Machine Learning for Modeling Water Demand
Author:
Affiliation:
1. Dept. of Human Geography, Univ. of Seville, Seville 41004, Spain (corresponding author).
2. Physical Geography and Regional Geographic Analysis, Univ. of Seville, Seville 41004, Spain.
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.1943-5452.0001067
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