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Pregled bibliografske jedinice broj: 703522

Development of Fuzzy Neural Network Methodology for Improvement of Water Quality Analytical Processes


Novak, Mirjana; Ukić, Šime; Lončarić Božić, Ana; Rogošić, Marko; Bolanča, Tomislav
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


Citiraj ovu publikaciju:

Novak, Mirjana; Ukić, Šime; Lončarić Božić, Ana; Rogošić, Marko; Bolanča, Tomislav
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)
Novak, M., Ukić, Š., Lončarić Božić, A., Rogošić, M. & Bolanča, T. (2014) Development of Fuzzy Neural Network Methodology for Improvement of Water Quality Analytical Processes. U: Proceedings of the IWA 6th Eastern European Young Water Professionals Conference «EAST Meets WEST».
@article{article, author = {Novak, Mirjana and Uki\'{c}, \v{S}ime and Lon\v{c}ari\'{c} Bo\v{z}i\'{c}, Ana and Rogo\v{s}i\'{c}, Marko and Bolan\v{c}a, Tomislav}, year = {2014}, pages = {493-500}, keywords = {ion chromatography, pulsed amperometric detection, retention modelling, fuzzy neural network, quantitative structure-retention relationships}, title = {Development of Fuzzy Neural Network Methodology for Improvement of Water Quality Analytical Processes}, keyword = {ion chromatography, pulsed amperometric detection, retention modelling, fuzzy neural network, quantitative structure-retention relationships}, publisher = {IWA the international water association}, publisherplace = {Istanbul, Turska} }
@article{article, author = {Novak, Mirjana and Uki\'{c}, \v{S}ime and Lon\v{c}ari\'{c} Bo\v{z}i\'{c}, Ana and Rogo\v{s}i\'{c}, Marko and Bolan\v{c}a, Tomislav}, year = {2014}, pages = {493-500}, keywords = {ion chromatography, pulsed amperometric detection, retention modelling, fuzzy neural network, quantitative structure-retention relationships}, title = {Development of Fuzzy Neural Network Methodology for Improvement of Water Quality Analytical Processes}, keyword = {ion chromatography, pulsed amperometric detection, retention modelling, fuzzy neural network, quantitative structure-retention relationships}, publisher = {IWA the international water association}, publisherplace = {Istanbul, Turska} }




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