction Using Principle Component Regression and Artificial Neural Network

inchio lou

Mathematical Problems in Engineering, 2012

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Adaptive Network Based Fuzzy Interference System (ANFIS) Modeling of an Anaerobic Wastewater Treatment Process

P Mullai

Innovations and Solutions

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Prediction of effluent quality of an anaerobic treatment plant under unsteady state through ANFIS modeling with on-line input variables

Serdar S . Çelebi

Chemical Engineering …, 2008

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Qualitative evaluation of wastewater treatment plant performance by a neural network model optimized by genetic algorithm

Dragana Dogancic

Proceedings of 5th International Electronic Conference on Water Sciences, 2020

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A Fuzzy Neural Network Model for the Estimation of the Feeding Rate to an Anaerobic Waste Water Treatment Process

Nikola Kasabov, Professor

1998

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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning

Bartosz Szeląg

Sensors, 2020

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Optimal Parameter Estimation in Activated Sludge Process Based Wastewater Treatment Practice

Veeriah Jegatheesan

Water, 2020

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Prediction of primary treatment effluent parameters by Fuzzy Inference System (FIS) approach

Şükran YALPIR

Procedia Computer Science, 2011

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Modeling and optimization of activated sludge bulking for a real wastewater treatment plant using hybrid artificial neural networks-genetic algorithm approach

Ali Kamarkhani

Process Safety and Environmental Protection, 2015

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