Neuro-Fuzzy Modelling on Experimental Data in Anaerobic Digestion of Organic Waste in Waters

Author

Yordanova, Snejana ; Noikova, Nelly ; Petrova, Rusanka ; Tzvetkov, Plamen

Author_Institution

Fac. of Autom., Tech. Univ. of Sofia, Sofia

fYear

2005

fDate

5-7 Sept. 2005

Firstpage

84

Lastpage

88

Abstract

The aim of the present paper is to develop neuro- fuzzy models of the anaerobic organic digestion process in wastewater treatment from laboratory and simulated experiments accounting for the variable organic load, ambient influence and microorganisms state in MATLAB environment. The main contributions are determination of significant model parameters via graphical sensitivity analysis, simulation experimentation and design and study in MATLAB of two "black-box" models for the biogas production rate, based respectively on classical feedforward backpropagation and Sugeno fuzzy logic neural networks. The models can find application in process prediction, optimization and control.

Keywords

backpropagation; biofuel; digital simulation; feedforward neural nets; fuzzy neural nets; microorganisms; sensitivity analysis; wastewater treatment; MATLAB environment; Sugeno fuzzy logic neural network; anaerobic organic digestion process; biogas production rate; black-box model; feedforward backpropagation; graphical sensitivity analysis; microorganism; simulation experimentation; wastewater treatment; Analytical models; Backpropagation; Fuzzy logic; MATLAB; Mathematical model; Microorganisms; Neural networks; Production; Sensitivity analysis; Wastewater treatment; Anaerobic digestion of organic waste; neuro-fuzzy modelling; sensitivity; simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2005. IDAACS 2005. IEEE

Conference_Location

Sofia

Print_ISBN

0-7803-9445-3

Electronic_ISBN

0-7803-9446-1

Type

conf

DOI

10.1109/IDAACS.2005.282946

Filename

4062097