The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT
Transactions ID Number: 88-101
Full Name: Daniel Dunea
Position: Doctor (Researcher)
Age: ON
Sex: Male
Address: University Valahia of Targoviste, Bdul Unirii No.18-24, Targoviste, 130082
Country: ROMANIA
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E-mail address: ddunea@yahoo.com
Other E-mails: m_oprea@yahoo.com
Title of the Paper: Fuzzy-APA: employing fuzzy and neural network techniques in data analysis of industrial wastewaters monitoring
Authors as they appear in the Paper: Daniel Dunea, Mihaela Oprea
Email addresses of all the authors: ddunea@yahoo.com, m_oprea@yahoo.com
Number of paper pages: 10
Abstract: A fuzzy logic based system for wastewater quality monitoring with the purpose of attenuating the environmental impact of the heavy metals loaded wastewaters is presented in this work. The design and implementation of a supervisory system in LabVIEW for data acquisition, system operation and distributed equipment control is briefly described. Fuzzy logic techniques were used to integrate nine water quality variables into a single quality index of the industrial effluent (EQI) by applying specific rules. The fuzzy rules for diagnosis were developed in MATLAB and were translated and integrated in a virtual instrument, which acted as a fuzzy rule based system, using quantitative and qualitative information, to support the decisional process in case of disturbances of the water quality status due to the effluent discharge impact. Generated EQI was used to train the artificial neural network using Quickprop algorithm, which has efficiently dealt with complex patterns, an!
d had a great ability to build up a neural system for prediction.
Keywords: Fuzzy logic, Fuzzy rules, Quickprop algorithm, Wastewater quality monitoring, Environmental indices
EXTENSION of the file: .pdf
Special (Invited) Session: A fuzzy logic based system for heavy metals loaded wastewaters monitoring
Organizer of the Session: 634-141
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