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Prethodno priopćenje

https://doi.org/10.17559/TV-20191119153507

Application of Predictive Models for Natural Gas Needs - Current State and Future Trends Review

Dušan Bajatović ; University of Novi Sad, Faculty of Technical Sciences, Department of Industrial Engineering and Engineering Management, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia
Aleksandar S. Anđelković orcid id orcid.org/0000-0003-2736-6793 ; University of Novi Sad, Faculty of Technical Sciences, Department of Energy & Process Engineering, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia
Ilija Ćosić ; University of Novi Sad, Faculty of Technical Sciences, Department of Industrial Engineering and Engineering Management, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia
Rado Maksimović ; University of Novi Sad, Faculty of Technical Sciences, Department of Industrial Engineering and Engineering Management, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia


Puni tekst: engleski pdf 1.638 Kb

str. 648-655

preuzimanja: 961

citiraj


Sažetak

Nowadays, in terms of trading on the world scale, to foresee a natural gas consumption represents an essential activity. In the first part, the paper examines the current state of the Serbian natural gas sector and methodology applied for prediction and capacity planning. In addition, the study intends to give a comprehensive assessment of predictive algorithms for natural gas needs involved in the last decade with projections and suggestions for future applications. The primary task is to evaluate used predictive models with an emphasis on the accuracy of the predictions obtained. Additionally, the paper will analyse used parameters, consumption scale, prediction scope, forecast algorithms, and other related information. The main objective of this study is to review the new-fangled information related analyses data from peer-reviewed journals, international conferences, and books.

Ključne riječi

artificial intelligence; model; natural gas; prediction; review

Hrčak ID:

236824

URI

https://hrcak.srce.hr/236824

Datum izdavanja:

15.4.2020.

Posjeta: 2.360 *