Evidence map›Paper›PMID 38008174›Full record

ArticleJournal of advanced research2024

Synergistic integration of digital twins and sustainable industrial internet of things for new generation energy investments.

Gang Kou, Hasan Dinçer, Serhat Yüksel, Muhammet Deveci

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PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of advanced research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Gang KouSchool of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China. Electronic address: kougang@swufe.edu.cn.
Hasan DinçerSchool of Business, Istanbul Medipol University, Istanbul, Turkey; University of Religions and Denominations, Qom, Iran; Clinic of Economics, Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str. 6, Baku, AZ1141, Azerbaijan. Electronic address: hdincer@medipol.edu.tr.
Serhat YükselSchool of Business, Istanbul Medipol University, Istanbul, Turkey; Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon; Clinic of Economics, Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str. 6, Baku, AZ1141, Azerbaijan. Electronic address: serhatyuksel@medipol.edu.tr.
Muhammet DeveciDepartment of Industrial Engineering, Turkish Naval Academy, National Defence University, 34940 Tuzla, Istanbul, Turkey; The Bartlett School of Sustainable Construction, University College London, 1-19 Torrington Place, London WC1E 7HB, UK; Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon. Electronic address: muhammetdeveci@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis study aims to identify optimal digital twin policies for enhancing renewable energy projects. Through a comprehensive analysis, the research evaluates the potential of digital twins in the renewable energy sector while considering triple bottom line perspectives.

objectivesThe study's main goal is to prioritize digital twin policies that can effectively boost renewable energy projects. The research aims to demonstrate the practical application and reliability of a proposed evaluation model.

methodsNine criteria, derived from literature review and triple bottom line viewpoints, are selected. Using the decision-making trial and evaluation laboratory (DEMATEL) methodology and Quantum picture fuzzy rough sets, criteria weights are determined. Quantum picture fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) evaluates sustainable industrial internet of things strategies in new-gen energy investments. VIsekriterijumska optimizcija i KOmpromisno Resenje (VIKOR) methodology enables a comparative assessment, and sensitivity analysis is conducted across nine cases.

resultsConsistent outcomes across various methods validate the model's reliability. Ecosystem preservation carries the highest weight (0.1147), followed by resource policy optimization with digital twins (0.1139). Distributed energy resilience ranks first (RCi 0.576), closely followed by energy efficiency optimization (RCi 0.542).

conclusionThis study underscores ecosystem preservation and efficient resource policies as pivotal for successful digital twin deployment in renewable energy projects. The findings highlight digital twins' potential contribution to environmental protection and ecosystem sustainability, emphasizing resource efficiency through their effective use.

Indexed as

Digital TwinsInvestment Decision, RenewablesPicture fuzzy rough numbersQuantum MechanicsSustainable industrial internet of thingsTriple Bottom Line

Identifiers

PMID38008174
PMCPMC11675074

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.