Backpropagation neural networks for modeling gasoline consumption
This paper presents an artificial neural network (ANN) approach to gasoline consumption (GC) forecasting in Lebanon. In order to provide the forecasted gasoline consumption, the ANN interpolates among the GC and its determinants in a training data set. In this study, four ANN models are presented an...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | article |
| منشور في: |
2003
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/3158 http://dx.doi.org/10.1016/S0196-8904(02)00087-0 http://www.sciencedirect.com/science/article/pii/S0196890402000870 |
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إضافة وسم
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| _version_ | 1864513460165935104 |
|---|---|
| author | Nasr, George |
| author2 | Badr, E.A. Joun, C. |
| author2_role | author author |
| author_facet | Nasr, George Badr, E.A. Joun, C. |
| author_role | author |
| dc.creator.none.fl_str_mv | Nasr, George Badr, E.A. Joun, C. |
| dc.date.none.fl_str_mv | 2003 2016-02-23T07:48:51Z 2016-02-23T07:48:51Z 2016-02-23 |
| dc.identifier.none.fl_str_mv | 0196-8904 http://hdl.handle.net/10725/3158 http://dx.doi.org/10.1016/S0196-8904(02)00087-0 Nasr, G. E., Badr, E. A., & Joun, C. (2003). Backpropagation neural networks for modeling gasoline consumption. Energy Conversion and Management, 44(6), 893-905. http://www.sciencedirect.com/science/article/pii/S0196890402000870 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Energy Conversion and Management |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Backpropagation neural networks for modeling gasoline consumption |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This paper presents an artificial neural network (ANN) approach to gasoline consumption (GC) forecasting in Lebanon. In order to provide the forecasted gasoline consumption, the ANN interpolates among the GC and its determinants in a training data set. In this study, four ANN models are presented and implemented on real GC data. The first model is a univariate model based on past consumption values. The second model is a multivariate model based on GC time series and price (P). The third model is also a multivariate model based on GC and car registration (CR). Finally, the fourth model combines GC, P and CR. Forecasting performance measures, such as mean square errors and mean absolute deviations, are presented for all models. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_bc1c4f035cb4b78c3855dabfc37ed388 |
| identifier_str_mv | 0196-8904 Nasr, G. E., Badr, E. A., & Joun, C. (2003). Backpropagation neural networks for modeling gasoline consumption. Energy Conversion and Management, 44(6), 893-905. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/3158 |
| publishDate | 2003 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Backpropagation neural networks for modeling gasoline consumptionNasr, GeorgeBadr, E.A.Joun, C.This paper presents an artificial neural network (ANN) approach to gasoline consumption (GC) forecasting in Lebanon. In order to provide the forecasted gasoline consumption, the ANN interpolates among the GC and its determinants in a training data set. In this study, four ANN models are presented and implemented on real GC data. The first model is a univariate model based on past consumption values. The second model is a multivariate model based on GC time series and price (P). The third model is also a multivariate model based on GC and car registration (CR). Finally, the fourth model combines GC, P and CR. Forecasting performance measures, such as mean square errors and mean absolute deviations, are presented for all models.PublishedN/A2016-02-23T07:48:51Z2016-02-23T07:48:51Z20032016-02-23Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0196-8904http://hdl.handle.net/10725/3158http://dx.doi.org/10.1016/S0196-8904(02)00087-0Nasr, G. E., Badr, E. A., & Joun, C. (2003). Backpropagation neural networks for modeling gasoline consumption. Energy Conversion and Management, 44(6), 893-905.http://www.sciencedirect.com/science/article/pii/S0196890402000870enEnergy Conversion and Managementinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/31582016-08-23T09:26:54Z |
| spellingShingle | Backpropagation neural networks for modeling gasoline consumption Nasr, George |
| status_str | publishedVersion |
| title | Backpropagation neural networks for modeling gasoline consumption |
| title_full | Backpropagation neural networks for modeling gasoline consumption |
| title_fullStr | Backpropagation neural networks for modeling gasoline consumption |
| title_full_unstemmed | Backpropagation neural networks for modeling gasoline consumption |
| title_short | Backpropagation neural networks for modeling gasoline consumption |
| title_sort | Backpropagation neural networks for modeling gasoline consumption |
| url | http://hdl.handle.net/10725/3158 http://dx.doi.org/10.1016/S0196-8904(02)00087-0 http://www.sciencedirect.com/science/article/pii/S0196890402000870 |