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master's thesis
Praćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža
Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology, 2021. urn:nbn:hr:149:553155
Žlabravec, Veronika
University of Zagreb
Faculty of Chemical Engineering and Technology

Institutional repository: Repository of Faculty of Chemical Engineering and Technology University of Zagreb

Cite this document

Žlabravec, V. (2021). Praćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža (Master's thesis). Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology. Retrieved from https://urn.nsk.hr/urn:nbn:hr:149:553155

Žlabravec, Veronika. "Praćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2021. https://urn.nsk.hr/urn:nbn:hr:149:553155

Žlabravec, Veronika. "Praćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2021. https://urn.nsk.hr/urn:nbn:hr:149:553155

Žlabravec, V. (2021). 'Praćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža', Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:149:553155

Žlabravec V. Praćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža [Master's thesis]. Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology; 2021 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:149:553155

V. Žlabravec, "Praćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža", Master's thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:149:553155

Metadata
TitlePraćenje koncentracije u procesu kristalizacije primjenom neuronskih mreža
Title (english)Concentration monitoring in the crystallization process using neural networks
AuthorVeronika Žlabravec
MentorNenad Bolf (mentor)
Committee memberNenad Bolf (predsjednik povjerenstva)
Committee memberJasna Prlić Kardum (član povjerenstva)
Committee memberŽeljka Ujević Andrijić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Chemical Engineering and Technology
Zagreb
Defense date and country2021-09-24, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Chemical Engineering
Abstract
Strogi zahtjevi i složenost procesa stvorili su potrebu za razvojem instrumenata i postupaka kojima će se proces kristalizacije moći kontinuirano pratiti i voditi. Za kontinuirano praćenje koncentracije kao jedne od najvažnijih značajki kvalitete, u posljednje vrijeme se sve više ispituju i primjenjuju optičke sonde za kontinuirano mjerenje. S prikupljenim spektralnim podatcima moguće je razviti kalibracijski model nekom od metoda strojnog učenja. U ovom radu razvijeni su i ispitani modeli neuronskih mreža za modeliranje ovisnosti koncentracije aktivne tvari ceritiniba u tetrahidrofuranu o temperaturi i spektralnim podacima dobivenim mjerenjima u UV-Vis spektru. Nizom eksperimenata, u kojima je ispitan utjecaj predobrade podataka, strukture i broja neurona, kao i prijenosne funkcije, analizirani su modeli razvijeni neuronskim mrežama. Kalibracijski modeli služit će za kontinuirano praćenje koncentracije ceritiniba u procesu kristalizacije navedenog sustava.
Abstract (english)
The strict requirements and complexity of the process have created the need to develop instruments and procedures by which the crystallization process can be continuously monitored and controlled. Recently, optical probes have been increasingly tested and applied for continuous concentration monitoring since this is one of the most important quality features. With collected spectral data, it is possible to develop a calibration model using one of the machine learning methods. In this work, application of neural networks as a method for modeling the dependence of concentration of active substance ceritinib in tetrahydrofuran on temperature and spectral data obtained by measurements in the UV-Vis spectrum was investigated. Through a series of experiments, in which the influence of data preprocessing, number of neurons, and transfer function was examined, models developed by neural networks were analyzed. The purpose of the developed calibration models is to continuously monitor the concentration in the process of crystallization of the particular system.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:149:553155
Study programmeTitle: Chemical Engineering - Graduate study
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka kemijskog inženjerstva (magistar/magistra inženjer/inženjerka kemijskog inženjerstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2023-04-17 12:48:14