Pregled bibliografske jedinice broj: 703522
Development of Fuzzy Neural Network Methodology for Improvement of Water Quality Analytical Processes
Development of Fuzzy Neural Network Methodology for Improvement of Water Quality Analytical Processes // Proceedings of the IWA 6th Eastern European Young Water Professionals Conference «EAST Meets WEST»
Istanbul, Turska: IWA the international water association, 2014. str. 493-500 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 703522 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Development of Fuzzy Neural Network Methodology for Improvement of Water Quality Analytical Processes
Autori
Novak, Mirjana ; Ukić, Šime ; Lončarić Božić, Ana ; Rogošić, Marko ; Bolanča, Tomislav
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the IWA 6th Eastern European Young Water Professionals Conference «EAST Meets WEST»
/ - : IWA the international water association, 2014, 493-500
Skup
IWA 6th Eastern European Young Water Professionals Conference «EAST Meets WEST»
Mjesto i datum
Istanbul, Turska, 28.05.2014. - 30.05.2014
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
ion chromatography ; pulsed amperometric detection ; retention modelling ; fuzzy neural network ; quantitative structure-retention relationships
Sažetak
Water quality management processes and in particular water quality measurements might be considered routine but most certainly are economically and ecologically demanding and time consuming. Constant improvement paradigm yield multidimensional complex water quality process optimization that often results in insufficient improvements. Advanced fuzzy neural solutions can be implemented to overcome such results. The aim of this work is development of fuzzy neural network methodology for modelling and optimization of carbohydrate monitoring in water systems. The networks were optimized by means of training algorithm and, in addition, quantitative structure retention relationship models were developed, enabling prediction of retention parameters for other carbohydrate compounds in analytical system. The results were validated using external carbohydrate set. The obtained prediction ability showed a potential of the applied methodology for improving water quality analytical processes.
Izvorni jezik
Engleski
Znanstvena područja
Kemija, Kemijsko inženjerstvo
POVEZANOST RADA
Projekti:
110005
Ustanove:
Fakultet kemijskog inženjerstva i tehnologije, Zagreb
Profili:
Mirjana Novak Stankov
(autor)
Tomislav Bolanča
(autor)
Marko Rogošić
(autor)
Ana Lončarić Božić
(autor)
Šime Ukić
(autor)