Staff View: Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

Electric power production data has the characteristics of massive data scale, high update frequency and fast growth rate. It is significant to process and analyse electric power production data to diagnose a fault. High levels of informa-tionalisation and intellectualization can be achieved in the a...

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Main Authors:	Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.
Other Authors:	58701334000
Format:	Article
Published:	Frontier Scientific Publishing 2024
Subjects:	Artificial Intelligent Algorithms Big Data Cloud Computing Power Systems Smart Grid
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id	my.uniten.dspace-34465
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spelling	my.uniten.dspace-344652024-10-14T11:19:58Z Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment Al-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S. 58701334000 14030355800 55057479600 58765817900 58168727000 Artificial Intelligent Algorithms Big Data Cloud Computing Power Systems Smart Grid Electric power production data has the characteristics of massive data scale, high update frequency and fast growth rate. It is significant to process and analyse electric power production data to diagnose a fault. High levels of informa-tionalisation and intellectualization can be achieved in the actual details of developing a Power Plant Fault Diagnosis Management System. Furthermore, cloud computing technology and association rule mining as the core technology based on analysis of domestic and foreign research. In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. Hadoop distributed architecture is used to design and implement the power private cloud computing cluster. The functions of private cloud computing clusters for power extensive data management and analysis are realised through MapReduce computing framework and Hbase database. The leakage fault cases verify the algorithm�s applicability and complete the correlation diagnosis of water wall leakage fault. Through analysing the functional requirements of the system in the project, using MySQL database and Enhancer platform, the intelligent fault diagnosis management system of cloud computing power plant is designed and developed, which realises the functions of system modules such as system authority management, electronic equipment account, technical supervision, expert database, data centre. The result shows that the proposed method improves the security problem of the system, the message-digest algorithm (MD5) is used to encrypt the user password, and a strict role authorisation system is designed to realise the access and manage the system�s security. � 2023 by author(s). Journal of Autonomous Intelligence is published by Frontier Scientific Publishing. Final 2024-10-14T03:19:58Z 2024-10-14T03:19:58Z 2023 Article 10.32629/jai.v6i1.640 2-s2.0-85175471600 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175471600&doi=10.32629%2fjai.v6i1.640&partnerID=40&md5=d9c3533f78ddb88331236ecaed878229 https://irepository.uniten.edu.my/handle/123456789/34465 6 1 All Open Access Gold Open Access Frontier Scientific Publishing Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Artificial Intelligent Algorithms Big Data Cloud Computing Power Systems Smart Grid
spellingShingle	Artificial Intelligent Algorithms Big Data Cloud Computing Power Systems Smart Grid Al-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S. Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
description	Electric power production data has the characteristics of massive data scale, high update frequency and fast growth rate. It is significant to process and analyse electric power production data to diagnose a fault. High levels of informa-tionalisation and intellectualization can be achieved in the actual details of developing a Power Plant Fault Diagnosis Management System. Furthermore, cloud computing technology and association rule mining as the core technology based on analysis of domestic and foreign research. In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. Hadoop distributed architecture is used to design and implement the power private cloud computing cluster. The functions of private cloud computing clusters for power extensive data management and analysis are realised through MapReduce computing framework and Hbase database. The leakage fault cases verify the algorithm�s applicability and complete the correlation diagnosis of water wall leakage fault. Through analysing the functional requirements of the system in the project, using MySQL database and Enhancer platform, the intelligent fault diagnosis management system of cloud computing power plant is designed and developed, which realises the functions of system modules such as system authority management, electronic equipment account, technical supervision, expert database, data centre. The result shows that the proposed method improves the security problem of the system, the message-digest algorithm (MD5) is used to encrypt the user password, and a strict role authorisation system is designed to realise the access and manage the system�s security. � 2023 by author(s). Journal of Autonomous Intelligence is published by Frontier Scientific Publishing.
author2	58701334000
author_facet	58701334000 Al-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S.
format	Article
author	Al-Jumaili A.H.A. Muniyandi R.C. Hasan M.K. Singh M.J. Paw J.K.S.
author_sort	Al-Jumaili A.H.A.
title	Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_short	Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_full	Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_fullStr	Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_full_unstemmed	Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
title_sort	intelligent transmission line fault diagnosis using the apriori associated rule algorithm under cloud computing environment
publisher	Frontier Scientific Publishing
publishDate	2024
_version_	1814061181458972672
score	13.222552

Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment

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