Urban Water Demand Forecasting with a Dynamic Artificial Neural Network Model
Author:
Affiliation:
1. Professor, Information Systems, Santa Clara Univ., Santa Clara, CA 95053.
2. Research Assistant, Santa Clara Univ., Santa Clara, CA 95053.
3. Data Mining Consultant, San Diego, CA 92128.
Publisher
American Society of Civil Engineers (ASCE)
Subject
Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering
Link
http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-9496%282008%29134%3A2%28138%29
Reference23 articles.
1. Short-Term Forecasting for Urban Water Consumption
2. State-Space versus Multiple Regression for Forecasting Urban Water Demand
3. A dynamic architecture for artificial neural networks
4. A dynamic artificial neural network model for forecasting time series events
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