Classication and Regression Framework for Characterizing Contaminant Source Zone.

Zhang, Hao.
2017-04-20T14:00:58.209Z

Abstract: In this thesis we develop two machine-learning frameworks for estimating quantitative metrics characterizing subsurface zones of chemically contaminated soil focusing on problems involving Dense Non-Aqueous Phase Liquid (DNAPL). Source zone characterization, a necessary first step in the development of the remediation strategy, is challenging due to practical constraints associated with ... read more

Subjects
Tufts University. Department of Electrical and Computer Engineering.
Permanent URL
http://hdl.handle.net/10427/012100
ID: tufts:21577
To Cite: DCA Citation Guide