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doctoral thesis
Primjena metoda umjetne inteligencije pri izboru materijala
Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2004. urn:nbn:hr:235:624569
Lisjak, Dragutin
University of Zagreb
Faculty of Mechanical Engineering and Naval Architecture

Institutional repository: Repository of Faculty of Mechanical Engineering and Naval Architecture University of Zagreb

Cite this document

Lisjak, D. (2004). Primjena metoda umjetne inteligencije pri izboru materijala (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:235:624569

Lisjak, Dragutin. "Primjena metoda umjetne inteligencije pri izboru materijala." Doctoral thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2004. https://urn.nsk.hr/urn:nbn:hr:235:624569

Lisjak, Dragutin. "Primjena metoda umjetne inteligencije pri izboru materijala." Doctoral thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2004. https://urn.nsk.hr/urn:nbn:hr:235:624569

Lisjak, D. (2004). 'Primjena metoda umjetne inteligencije pri izboru materijala', Doctoral thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, accessed 29 November 2024, https://urn.nsk.hr/urn:nbn:hr:235:624569

Lisjak D. Primjena metoda umjetne inteligencije pri izboru materijala [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture; 2004 [cited 2024 November 29] Available at: https://urn.nsk.hr/urn:nbn:hr:235:624569

D. Lisjak, "Primjena metoda umjetne inteligencije pri izboru materijala", Doctoral thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2004. Available at: https://urn.nsk.hr/urn:nbn:hr:235:624569

Metadata
TitlePrimjena metoda umjetne inteligencije pri izboru materijala
Title (english)Application of artifical intelligence methods in materials selection
AuthorDragutin Lisjak
MentorTomislav Filetin (mentor)
Committee memberBranko Novaković (predsjednik povjerenstva)
Committee memberTomislav Filetin (član povjerenstva)
Committee memberMladen Stupnišek (član povjerenstva)
Committee memberBojan Jerbić (član povjerenstva)
Committee memberDarko Grundler (član povjerenstva)
MBZ: 173300
GranterUniversity of Zagreb
Faculty of Mechanical Engineering and Naval Architecture
Zagreb
Defense date and country2004-11-24, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mechanical Engineering
Universal decimal classification
(UDC)		620 - Materials testing. Power stations. Economics of energy
004 - Computer science and technology. Computing. Data processing
Abstract
U radu je sažeto dan prikaz aktualnih metoda umjetne inteligencije: neuronskih mreža, neizrazite logike, genetičkih algoritama i ekspertnih sustava. Detaljno je opisana struktura zamišljenog inteligentnog sustava za izbor materijala u uvjetima trošenja kao i način za poboljšanje njegove glavne komponente mehanizma zaključivanja. Također su opisani i podmehanizmi glavnog mehanizma zaključivanja: mehanizam za obradu konverzacije, mehanizam za obradu asocijacija, mehanizam za obradu pravila mehanizam za obradu kriterija i izbor materijala, mehanizam za izbora postupaka modificiranja površina. U eksperimentalnom dijelu rada dan je plan izgradnje inteligentnog sustav za izbor materijala, način prikaza rezultata eksperimenta te pregled softverskih alata. Prikazani su načini mapiranja ulazno-izlaznih skupova za učenje neuronskih mreža i mehanizama zaključivanja neizrazite (fuzzy) logike. Prikazan je način kreiranja vremenskih asocijativnih matrica odgovornih za dobivanje i objašnjenje rješenja razmatranog problema. Prikazan je način optimiranja parametara neuronskih mreža genetičkim algoritmima, kao i primjena NeuroFuzzy modela neizrazite logike. Dan je konkretni primjer načina rada mehanizma zaključivanja inteligentnog sustava za izbor materijala.
Abstract (english)
In the work, current artifical intelligence methods are concisely presented: neural networks, fuzzy logic, genetic algorithms and expert systems. Structure of the designed intelligent system for material selection in tribological conditions is described detailedly, as well as the ways for improvement of its main inference engine component. The subengines of the main inference engine are also presented: conversation processing engine, associations processing engine, rules processing engine, criteria processing & material selection engine, engine for selection of surface modification processes. In experimental part of the work, concept for construction of the intelligent system for material selection is given, as well as the method how to present the experimental results and an overview of software tools. Mapping methods of the input-output data for training of neural networks and inference engines using fuzzy logic are presented. Procedure for creating of the time associative matrices which manage obtaining and explanation of the solution of the analyzed problem is presented. Optimizing of neural network using genetic algorithms is presented, as well as application of NeuroFuzzy model of fuzzy logic. An actual example illustrating operating principle of inference engine of the intelligent system for material selection is provided.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:235:624569
Study programmeTitle: Mechanical Engineering and Naval Architecture
Study programme type: university
Study level: postgraduate
Academic / professional title: doktor/doktorica znanosti, područje tehničkih znanosti (doktor/doktorica znanosti, područje tehničkih znanosti)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-12-04 13:54:50