Citations (51)
Keep up to date with the latest research on this topic with citation updates for this article.
Read on this site (2)
Maria Xenochristou & Zoran Kapelan. (2020) An ensemble stacked model with bias correction for improved water demand forecasting. Urban Water Journal 17:3, pages 212-223.
Read now
Read now
Bruno Melo Brentan, Gustavo Lima Meirelles, Daniel Manzi & Edevar Luvizotto. (2018) Water demand time series generation for distribution network modeling and water demand forecasting. Urban Water Journal 15:2, pages 150-158.
Read now
Read now
Articles from other publishers (49)
Xinyu Xia, Bin Liu, Rui Tian, Zuli He, Suyue Han, Ke Pan, Jingjing Yang & Yiting Zhang. (2023) An interval water demand prediction method to reduce uncertainty: A case study of Sichuan Province, China. Environmental Research 238, pages 117143.
Crossref
Crossref
Madani Bessedik, Chérifa Abdelbaki, Sidi Mohamed Tiar, Abderrahim Badraoui, Abdesselam Megnounif, Mattheus Goosen, Khaldoon A. Mourad, Mirza Barjees Baig & Abed Alataway. (2023) Strategic Decision-Making in Sustainable Water Management Using Demand Analysis and the Water Evaluation and Planning Model. Sustainability 15:22, pages 16083.
Crossref
Crossref
Hossein Namdari, Ali Haghighi & Seyed Mohammad Ashrafi. (2023) Short-term urban water demand forecasting; application of 1D convolutional neural network (1D CNN) in comparison with different deep learning schemes. Stochastic Environmental Research and Risk Assessment.
Crossref
Crossref
M Kavya, Aneesh Mathew, Padala Raja Shekar & Sarwesh P. (2023) Short term water demand forecast modelling using artificial intelligence for smart water management. Sustainable Cities and Society 95, pages 104610.
Crossref
Crossref
Yipeng Wu, Xiaoting Wang, Shuming Liu, Xipeng Yu & Xue Wu. (2023) A weighting strategy to improve water demand forecasting performance based on spatial correlation between multiple sensors. Sustainable Cities and Society 93, pages 104545.
Crossref
Crossref
Feifei He, Hairong Zhang, Qinjuan Wan, Shu Chen & Yuqi Yang. (2023) Medium Term Streamflow Prediction Based on Bayesian Model Averaging Using Multiple Machine Learning Models. Water 15:8, pages 1548.
Crossref
Crossref
Pranav Dhawan, Daniele Dalla Torre, Ariele Zanfei, Andrea Menapace, Michele Larcher & Maurizio Righetti. (2023) Assessment of ERA5-Land Data in Medium-Term Drinking Water Demand Modelling with Deep Learning. Water 15:8, pages 1495.
Crossref
Crossref
Lifeng Wu & Yuan Meng. (2023) Water Requirement in North China from Grey Point Prediction and Grey Interval Prediction. Water 15:8, pages 1453.
Crossref
Crossref
Hauwa Mustafa, Gasim Hayder, S. Abba, Abeer Algarni, Mohammed Mnzool & Abdurahman Nour. (2023) Performance Evaluation of Hydroponic Wastewater Treatment Plant Integrated with Ensemble Learning Techniques: A Feature Selection Approach. Processes 11:2, pages 478.
Crossref
Crossref
Cai Jian, Jinliang GaoYongpeng Xu. (2022) Anomaly Detection and Classification in Water Distribution Networks Integrated with Hourly Nodal Water Demand Forecasting Models and Feature Extraction Technique. Journal of Water Resources Planning and Management 148:11.
Crossref
Crossref
Muhammad Ahmad Raza, Mohammed M. A. Almazah, Zulfiqar Ali, Ijaz Hussain & Fuad S. Al-Duais. (2022) Application of Extreme Learning Machine Algorithm for Drought Forecasting. Complexity 2022, pages 1-28.
Crossref
Crossref
Qiongfang Li, Yao Du, Zhennan Liu, Zhengmo Zhou, Guobin Lu & Qihui Chen. (2022) Drought prediction in the Yunnan–Guizhou Plateau of China by coupling the estimation of distribution algorithm and the extreme learning machine. Natural Hazards 113:3, pages 1635-1661.
Crossref
Crossref
Shengle Cao, Ruifeng You, Xinying Li, Jingjing Jia, Jun Wang & Yang Liu. (2022) A novel approach for estimating the capacity of ungauged small reservoirs using remote sensing and DEM. Hydrology Research 53:7, pages 1001-1016.
Crossref
Crossref
Cai Jian, Jinliang Gao, Yongpeng Xu & Liqun Deng. (2022) A framework for forecasting the hourly nodal water demand and improving the performance of real-time hydraulic models considering model uncertainty. Journal of Hydroinformatics 24:3, pages 497-516.
Crossref
Crossref
Seda Hatice GÖKLER & Semra BORAN. (2022) Prediction of Demand for Red Blood Cells Using Artificial Intelligence Methods. Academic Platform Journal of Engineering and Smart Systems 10:2, pages 86-93.
Crossref
Crossref
Ariele Zanfei, Andrea MenapaceFrancesco Granata, Rudy Gargano, Matteo FrisinghelliMaurizio Righetti. (2022) An Ensemble Neural Network Model to Forecast Drinking Water Consumption. Journal of Water Resources Planning and Management 148:5.
Crossref
Crossref
Ganggang Zhang, Yingbin Hu, Dongxuan Yang, Lei Ma, Mengqi Zhang & Xinliang Liu. (2022) Short-Term Bathwater Demand Forecasting for Shared Shower Rooms in Smart Campuses Using Machine Learning Methods. Water 14:8, pages 1291.
Crossref
Crossref
Omnia Abu Waraga, Abdulrahman Abdeljaber, Manar Abu Talib & Mohamed Abdallah. (2021) Investigating Water Consumption Patterns Through Time Series Clustering. Investigating Water Consumption Patterns Through Time Series Clustering.
Rana Muhammad Adnan, Reham R. Mostafa, Ozgur Kisi, Zaher Mundher Yaseen, Shamsuddin Shahid & Mohammad Zounemat-Kermani. (2021) Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization. Knowledge-Based Systems 230, pages 107379.
Crossref
Crossref
A. A. Masrur Ahmed, Ravinesh C. Deo, Afshin Ghahramani, Nawin Raj, Qi Feng, Zhenliang Yin & Linshan Yang. (2021) LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios. Stochastic Environmental Research and Risk Assessment 35:9, pages 1851-1881.
Crossref
Crossref
Tony Salloom, Okyay Kaynak & Wei He. (2021) A novel deep neural network architecture for real-time water demand forecasting. Journal of Hydrology 599, pages 126353.
Crossref
Crossref
Kang-Min Koo, Kuk-Heon Han, Kyung-Soo Jun, Gyumin Lee, Jung-Sik Kim & Kyung-Taek Yum. (2021) Performance Assessment for Short-Term Water Demand Forecasting Models on Distinctive Water Uses in Korea. Sustainability 13:11, pages 6056.
Crossref
Crossref
A. A. Masrur Ahmed, Ravinesh C Deo, Nawin Raj, Afshin Ghahramani, Qi Feng, Zhenliang Yin & Linshan Yang. (2021) Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data. Remote Sensing 13:4, pages 554.
Crossref
Crossref
Mukesh K. Tiwari, Ravinesh C. Deo & Jan F. Adamowski. 2021. Advances in Streamflow Forecasting. Advances in Streamflow Forecasting
263
279
.
Anna Di Mauro, Andrea Cominola, Andrea Castelletti & Armando Di Nardo. (2020) Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets. Water 13:1, pages 36.
Crossref
Crossref
Salah L. Zubaidi, Iqbal H. Abdulkareem, Khalid S. Hashim, Hussein Al-Bugharbee, Hussein Mohammed Ridha, Sadik Kamel Gharghan, Fuod F. Al-Qaim, Magomed Muradov, Patryk Kot & Rafid Al-Khaddar. (2020) Hybridised Artificial Neural Network Model with Slime Mould Algorithm: A Novel Methodology for Prediction of Urban Stochastic Water Demand. Water 12:10, pages 2692.
Crossref
Crossref
Mohammad Zounemat-Kermani, Elena Matta, Andrea Cominola, Xilin Xia, Qing Zhang, Qiuhua Liang & Reinhard Hinkelmann. (2020) Neurocomputing in surface water hydrology and hydraulics: A review of two decades retrospective, current status and future prospects. Journal of Hydrology 588, pages 125085.
Crossref
Crossref
Manish Shrestha, Sujal Manandhar & Sangam Shrestha. (2020) Forecasting water demand under climate change using artificial neural network: a case study of Kathmandu Valley, Nepal. Water Supply 20:5, pages 1823-1833.
Crossref
Crossref
Salah L. Zubaidi, Sandra Ortega-Martorell, Hussein Al-Bugharbee, Ivan Olier, Khalid S. Hashim, Sadik Kamel Gharghan, Patryk Kot & Rafid Al-Khaddar. (2020) Urban Water Demand Prediction for a City That Suffers from Climate Change and Population Growth: Gauteng Province Case Study. Water 12:7, pages 1885.
Crossref
Crossref
Salah Zubaidi, Hussein Al-Bugharbee, Sandra Ortega-Martorell, Sadik Gharghan, Ivan Olier, Khalid Hashim, Nabeel Al-Bdairi & Patryk Kot. (2020) A Novel Methodology for Prediction Urban Water Demand by Wavelet Denoising and Adaptive Neuro-Fuzzy Inference System Approach. Water 12:6, pages 1628.
Crossref
Crossref
Hongyan Du, Zhihua Zhao & Huifeng Xue. (2020) ARIMA-M: A New Model for Daily Water Consumption Prediction Based on the Autoregressive Integrated Moving Average Model and the Markov Chain Error Correction. Water 12:3, pages 760.
Crossref
Crossref
Jorge E. Pesantez, Emily Zechman Berglund & Nikhil Kaza. (2020) Smart meters data for modeling and forecasting water demand at the user-level. Environmental Modelling & Software 125, pages 104633.
Crossref
Crossref
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 34:3, pages 1265-1279.
Crossref
Crossref
Md Shamsur Rahim, Khoi Anh Nguyen, Rodney Anthony Stewart, Damien Giurco & Michael Blumenstein. (2020) Machine Learning and Data Analytic Techniques in Digital Water Metering: A Review. Water 12:1, pages 294.
Crossref
Crossref
N. Rasifaghihi, S.S. Li & F. Haghighat. (2020) Forecast of urban water consumption under the impact of climate change. Sustainable Cities and Society 52, pages 101848.
Crossref
Crossref
Koutiva & Makropoulos. (2019) Exploring the Effects of Alternative Water Demand Management Strategies Using an Agent-Based Model. Water 11:11, pages 2216.
Crossref
Crossref
Guoqiang Chen, Tianyu Long, Yun Bai & Jin Zhang. (2019) A Forecasting Framework Based on Kalman Filter Integrated Multivariate Local Polynomial Regression: Application to Urban Water Demand. Neural Processing Letters 50:1, pages 497-513.
Crossref
Crossref
Piao Hu, Jun Tong, Jingcheng Wang, Yue Yang & Luca de Oliveira Turci. (2019) A hybrid model based on CNN and Bi-LSTM for urban water demand prediction. A hybrid model based on CNN and Bi-LSTM for urban water demand prediction.
Soukayna Mouatadid, Jan F. Adamowski, Mukesh K. Tiwari & John M. Quilty. (2019) Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting. Agricultural Water Management 219, pages 72-85.
Crossref
Crossref
Mohammad Rezaie-Balf, Sungwon Kim, Hossein Fallah & Sina Alaghmand. (2019) Daily river flow forecasting using ensemble empirical mode decomposition based heuristic regression models: Application on the perennial rivers in Iran and South Korea. Journal of Hydrology 572, pages 470-485.
Crossref
Crossref
Mohammad Rezaie-Balf, Ozgur Kisi & Lloyd H. C. Chua. (2019) Application of ensemble empirical mode decomposition based on machine learning methodologies in forecasting monthly pan evaporation. Hydrology Research 50:2, pages 498-516.
Crossref
Crossref
Zaher Mundher Yaseen, Sadeq Oleiwi Sulaiman, Ravinesh C. Deo & Kwok-Wing Chau. (2019) An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction. Journal of Hydrology 569, pages 387-408.
Crossref
Crossref
John Quilty, Jan Adamowski & Marie‐Amélie Boucher. (2019) A Stochastic Data‐Driven Ensemble Forecasting Framework for Water Resources: A Case Study Using Ensemble Members Derived From a Database of Deterministic Wavelet‐Based Models. Water Resources Research 55:1, pages 175-202.
Crossref
Crossref
Abdullahi Uwaisu Muhammad, Xiaodong Li & Jun Feng. 2019. Machine Learning and Intelligent Communications. Machine Learning and Intelligent Communications
595
622
.
Guancheng GuoShuming LiuYipeng WuJunyu LiRen ZhouXiaoyun Zhu. (2018) Short-Term Water Demand Forecast Based on Deep Learning Method. Journal of Water Resources Planning and Management 144:12.
Crossref
Crossref
Soukayna Mouatadid, Nawin Raj, Ravinesh C. Deo & Jan F. Adamowski. (2018) Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region. Atmospheric Research 212, pages 130-149.
Crossref
Crossref
Kai Wang & Evan G.R. Davies. (2018) Municipal water planning and management with an end-use based simulation model. Environmental Modelling & Software 101, pages 204-217.
Crossref
Crossref
Hua’an Wu, Bo Zeng & Meng Zhou. (2017) Forecasting the Water Demand in Chongqing, China Using a Grey Prediction Model and Recommendations for the Sustainable Development of Urban Water Consumption. International Journal of Environmental Research and Public Health 14:11, pages 1386.
Crossref
Crossref
Md Mahmudul Haque, Amaury de Souza & Ataur Rahman. (2016) Water Demand Modelling Using Independent Component Regression Technique. Water Resources Management 31:1, pages 299-312.
Crossref
Crossref