Error modeling of demand patterns to improve forecasting accuracy
This study aims to estimate and model error patterns to reduce forecast error and improve forecast accuracy for time series data. The objective is to assess the impact of incorporating error patterns as features in long short-term memory and transformer neural network models. The research employs a...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175223 |
| _version_ | 1811688934786203648 |
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| author | Sa, Ziheng |
| author2 | Jagath C Rajapakse |
| author_facet | Jagath C Rajapakse Sa, Ziheng |
| author_sort | Sa, Ziheng |
| collection | NTU |
| description | This study aims to estimate and model error patterns to reduce forecast error and improve forecast accuracy for time series data. The objective is to assess the impact of incorporating error patterns as features in long short-term memory and transformer neural network models. The research employs a comprehensive approach, utilizing a dataset comprising over 450 time series to evaluate baseline and modified models. Results reveal mixed outcomes, with some instances showing enhanced performance while others demonstrate no significant improvement or decline in performance. These findings underscore the complexities inherent in error modeling and emphasize the need for further investigation. Despite inconclusive results, this study contributes valuable insights into the challenges and opportunities associated with error modeling in time series forecasting. This paves the way for future research endeavors aimed at refining and advancing error modeling techniques in this domain. |
| first_indexed | 2024-10-01T05:40:06Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/175223 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:40:06Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1752232024-04-26T15:41:44Z Error modeling of demand patterns to improve forecasting accuracy Sa, Ziheng Jagath C Rajapakse School of Computer Science and Engineering ASJagath@ntu.edu.sg Computer and Information Science Error model Time series forecast This study aims to estimate and model error patterns to reduce forecast error and improve forecast accuracy for time series data. The objective is to assess the impact of incorporating error patterns as features in long short-term memory and transformer neural network models. The research employs a comprehensive approach, utilizing a dataset comprising over 450 time series to evaluate baseline and modified models. Results reveal mixed outcomes, with some instances showing enhanced performance while others demonstrate no significant improvement or decline in performance. These findings underscore the complexities inherent in error modeling and emphasize the need for further investigation. Despite inconclusive results, this study contributes valuable insights into the challenges and opportunities associated with error modeling in time series forecasting. This paves the way for future research endeavors aimed at refining and advancing error modeling techniques in this domain. Bachelor's degree 2024-04-21T13:49:59Z 2024-04-21T13:49:59Z 2024 Final Year Project (FYP) Sa, Z. (2024). Error modeling of demand patterns to improve forecasting accuracy. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175223 https://hdl.handle.net/10356/175223 en SCSE23-0550 application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science Error model Time series forecast Sa, Ziheng Error modeling of demand patterns to improve forecasting accuracy |
| title | Error modeling of demand patterns to improve forecasting accuracy |
| title_full | Error modeling of demand patterns to improve forecasting accuracy |
| title_fullStr | Error modeling of demand patterns to improve forecasting accuracy |
| title_full_unstemmed | Error modeling of demand patterns to improve forecasting accuracy |
| title_short | Error modeling of demand patterns to improve forecasting accuracy |
| title_sort | error modeling of demand patterns to improve forecasting accuracy |
| topic | Computer and Information Science Error model Time series forecast |
| url | https://hdl.handle.net/10356/175223 |
| work_keys_str_mv | AT saziheng errormodelingofdemandpatternstoimproveforecastingaccuracy |