Autors: Yordanova, S. T., Noikova N., Petrova R., Tzvetkov, P. M.
Title: Neuron-Fuzzy Modelling on Experimental Data in Anaerobic Digestion of Organic Waste in Waters
Keywords: Anaerobic digestion of organic waste, neuro-fuzzy modelling, sensitivity, simulatio

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.

References

    Issue

    Third IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2005, pp. 84-88, 2005, Bulgaria, IEEE, ISBN:0-7803-9446-1;978-078039446-9, DOI: 10.1109/IDAACS.2005.282946

    Full text of the publication

    Цитирания (Citation/s):
    1. Pezhman Kazemi, Jean-Philippe Steyer, Christophe Bengoa, Josep Font, Jaume Giralt Robust Data-Driven Soft Sensors for Online Monitoring of Volatile Fatty Acids in Anaerobic Digestion Processes - 2020 - в издания, индексирани в Scopus или Web of Science
    2. Pengfei Yan, Minghui Gai, Yuhong Wang and Xiaoyong Gao (2021), Review of Soft Sensors in Anaerobic Digestion Process, J. Processes, MDPI 9(1434), pp. 1-21, https://doi.org/10.3390/pr9081434,https://www.mdpi.com/journal/processes - 2021 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science