Genetic case-based reasoning for improved mobile phone faults diagnosis

Mohammed, Mazin Abed and Abd Ghani, Mohd Khanapi and Arunkumar, N. and Obaid, Omar Ibrahim and A. Mostafa, Salama and Musa Jaber, Mustafa and Burhanuddin, M.A. and Mohammed Matar, Bilal and Abdullatif, Saif Khalid and Ahmed Ibrahim, Dheyaa (2018) Genetic case-based reasoning for improved mobile phone faults diagnosis. COMPUTERS & ELECTRICAL ENGINEERING, 71. pp. 212-222. ISSN 0045-7906

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Different types of fault diagnostic applications that utilize case-based reasoning (CBR) are applied in the diagnosis process. However, CBR cannot provide solutions to unanticipated or unknown problems. Therefore, further investigation of the retrieval and revision mechanisms of CBR is essential in improving the diagnosis accuracy and precision of the method. This study proposes a hybrid scheme that combines the genetic algorithm and CBR (GCBR) to improve CBR diagnosis. CBR applies experience and knowledge on existing cases of fault diagnosis to newly provided cases. The genetic algorithm aggregates and revises relevant cases to provide solutions to unknown cases. GCBR is implemented in a mobile phone fault diagnosis application. This domain is a good testing environment because mobile phones are of various types and models. Test results show that GCBR can detect several mobile phone faults with average accuracy 98.7%.

Item Type: Article
Uncontrolled Keywords: Mobile phone fault diagnosis; Genetic algorithm; Case-based reasoning; Hybrid fault diagnosis
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
T Technology > T Technology (General) > T11.95-12.5 Industrial directories > T58.6-58.62 Management information systems
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: UiTM Student Praktikal
Date Deposited: 06 Jan 2022 02:34
Last Modified: 06 Jan 2022 02:34

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