Medium-Term Urban Water Demand Forecasting with Limited Data Using an Ensemble Wavelet–Bootstrap Machine-Learning Approach-Reference-Cited by-同舟云学术

Medium-Term Urban Water Demand Forecasting with Limited Data Using an Ensemble Wavelet–Bootstrap Machine-Learning Approach

Published:2015-02 Issue:2 Volume:141 Page:04014053
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Tiwari Mukesh K.¹,Adamowski Jan F.²

Affiliation:

1. Assistant Professor, Dept. of Soil and Water Engineering, College of Agricultural Engineering and Technology, Anand Agricultural Univ., Godhra, Gujarat 389001, India.

2. Assistant Professor, Dept. of Bioresource Engineering, McGill Univ., Quebec, Canada H9X 3V9 (corresponding author).

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%29WR.1943-5452.0000454

Reference56 articles.

1. Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting

2. Peak Daily Water Demand Forecast Modeling Using Artificial Neural Networks

3. A Spectral Analysis Based Methodology to Detect Climatological Influences on Daily Urban Water Demand

4. A wavelet neural network conjunction model for groundwater level forecasting

5. 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

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