A Comparison of Short-Term Water Demand Forecasting Models
Author
Abstract
Suggested Citation
DOI: 10.1007/s11269-019-02213-y
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Guoqiang Chen & Tianyu Long & Jiangong Xiong & Yun Bai, 2017. "Multiple Random Forests Modelling for Urban Water Consumption Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4715-4729, December.
- Ashu Jain & Ashish Kumar Varshney & Umesh Chandra Joshi, 2001. "Short-Term Water Demand Forecast Modelling at IIT Kanpur Using Artificial Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 15(5), pages 299-321, October.
- Salah L. Zubaidi & Sadik K. Gharghan & Jayne Dooley & Rafid M. Alkhaddar & Mawada Abdellatif, 2018. "Short-Term Urban Water Demand Prediction Considering Weather Factors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4527-4542, November.
- Jorge Caiado, 2009. "Performance of combined double seasonal univariate time series models for forecasting water demand," CEMAPRE Working Papers 0903, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
- Mukand Babel & Victor Shinde, 2011. "Identifying Prominent Explanatory Variables for Water Demand Prediction Using Artificial Neural Networks: A Case Study of Bangkok," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1653-1676, April.
- Linas Gelažanskas & Kelum A. A. Gamage, 2015. "Forecasting Hot Water Consumption in Residential Houses," Energies, MDPI, vol. 8(11), pages 1-16, November.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Anna Borucka, 2023. "Seasonal Methods of Demand Forecasting in the Supply Chain as Support for the Company’s Sustainable Growth," Sustainability, MDPI, vol. 15(9), pages 1-21, April.
- Irene Marzola & Stefano Alvisi & Marco Franchini, 2022. "A Comparison of Model-Based Methods for Leakage Localization in Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5711-5727, November.
- Salah L. Zubaidi & Sandra Ortega-Martorell & Patryk Kot & Rafid M. Alkhaddar & Mawada Abdellatif & Sadik K. Gharghan & Maytham S. Ahmed & Khalid Hashim, 2020. "A Method for Predicting Long-Term Municipal Water Demands Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1265-1279, February.
- Caspar V. C. Geelen & Doekle R. Yntema & Jaap Molenaar & Karel J. Keesman, 2021. "Burst Detection by Water Demand Nowcasting Based on Exogenous Sensors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(4), pages 1183-1196, March.
- Jens Kley-Holsteg & Florian Ziel, 2020. "Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso," Papers 2005.04522, arXiv.org.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Salah L. Zubaidi & Sadik K. Gharghan & Jayne Dooley & Rafid M. Alkhaddar & Mawada Abdellatif, 2018. "Short-Term Urban Water Demand Prediction Considering Weather Factors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4527-4542, November.
- Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & En-hong Guan & Yong-xiang Wu & Juan Gao & Rui-min He, 2016. "Adaptation to climate change impacts on water demand," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(1), pages 81-99, January.
- Mukand Babel & Nisuchcha Maporn & Victor Shinde, 2014. "Incorporating Future Climatic and Socioeconomic Variables in Water Demand Forecasting: A Case Study in Bangkok," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 2049-2062, May.
- Md Haque & Ataur Rahman & Dharma Hagare & Golam Kibria, 2014. "Probabilistic Water Demand Forecasting Using Projected Climatic Data for Blue Mountains Water Supply System in Australia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1959-1971, May.
- Jens Kley-Holsteg & Florian Ziel, 2020. "Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso," Papers 2005.04522, arXiv.org.
- Vinit Sehgal & Rajeev Sahay & Chandranath Chatterjee, 2014. "Effect of Utilization of Discrete Wavelet Components on Flood Forecasting Performance of Wavelet Based ANFIS Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1733-1749, April.
- Karamaziotis, Panagiotis I. & Raptis, Achilleas & Nikolopoulos, Konstantinos & Litsiou, Konstantia & Assimakopoulos, Vassilis, 2020. "An empirical investigation of water consumption forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(2), pages 588-606.
- Linas Gelažanskas & Kelum A. A. Gamage, 2016. "Distributed Energy Storage Using Residential Hot Water Heaters," Energies, MDPI, vol. 9(3), pages 1-13, February.
- Sara Fontdecaba & Pere Grima & Lluís Marco & Lourdes Rodero & José Sánchez-Espigares & Ignasi Solé & Xavier Tort-Martorell & Dominique Demessence & Victor Martínez De Pablo & Jordi Zubelzu, 2012. "A Methodology to Model Water Demand based on the Identification of Homogenous Client Segments. Application to the City of Barcelona," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(2), pages 499-516, January.
- Abdüsselam Altunkaynak, 2007. "Forecasting Surface Water Level Fluctuations of Lake Van by Artificial Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(2), pages 399-408, February.
- Bo Lin & Shuhui Li & Yang Xiao, 2017. "Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System," Energies, MDPI, vol. 10(11), pages 1-17, October.
- Carvalho, Isabella de Castro & Calijuri, Maria Lúcia & Assemany, Paula Peixoto & Silva, Marcos Dornelas Freitas Machado e & Moreira Neto, Ronan Fernandes & Santiago, Aníbal da Fonseca & de Souza, Maur, 2013. "Sustainable airport environments: A review of water conservation practices in airports," Resources, Conservation & Recycling, Elsevier, vol. 74(C), pages 27-36.
- Gajda, Janusz & Bartnicki, Grzegorz & Burnecki, Krzysztof, 2018. "Modeling of water usage by means of ARFIMA–GARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 644-657.
- C. Iglesias & J. Martínez Torres & P. García Nieto & J. Alonso Fernández & C. Díaz Muñiz & J. Piñeiro & J. Taboada, 2014. "Turbidity Prediction in a River Basin by Using Artificial Neural Networks: A Case Study in Northern Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 319-331, January.
- Marcel Antal & Tudor Cioara & Ionut Anghel & Radoslaw Gorzenski & Radoslaw Januszewski & Ariel Oleksiak & Wojciech Piatek & Claudia Pop & Ioan Salomie & Wojciech Szeliga, 2019. "Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model," Energies, MDPI, vol. 12(5), pages 1-18, March.
- Dong-Her Shih & Ching-Hsien Liao & Ting-Wei Wu & Huan-Shuo Chang & Ming-Hung Shih, 2022. "WSI: A New Early Warning Water Survival Index for the Domestic Water Demand," Mathematics, MDPI, vol. 10(23), pages 1-19, November.
- Sankhadeep Chatterjee & Sarbartha Sarkar & Nilanjan Dey & Soumya Sen, 2018. "Non-Dominated Sorting Genetic Algorithm-II-Induced Neural-Supported Prediction of Water Quality with Stability Analysis," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-20, June.
- Thomas M Fullerton Jr & Arturo Elias, 2004. "Short-Term Water Consumption Dynamics in El Paso, Texas," Others 0410005, University Library of Munich, Germany.
- George Panagopoulos & George Bathrellos & Hariklia Skilodimou & Faini Martsouka, 2012. "Mapping Urban Water Demands Using Multi-Criteria Analysis and GIS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(5), pages 1347-1363, March.
- Dongwoo Jang & Gyewoon Choi, 2017. "Estimation of Non-Revenue Water Ratio for Sustainable Management Using Artificial Neural Network and Z-Score in Incheon, Republic of Korea," Sustainability, MDPI, vol. 9(11), pages 1-15, October.
More about this item
Keywords
Water demand; Short-term forecasting; Moving window;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:33:y:2019:i:4:d:10.1007_s11269-019-02213-y. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.