A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques
This paper proposes a method for short-term weekly water-demand forecasting combining various statistical techniques. In the proposed method, training datasets are prepared through exploratory data analysis, several data preprocessing steps, and an input selection step; also, forecasting models are...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-09-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/69/1/154 |
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| author | Jungwon Yu Hyansu Bae Mi-Seon Kang Kwang-Ju Kim In-Su Jang |
| author_facet | Jungwon Yu Hyansu Bae Mi-Seon Kang Kwang-Ju Kim In-Su Jang |
| author_sort | Jungwon Yu |
| collection | DOAJ |
| description | This paper proposes a method for short-term weekly water-demand forecasting combining various statistical techniques. In the proposed method, training datasets are prepared through exploratory data analysis, several data preprocessing steps, and an input selection step; also, forecasting models are constructed by support vector regression. After this, weekly water-demand forecasts are calculated using iterated and direct strategies. To verify the performance, the proposed method is applied to urban hourly water-demand datasets provided by the Battle of Water Demand Forecasting organized in the 3rd WDSA-CCWI Joint Conference. |
| format | Article |
| id | doaj-art-bb331bdaf9f6474f99ef96800ab8616d |
| institution | Kabale University |
| issn | 2673-4591 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-bb331bdaf9f6474f99ef96800ab8616d2025-08-20T03:43:36ZengMDPI AGEngineering Proceedings2673-45912024-09-0169115410.3390/engproc2024069154A Study on Short-Term Water-Demand Forecasting Using Statistical TechniquesJungwon Yu0Hyansu Bae1Mi-Seon Kang2Kwang-Ju Kim3In-Su Jang4Daegu-Gyeongbuk Research Division, Electronics and Telecommunications Research Institute, Daegu 42994, Republic of KoreaDaegu-Gyeongbuk Research Division, Electronics and Telecommunications Research Institute, Daegu 42994, Republic of KoreaDaegu-Gyeongbuk Research Division, Electronics and Telecommunications Research Institute, Daegu 42994, Republic of KoreaDaegu-Gyeongbuk Research Division, Electronics and Telecommunications Research Institute, Daegu 42994, Republic of KoreaDaegu-Gyeongbuk Research Division, Electronics and Telecommunications Research Institute, Daegu 42994, Republic of KoreaThis paper proposes a method for short-term weekly water-demand forecasting combining various statistical techniques. In the proposed method, training datasets are prepared through exploratory data analysis, several data preprocessing steps, and an input selection step; also, forecasting models are constructed by support vector regression. After this, weekly water-demand forecasts are calculated using iterated and direct strategies. To verify the performance, the proposed method is applied to urban hourly water-demand datasets provided by the Battle of Water Demand Forecasting organized in the 3rd WDSA-CCWI Joint Conference.https://www.mdpi.com/2673-4591/69/1/154water demandshort-term forecastingsupport vector regressioniterated strategydirect strategy |
| spellingShingle | Jungwon Yu Hyansu Bae Mi-Seon Kang Kwang-Ju Kim In-Su Jang A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques Engineering Proceedings water demand short-term forecasting support vector regression iterated strategy direct strategy |
| title | A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques |
| title_full | A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques |
| title_fullStr | A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques |
| title_full_unstemmed | A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques |
| title_short | A Study on Short-Term Water-Demand Forecasting Using Statistical Techniques |
| title_sort | study on short term water demand forecasting using statistical techniques |
| topic | water demand short-term forecasting support vector regression iterated strategy direct strategy |
| url | https://www.mdpi.com/2673-4591/69/1/154 |
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