TY - JOUR
T1 - Optimal and objective placement of sensors in water distribution systems using information theory
AU - Khorshidi, Mohammad S.
AU - Nikoo, Mohammad Reza
AU - Sadegh, Mojtaba
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/10/15
Y1 - 2018/10/15
N2 - Optimization-based deployment of contamination warning system in water distribution systems has been widely used in the literature, due to their superior performance compared to rule- and opinion-based approaches. However, optimization techniques impose an excessive computational burden, which in turn is compensated for by shrinking the problem's decision space and/or using faster optimization algorithms with less accuracy. This imposes subjectivity in interpretation of the system and associated risks, and undermines model's accuracy by not exploring the entire feasible space. We propose a framework that uses information theoretic techniques, including value of information and transinformation entropy, for optimal sensor placement. This can be used either as pre-selection, i.e. pinpointing best potential locations of sensors to be in turn used in optimization framework, or ultimate selection, i.e. single-handedly selecting sensor locations from the feasible space. The proposed framework is then applied to Lamerd water distribution system, in Fars province, Iran, and the results are compared to the suggested potential locations of sensors in previous studies and results of TEVA-SPOT model. The proposed information theoretic scheme enhances the decision space, provides more accurate results, significantly reduces the computational burden, and warrants objective selection of sensor placement.
AB - Optimization-based deployment of contamination warning system in water distribution systems has been widely used in the literature, due to their superior performance compared to rule- and opinion-based approaches. However, optimization techniques impose an excessive computational burden, which in turn is compensated for by shrinking the problem's decision space and/or using faster optimization algorithms with less accuracy. This imposes subjectivity in interpretation of the system and associated risks, and undermines model's accuracy by not exploring the entire feasible space. We propose a framework that uses information theoretic techniques, including value of information and transinformation entropy, for optimal sensor placement. This can be used either as pre-selection, i.e. pinpointing best potential locations of sensors to be in turn used in optimization framework, or ultimate selection, i.e. single-handedly selecting sensor locations from the feasible space. The proposed framework is then applied to Lamerd water distribution system, in Fars province, Iran, and the results are compared to the suggested potential locations of sensors in previous studies and results of TEVA-SPOT model. The proposed information theoretic scheme enhances the decision space, provides more accurate results, significantly reduces the computational burden, and warrants objective selection of sensor placement.
KW - Contamination warning system
KW - Sensor placement
KW - Transinformation entropy
KW - Value of information
KW - Water distribution system
UR - http://www.scopus.com/inward/record.url?scp=85049062103&partnerID=8YFLogxK
U2 - 10.1016/j.watres.2018.06.050
DO - 10.1016/j.watres.2018.06.050
M3 - Article
C2 - 29960176
AN - SCOPUS:85049062103
SN - 0043-1354
VL - 143
SP - 218
EP - 228
JO - Water Research
JF - Water Research
ER -