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Intelligent Decision Support System for Lowering the Costs of Service Calls for Smart Meters.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Intelligent Decision Support System for Lowering the Costs of Service Calls for Smart Meters./
Author:	Siryani, Joseph.
Description:	1 online resource (124 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
Contained By:	Dissertation Abstracts International79-03B(E).
Subject:	Engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9780355470857

Intelligent Decision Support System for Lowering the Costs of Service Calls for Smart Meters.
Siryani, Joseph.

Intelligent Decision Support System for Lowering the Costs of Service Calls for Smart Meters. - 1 online resource (124 pages)

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.

Thesis (Ph.D.)--The George Washington University, 2018.

Includes bibliographical references

The operations and maintenance (O&M) of the electric smart meter (ESM) systems constitute the most expensive systems engineering lifecycle phase, where resources drive costs up. Customer service calls activities are one of the cost items that are directly linked to the success of smart meter operations. As the number of field visits required to customer sites increases and the quality of meter reading decreases, the effect on volume of calls to customer care center will increase and overall customer satisfaction will most likely decrease.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355470857Subjects--Topical Terms:

561152
Engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Intelligent Decision Support System for Lowering the Costs of Service Calls for Smart Meters.
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100 1 $a Siryani, Joseph. $3 1190673
245 1 0 $a Intelligent Decision Support System for Lowering the Costs of Service Calls for Smart Meters.
264 0 $c 2018
300 $a 1 online resource (124 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
500 $a Advisers: Bereket Tanju; Timothy Eveleigh.
502 $a Thesis (Ph.D.)--The George Washington University, 2018.
504 $a Includes bibliographical references
520 $a The operations and maintenance (O&M) of the electric smart meter (ESM) systems constitute the most expensive systems engineering lifecycle phase, where resources drive costs up. Customer service calls activities are one of the cost items that are directly linked to the success of smart meter operations. As the number of field visits required to customer sites increases and the quality of meter reading decreases, the effect on volume of calls to customer care center will increase and overall customer satisfaction will most likely decrease.
520 $a This research focuses on introducing an intelligent decision-support system (iDSS) for lowering the costs of service calls for ESM systems. The iDSS is a novel approach that leverages advanced analytics of ESM network communication-quality data, to improve predictions for smart meter field operations, and provides actionable decision recommendations regarding whether to send a technician to a customer location to resolve an ESM issue. The predictive model is empirically evaluated using datasets from a commercial ESM network. The efficiency and accuracy of the approach are demonstrated using various machine learning classifiers. The research results will demonstrate, that this approach generates statistically noteworthy estimations, and improves the cost efficiency of ESM network O&M, implying significant contributions to the fields of systems engineering O&M cost optimization, and the applications of ESM machine learning and advanced analytics.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Engineering. $3 561152
650 4 $a Artificial intelligence. $3 559380
650 4 $a Operations research. $3 573517
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The George Washington University. $b Systems Engineering. $3 1148622
773 0 $t Dissertation Abstracts International $g 79-03B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10640838 $z click for full text (PQDT)