{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T11:03:48Z","timestamp":1777547028035,"version":"3.51.4"},"reference-count":42,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Asia Pac. J. Oper. Res."],"published-print":{"date-parts":[[2013,4]]},"abstract":"<jats:p> The possibility for more confidential predictions, leaning on scientific methods and accomplishments of information technology leaves more time for the realization of logistic needs. Longstanding ambitions to acquire desired levels of efficiency within the system with minimal costs of resources, materials, energy and money are the features of executive structures of logistic systems. A successful logistic process is based on validation of technological development, indicating the need for a faster and more confidential integration of logistic systems and \"instilling confidence\" with military units that provide critical support (supply, transport and maintenance) will be reliably realized according to relevance and priority. Conclusions like these impose the necessity that the decision-making process of logistic organs is accessed carefully and systematically, since any wrong decision leads to a reduced state of readiness for military units. To facilitate the day-to-day operation of the Army of Serbia and the completion of both scheduled and unscheduled tasks it is necessary to satisfy the wide range of transport requirements. In this paper, the Adaptive Neuro Fuzzy Inference System (ANFIS) is described, thus making possible a strategy of coordination of transport assets to formulate an automatic control strategy. This model successfully imitates the decision-making process of the chiefs of logistic support. As a result of the research, it is shown that the suggested ANFIS, which has the ability to learn, has a possibility to imitate the decision-making process of the transport support officers and show the level of competence that is comparable with the level of their competence. <\/jats:p>","DOI":"10.1142\/s0217595912500534","type":"journal-article","created":{"date-parts":[[2013,1,31]],"date-time":"2013-01-31T13:05:15Z","timestamp":1359637515000},"page":"1250053","source":"Crossref","is-referenced-by-count":11,"title":["APPLICATION OF ADAPTIVE NEURO FUZZY INFERENCE SYSTEM IN THE PROCESS OF TRANSPORTATION SUPPORT"],"prefix":"10.1142","volume":"30","author":[{"given":"DRAGAN","family":"PAMU\u010cAR","sequence":"first","affiliation":[{"name":"Military Academy, University of Defence, Pavla Jurisica Sturma 33, 11000 Belgrade, Serbia"}]},{"given":"VESKO","family":"LUKOVAC","sequence":"additional","affiliation":[{"name":"Military Academy, University of Defence, Pavla Jurisica Sturma 33, 11000 Belgrade, Serbia"}]},{"given":"SNE\u017dANA","family":"PEJ\u010cI\u0106-TARLE","sequence":"additional","affiliation":[{"name":"Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia"}]}],"member":"219","published-online":{"date-parts":[[2013,4,4]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1287\/inte.19.4.20"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1109\/41.807988"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1287\/trsc.25.1.19"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1057\/jors.1980.170"},{"key":"rf5","volume-title":"Applied Mathematical Programming","author":"Bradley S. 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