Water characterization and early contamination detection in highly varying stochastic background water, based on Machine Learning methodology for processing real-time UV-Spectrophotometry-Reference-Cited by-同舟云学术

Water characterization and early contamination detection in highly varying stochastic background water, based on Machine Learning methodology for processing real-time UV-Spectrophotometry

Published:2019-05 Issue: Volume:155 Page:333-342
ISSN:0043-1354
Container-title:Water Research
language:en
Short-container-title:Water Research

Author:

Asheri Arnon Tehila,Ezra Shai,Fishbain Barak^ORCID

Funder

Mekorot

Israel's national water company

WaTech division; Real-Tech Inc., Whitby, Ontario Canada

Canada-Israel Industrial Research and Development Foundation

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Water Science and Technology,Ecological Modeling,Environmental Engineering,Civil and Structural Engineering

Reference24 articles.

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2. A Coupled Decision Trees Bayesian Approach for Water Distribution Systems Event Detection;Arad,2012

3. Contamination detection of water with varying routine backgrounds by UV-spectrophotometry;Asheri-Arnon;J. Water Resour. Plann. Manag.,2018

4. Sparse and Redundant Representations from Theory to Applications in Signal and Image Processing;Elad,2010

5. Spectral methods for the analysis of bacteria in water wells;Frolich;Sci. Rep.,2017

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