Large metropolitan water demand forecasting using DAN2, FTDNN, and KNN models: A case study of the city of Tehran, Iran
Author:
Affiliation:
1. Information Systems Department, Santa Clara University, Santa Clara, California, USA
2. Civil Engineering Department, Sharif University of Technology, Tehran, Iran
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/1573062X.2016.1223858
Reference8 articles.
1. Billings, R.B. and Jones, C.V., 2008. Forecasting Urban Water Demand, 2nd ed. American Water Works Association, Denver, Co. chapter 14, 299–308.
2. Urban Water Demand Forecasting: Review of Methods and Models
3. Evaluation of Artificial Neural Network Techniques for Municipal Water Consumption Modeling
4. A dynamic artificial neural network model for forecasting time series events
5. Urban Water Demand Forecasting with a Dynamic Artificial Neural Network Model
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