Improving Efficiency of the Bayesian Approach to Water Distribution Contaminant Source Characterization with Support Vector Regression-Reference-Cited by-同舟云学术

Improving Efficiency of the Bayesian Approach to Water Distribution Contaminant Source Characterization with Support Vector Regression

Published:2014-01 Issue:1 Volume:140 Page:3-11
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Wang Hui¹,Harrison Kenneth W.²

Affiliation:

1. Bureau of Economic Geology, Univ. of Texas, Austin, TX 78758-4445 (corresponding author).

2. Earth System Science Interdisciplinary Center, College Park, MD 20740-3823; and Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771.

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.1943-5452.0000323

Reference35 articles.

1. Simulating Nonresidential Water Demand with a Stochastic End-Use Model

2. Simulating Residential Water Demand with a Stochastic End-Use Model

3. Bayesian Methods for Data Analysis

4. Chang C.-C. and Lin C.-J. (2001). “LIBSVM: A library for support vector machines.” 〈http://www.csie.ntu.edu.tw/∼cjlin/libsvm〉 (Oct. 9 2013).

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