<?xml version="1.0"?><rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:edm="http://www.europeana.eu/schemas/edm/" xmlns:wgs84_pos="http://www.w3.org/2003/01/geo/wgs84_pos" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:rdaGr2="http://rdvocab.info/ElementsGr2" xmlns:oai="http://www.openarchives.org/OAI/2.0/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:ore="http://www.openarchives.org/ore/terms/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:dcterms="http://purl.org/dc/terms/"><edm:WebResource rdf:about="http://www.dlib.si/stream/URN:NBN:SI:DOC-R8RET3FU/77-7cb910937fdb4908ac8-d2ed2f14-ae-f/PDF"><dcterms:extent>5633 KB</dcterms:extent></edm:WebResource><edm:WebResource rdf:about="http://www.dlib.si/stream/URN:NBN:SI:DOC-R8RET3FU/d623ecd6-3874-4bc3-abd7-e3ed53e286d0/TEXT"><dcterms:extent>248 KB</dcterms:extent></edm:WebResource><edm:WebResource rdf:about="http://www.dlib.si/stream/URN:NBN:SI:DOC-R8RET3FU/b8789c79-f01d-42da-bcfa-e23f1d7490e7/WEB"><dcterms:extent>0 KB</dcterms:extent></edm:WebResource><edm:ProvidedCHO rdf:about="URN:NBN:SI:DOC-R8RET3FU"><dcterms:issued>2013</dcterms:issued><dc:creator>Jelušič, Primož</dc:creator><dc:contributor>Kravanja, Stojan</dc:contributor><dc:contributor>Žlender, Bojan</dc:contributor><dc:format xml:lang="sl">XV, 130, IX, VIII str., 30 cm</dc:format><dc:identifier>COBISSID:17239574</dc:identifier><dc:identifier>URN:URN:NBN:SI:doc-R8RET3FU</dc:identifier><dc:language>sl</dc:language><dc:publisher xml:lang="sl">P. Jelušič</dc:publisher><dc:source xml:lang="sl">visokošolska dela</dc:source><dc:subject xml:lang="sl">Analiza</dc:subject><dc:subject xml:lang="sl">ANFIS</dc:subject><dc:subject xml:lang="sl">Disertacije</dc:subject><dc:subject xml:lang="sl">Geotehnične konstrukcije</dc:subject><dc:subject xml:lang="sl">mehka logika</dc:subject><dc:subject xml:lang="sl">modeli mehke logike</dc:subject><dc:subject xml:lang="sl">nevronske mreže</dc:subject><dc:subject xml:lang="sl">NLP</dc:subject><dc:subject xml:lang="sl">pavement structure</dc:subject><dc:subject xml:lang="sl">podporna konstrukcija s pasivnimi sidri</dc:subject><dc:subject xml:lang="sl">podzemno skladišče plina</dc:subject><dc:subject xml:lang="sl">soil nailing</dc:subject><dc:subject xml:lang="sl">underground gas storage</dc:subject><dc:subject xml:lang="sl">voziščna konstrukcija</dc:subject><dc:title xml:lang="sl">Modeli mehke logike in nevronske mreže za analizo geotehničnih konstrukcij| doktorska disertacija|</dc:title><dc:description xml:lang="sl">In this PhD dissertation, we have developed new models for the analysis of pavement, soil nal structure and underground gas storage. The models were developed by ANFIS method (adaptive network based fuzzy inference system). TheANFIS technique has better prediction capability then conventional analitical methods. The ANFIS models were developed on the basis of geotechnical calculation models and optimization models. The optimization is performed by the non-linear programming (NLP) approach. The accuracy of ANFIS models depends on the nonlinearity of the problem and neural network topologies. Therefore, the ANFIS models with different neural network topologywere developed. To test and validate the ANFIS models, a data sets were chosen, which was not used while training the network, was employed. In the PhD dissertation ANFIS models are developed for the prediction of pavementhorizontal strain at the bottom of the asphalt layer and vertical strain on the top of the sub-grade. The developed ANFIS models for soil nail wall are used to predict safety factor and optimal inclination of soil nail for any design soil nail wall. The ANFIS models for underground gas storage predict the optimal costs per unit of gas and optimal design of underground gas storage</dc:description><dc:description xml:lang="sl">V doktorski disertaciji smo razvili nove modele za analizo voziščne konstrukcije, podporne konstrukcije in podzemne konstrukcije. Modele smo izdelali z adaptivnimi nevronskimi mrežami in mehkim identifikacijskim sistemom (adaptive network based fuzzy inference system, ANFIS). ANFIS metoda v splošnem omogoča izdelavo geotehničnih modelov, ki imajo večjo sposobnost napovedi kot konvencionalne analitične metode. ANFIS modele smo izdelali na podlagi geomehanskih računskih modelov in optimizacijskih modelov. Optimizacijske modele smo izdelali z nelinearnim programiranjem (nonlinear programming, NLP). Natančnost napovedi modelov je odvisna od nelinearnosti obravnavanega problema. Ugotovili smo, da je v ANFIS modelih bistvenega pomenarazvrstitev nevronov. Za ta namen smo razvili ANFIS modele z različno topologijo nevronov in uporabili tisto, ki je imela najmanjšo odstopanje gledena množico testnih podatkov. V doktorski disertaciji razviti ANFIS modeli voziščne konstrukcije omogočajo napovedovanje horizontalne specifične deformacije na dnu asfaltne plasti in vertikalne specifične deformacije na podlagi. Razviti modeli za podporno konstrukcijo s pasivnimi sidri omogočajo napovedovanje faktorja varnosti in optimalnega naklona pasivnih sider. Dobljeni ANFIS modeli za podzemne konstrukcije omogočajo napovedovanje optimalnih izdelavnih stroškov podzemnega skladišča plina in optimalne zasnove kaverne</dc:description><edm:type>TEXT</edm:type><dc:type xml:lang="sl">visokošolska dela</dc:type><dc:type xml:lang="en">theses and dissertations</dc:type><dc:type rdf:resource="http://www.wikidata.org/entity/Q1266946" /></edm:ProvidedCHO><ore:Aggregation rdf:about="http://www.dlib.si/?URN=URN:NBN:SI:DOC-R8RET3FU"><edm:aggregatedCHO rdf:resource="URN:NBN:SI:DOC-R8RET3FU" /><edm:isShownBy rdf:resource="http://www.dlib.si/stream/URN:NBN:SI:DOC-R8RET3FU/77-7cb910937fdb4908ac8-d2ed2f14-ae-f/PDF" /><edm:rights rdf:resource="http://rightsstatements.org/vocab/InC/1.0/" /><edm:provider>Slovenian National E-content Aggregator</edm:provider><edm:intermediateProvider xml:lang="en">National and University Library of Slovenia</edm:intermediateProvider><edm:dataProvider xml:lang="sl">Univerza v Mariboru, Fakulteta za gradbeništvo, prometno inženirstvo in arhitekturo</edm:dataProvider><edm:object rdf:resource="http://www.dlib.si/streamdb/URN:NBN:SI:DOC-R8RET3FU/maxi/edm" /><edm:isShownAt rdf:resource="http://www.dlib.si/details/URN:NBN:SI:DOC-R8RET3FU" /></ore:Aggregation></rdf:RDF>