Di-ANFIS: an integrated blockchain–IoT–big data-enabled
framework for evaluating service supply chain performance

J 2021

Di-ANFIS: an integrated blockchain–IoT–big data-enabled framework for evaluating service supply chain performance

BAMAKAN, Seyed Mojtaba Hosseini, Najmeh FAREGH and Ahad ZARERAVASAN

Basic information

Original name

Di-ANFIS: an integrated blockchain–IoT–big data-enabled framework for evaluating service supply chain performance

Authors

BAMAKAN, Seyed Mojtaba Hosseini (364 Islamic Republic of Iran), Najmeh FAREGH (364 Islamic Republic of Iran) and Ahad ZARERAVASAN (364 Islamic Republic of Iran, guarantor, belonging to the institution)

Edition

Journal of Computational Design and Engineering, Netherlands, University of Oxford, 2021, 2288-5048

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 6.167

RIV identification code

RIV/00216224:14560/21:00121669

Organization unit

Faculty of Economics and Administration

DOI

http://dx.doi.org/10.1093/jcde/qwab007

UT WoS

000646113800013

Keywords in English

blockchain; industry 4.0; Internet of Things (IoT); big data; service supply chain; performance evaluation

Abstract

V originále

Service supply chain management is a complex process because of its intangibility, high diversity of services, trustless settings, and uncertain conditions. However, the traditional evaluating models mostly consider the historical performance data and fail to predict and diagnose the problems’ root. This paper proposes a distributed, trustworthy, tamper-proof, and learning framework for evaluating service supply chain performance based on Blockchain and Adaptive Network-based Fuzzy Inference Systems (ANFIS) techniques, named Di-ANFIS. The main objectives of this research are: 1) presenting hierarchical criteria of service supply chain performance to cope with the diagnosis of the problems’ root; 2) proposing a smart learning model to deal with the uncertainty conditions by a combination of neural network and fuzzy logic, 3) and introducing a distributed Blockchain-based framework due to the dependence of ANFIS on big data and the lack of trust and security in the supply chain. Furthermore, the proposed six-layer conceptual framework consists of the data layer, connection layer, Blockchain layer, smart layer, ANFIS layer, and application layer. This architecture creates a performance management system using the Internet of Things (IoT), smart contracts, and ANFIS based on the Blockchain platform. The Di-ANFIS model provides a performance evaluation system without needing a third party and a reliable intermediary that provides an agile and diagnostic model in a smart and learning process. It also saves computing time and speeds up information flow.

Links

EF16_027/0008360, research and development project

Name: Postdoc@MUNI

Files attached

Di-ANFIS.pdf

Find similar documents

Citovat

BAMAKAN, Seyed Mojtaba Hosseini, Najmeh FAREGH and Ahad ZARERAVASAN. Di-ANFIS: an integrated blockchain–IoT–big data-enabled framework for evaluating service supply chain performance. Journal of Computational Design and Engineering. Netherlands: University of Oxford, 2021, vol. 8, No 2, p. 676-690. ISSN 2288-5048. Available from: https://dx.doi.org/10.1093/jcde/qwab007.

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   article_location = {Netherlands},
   article_number = {2},
   doi = {http://dx.doi.org/10.1093/jcde/qwab007},
   keywords = {blockchain; industry 4.0; Internet of Things (IoT); big data; service supply chain; performance evaluation},
   language = {eng},
   issn = {2288-5048},
   journal = {Journal of Computational Design and Engineering},
   title = {Di-ANFIS: an integrated blockchain–IoT–big data-enabled framework for evaluating service supply chain performance},
   url = {https://academic.oup.com/jcde/article/8/2/676/6141474?login=true},
   volume = {8},
   year = {2021}
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AU  - Bamakan, Seyed Mojtaba Hosseini - Faregh, Najmeh - Zareravasan, Ahad
PY  - 2021
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JF  - Journal of Computational Design and Engineering
VL  - 8
IS  - 2
SP  - 676-690
EP  - 676-690
PB  - University of Oxford
SN  - 22885048
KW  - blockchain
KW  - industry 4.0
KW  - Internet of Things (IoT)
KW  - big data
KW  - service supply chain
KW  - performance evaluation
UR  - https://academic.oup.com/jcde/article/8/2/676/6141474?login=true
N2  - Service supply chain management is a complex process because of its intangibility, high diversity of services, trustless settings, and uncertain conditions. However, the traditional evaluating models mostly consider the historical performance data and fail to predict and diagnose the problems’ root. This paper proposes a distributed, trustworthy, tamper-proof, and learning framework for evaluating service supply chain performance based on Blockchain and Adaptive Network-based Fuzzy Inference Systems (ANFIS) techniques, named Di-ANFIS. The main objectives of this research are: 1) presenting hierarchical criteria of service supply chain performance to cope with the diagnosis of the problems’ root; 2) proposing a smart learning model to deal with the uncertainty conditions by a combination of neural network and fuzzy logic, 3) and introducing a distributed Blockchain-based framework due to the dependence of ANFIS on big data and the lack of trust and security in the supply chain. Furthermore, the proposed six-layer conceptual framework consists of the data layer, connection layer, Blockchain layer, smart layer, ANFIS layer, and application layer. This architecture creates a performance management system using the Internet of Things (IoT), smart contracts, and ANFIS based on the Blockchain platform. The Di-ANFIS model provides a performance evaluation system without needing a third party and a reliable intermediary that provides an agile and diagnostic model in a smart and learning process. It also saves computing time and speeds up information flow.
ER  -

BAMAKAN, Seyed Mojtaba Hosseini, Najmeh FAREGH and Ahad ZARERAVASAN. Di-ANFIS: an integrated blockchain–IoT–big data-enabled framework for evaluating service supply chain performance. \textit{Journal of Computational Design and Engineering}. Netherlands: University of Oxford, 2021, vol.~8, No~2, p.~676-690. ISSN~2288-5048. Available from: https://dx.doi.org/10.1093/jcde/qwab007.

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