Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Reference31 articles.
1. Abebe Y, Kabir G, Tesfamariam S (2018) Assessing urban areas vulnerability to pluvial flooding using GIS applications and Bayesian Belief Network model. Journal of Cleaner Production 174:1629–1641
2. Adamowski J, Fung Chan H, Prasher SO, Ozga-Zielinski B, Sliusarieva A (2012) Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal. Canada. Water Resources Research 48:1
3. Al-Zahrani MA, Abo-Monasar A (2015) Urban Residential Water Demand Prediction Based on Artificial Neural Networks and Time Series Models. Water Resources Management 29(10):3651–3662
4. Anbari MJ, Tabesh M, Roozbahani A (2017) Risk assessment model to prioritize sewer pipes inspection in wastewater collection networks. Journal of environmental management 190:91–101
5. Azadeh A, Neshat N, Hamidipour H (2011) Hybrid fuzzy regression–artificial neural network for improvement of short-term water consumption estimation and forecasting in uncertain and complex environments: Case of a large metropolitan city. Journal of Water Resources Planning and Management 138(1):71–75
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