Analysis of methods and techniques for prediction of natural gas consumption
Due to its many advantages, demand for natural gas has increased considerably and many models for predicting natural gas consumption are developed. The aim of this paper is to present an overview and systematic analysis of the latest research papers that deal with predictions of natural gas consumpt...
| Permalink: | http://skupni.nsk.hr/Record/nsk.NSK01001059517/Details |
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| Matična publikacija: |
Journal of information and organizational sciences (Online) 43 (2019), 1 ; str. 99-117 |
| Glavni autori: | Šebalj, Dario (Author), Mesarić, Josip, Dujak, Davor |
| Vrsta građe: | e-članak |
| Jezik: | eng |
| Predmet: | |
| Online pristup: |
https://doi.org/10.31341/jios.43.1.6 Journal of information and organizational sciences (Online) Hrčak |
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| 100 | 1 | |a Šebalj, Dario |4 aut | |
| 245 | 1 | 0 | |a Analysis of methods and techniques for prediction of natural gas consumption |h [Elektronička građa] : |b a literature review / |c Dario Šebalj, Josip Mesarić, Davor Dujak. |
| 300 | |b Ilustr. | ||
| 504 | |a Bibliografija: 47 jed. | ||
| 504 | |a Abstract. | ||
| 520 | |a Due to its many advantages, demand for natural gas has increased considerably and many models for predicting natural gas consumption are developed. The aim of this paper is to present an overview and systematic analysis of the latest research papers that deal with predictions of natural gas consumption for residential and commercial use from the year 2002 to 2017. Literature overview analysis was conducted using the two most relevant scientific databases Web of Science Core Collection and Scopus. The results indicate neural networks as the most common method used for predictions of natural gas consumption, while most accurate methods are genetic algorithms, support vector machines and ANFIS. Most used input variables are past natural gas consumption data and weather data, and prediction is most commonly made on daily and annual level on a country area level. Limitations of the research raise from relatively small number of analyzed papers but still research could be used for significant improving of prediction models for natural gas consumption. | ||
| 653 | 0 | |a Prirodni plin |a Potrošnja |a Modeli predviđanja |a Energija |a Pregled literature | |
| 700 | 1 | |a Mesarić, Josip |4 aut | |
| 700 | 1 | |a Dujak, Davor |4 aut | |
| 773 | 0 | |t Journal of information and organizational sciences (Online) |x 1846-9418 |g 43 (2019), 1 ; str. 99-117 |w nsk.(HR-ZaNSK)000672813 | |
| 981 | |b Be2019 |b B02/19 | ||
| 998 | |b tino2004 | ||
| 856 | 4 | 0 | |u https://doi.org/10.31341/jios.43.1.6 |
| 856 | 4 | 0 | |u https://jios.foi.hr/index.php/jios/article/view/1211 |y Journal of information and organizational sciences (Online) |
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| 856 | 4 | 0 | |u https://hrcak.srce.hr/221388 |y Hrčak |