Metode raspoznavanja obrazaca i njihova primjena u analitičkoj kemiji

undergraduate thesis

• Title (english): Pattern recognition methods and their application in analytical chemistry
• Author: Anja Rakas
• Mentor: Šime Ukić (mentor)
• Committee member: Šime Ukić (predsjednik povjerenstva)
• Committee member: Irena Škorić (član povjerenstva)
• Committee member: Mirjana Novak Stankov (član povjerenstva)
• Granter: University of Zagreb; Faculty of Chemical Engineering and Technology; Zagreb
• Defense date and country: 2018-09-19, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Chemistry; Analytic Chemistry

Abstract

Rudarenje podataka je novi pristup koji omogućava izvlačenje korisnih informacija iz skupova podataka. Prepoznavanje obrazaca izučava se u mnogim područjima kao što su biologija, medicina, psihologija, informatika, statistika... Postoje različite metode za prepoznavanje obrazaca. Primjerice linearna regresija, strojno učenje, metoda najbližeg susjeda i druge. Jedan od oblika prepoznavanja obrazaca je klasifikacija koja pokušava koja pokušava podijeliti ulazne veličine u različite skupove (klase). U ovom radu opisani su načini prepoznavanja obrazaca i povezane metode koje su od značajne koristi analitičkoj kemiji.

Abstract (english)

Data mining is a new approach of revealing valuable information from different and mostly large data sets. Pattern recognition is studding in many areas such as biology, medicine, psychology, informatics, statistics... There are different methods to recognize patterns. For example, linear regression, machine learning, closest neighbor method, and more. One of them is classification that attempts to divide the input value into various classes. This work presents various modes of pattern recognition and related methods that are beneficial in analytical chemistry.

• Keywords: rudarenje podataka; prepoznavanje obrazaca; metode; analitička kemija
• Keywords (english): data mining; pattern recognitions; methods; analytical chemistry
• Language: croatian
• URN:NBN: urn:nbn:hr:149:334039
• Project: Number: IP-2014-09-7992; Title: Modeliranje okolišnih aspekata napredne obrade voda za razgradnju prioritetnih onečišćivala; Title: Modeling of environmental aspects of advanced water treatment for fegradation of priority pollutants; Acronym: MEAoWT; Leader: Tomislav Bolanča; Jurisdiction: Croatia; Funder: HRZZ; Funding stream: IP
• Study programme: Title: Applied Chemistry - Undergraduate study; specializations in: Environmental chemistry and green technologies, Advanced materials and technologies, Applied organic chemistry; Course: Environmental chemistry and green technologies; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) primijenjene kemije (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) primijenjene kemije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2022-05-20 13:21:25