Optimal placement of water quality monitoring stations in sewer systems: An information theory approach

B. K. Banik; L. Alfonso; A. S. Torres; A. Mynett; C. Di Cristo; A. Leopardi

doi:10.1016/j.proeng.2015.08.956

Optimal placement of water quality monitoring stations in sewer systems: An information theory approach

B. K. Banik^*, L. Alfonso, A. S. Torres, A. Mynett, C. Di Cristo, A. Leopardi

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Scientific › peer-review

22 Citations (Scopus)

Abstract

A core problem associated with the water quality monitoring in the sewer system is the optimal placement of a limited number of monitoring sites. A methodology is provided for optimally design water quality monitoring stations in sewer networks. The methodology is based on information theory, formulated as a multi-objective optimization problem and solved using NSGA-II. Computer code is written to estimate two entropy quantities, namely Joint Entropy, a measure of information content, and Total Correlation, a measure of redundancy, which are maximized and minimized, respectively. The test on a real sewer network suggests the effectiveness of the proposed methodology.

Original language	English
Pages (from-to)	1308-1317
Number of pages	10
Journal	Procedia Engineering
Volume	119
Issue number	1
DOIs	https://doi.org/10.1016/j.proeng.2015.08.956
Publication status	Published - 2015
Externally published	Yes
Event	13th Computer Control for Water Industry Conference - Hugh Aston Building, De Montfort University , Leicester, United Kingdom Duration: 2 Sept 2015 → 4 Sept 2015 Conference number: 13

Keywords

Entropy
Information theory
Monitoring stations
NSGA-II
Optimization
Sewer systems

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10.1016/j.proeng.2015.08.956

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title = "Optimal placement of water quality monitoring stations in sewer systems: An information theory approach",

abstract = "A core problem associated with the water quality monitoring in the sewer system is the optimal placement of a limited number of monitoring sites. A methodology is provided for optimally design water quality monitoring stations in sewer networks. The methodology is based on information theory, formulated as a multi-objective optimization problem and solved using NSGA-II. Computer code is written to estimate two entropy quantities, namely Joint Entropy, a measure of information content, and Total Correlation, a measure of redundancy, which are maximized and minimized, respectively. The test on a real sewer network suggests the effectiveness of the proposed methodology.",

keywords = "Entropy, Information theory, Monitoring stations, NSGA-II, Optimization, Sewer systems",

author = "Banik, {B. K.} and L. Alfonso and Torres, {A. S.} and A. Mynett and {Di Cristo}, C. and A. Leopardi",

year = "2015",

doi = "10.1016/j.proeng.2015.08.956",

language = "English",

volume = "119",

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journal = "Procedia Engineering",

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note = "13th Computer Control for Water Industry Conference, CCWI 2015 ; Conference date: 02-09-2015 Through 04-09-2015",

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T1 - Optimal placement of water quality monitoring stations in sewer systems

T2 - 13th Computer Control for Water Industry Conference

AU - Banik, B. K.

AU - Alfonso, L.

AU - Torres, A. S.

AU - Mynett, A.

AU - Di Cristo, C.

AU - Leopardi, A.

N1 - Conference code: 13

PY - 2015

Y1 - 2015

N2 - A core problem associated with the water quality monitoring in the sewer system is the optimal placement of a limited number of monitoring sites. A methodology is provided for optimally design water quality monitoring stations in sewer networks. The methodology is based on information theory, formulated as a multi-objective optimization problem and solved using NSGA-II. Computer code is written to estimate two entropy quantities, namely Joint Entropy, a measure of information content, and Total Correlation, a measure of redundancy, which are maximized and minimized, respectively. The test on a real sewer network suggests the effectiveness of the proposed methodology.

AB - A core problem associated with the water quality monitoring in the sewer system is the optimal placement of a limited number of monitoring sites. A methodology is provided for optimally design water quality monitoring stations in sewer networks. The methodology is based on information theory, formulated as a multi-objective optimization problem and solved using NSGA-II. Computer code is written to estimate two entropy quantities, namely Joint Entropy, a measure of information content, and Total Correlation, a measure of redundancy, which are maximized and minimized, respectively. The test on a real sewer network suggests the effectiveness of the proposed methodology.

KW - Entropy

KW - Information theory

KW - Monitoring stations

KW - NSGA-II

KW - Optimization

KW - Sewer systems

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DO - 10.1016/j.proeng.2015.08.956

M3 - Conference article

AN - SCOPUS:84941077779

SN - 1877-7058

VL - 119

SP - 1308

EP - 1317

JO - Procedia Engineering

JF - Procedia Engineering

IS - 1

Y2 - 2 September 2015 through 4 September 2015

ER -

Optimal placement of water quality monitoring stations in sewer systems: An information theory approach

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Keywords

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