Journal of Water Resource and Protection

Vol.9 No.2(2017), Paper ID 74103, 22 pages

DOI:10.4236/jwarp.2017.92014

 

Adaptive Surrogate Model Based Optimization (ASMBO) for Unknown Groundwater Contaminant Source Characterizations Using Self-Organizing Maps

 

Shahrbanoo Hazrati-Yadkoori, Bithin Datta

 

Discipline of Civil Engineering, College of Science and Engineering, James Cook University, Townsville, Australia
CRC for Contamination Assessment and Remediation of the Environment, CRC CARE, University of Newcastle, Callaghan, Australia

 

Copyright © 2017 Shahrbanoo Hazrati-Yadkoori, Bithin Datta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

 

How to Cite this Article


Hazrati-Yadkoori, S. and Datta, B. (2017) Adaptive Surrogate Model Based Optimization (ASMBO) for Unknown Groundwater Contaminant Source Characterizations Using Self-Organizing Maps. Journal of Water Resource and Protection, 9, 193-214. doi: 10.4236/jwarp.2017.92014.

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