Please use this identifier to cite or link to this item: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/27931
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dc.contributor.authorAbubakar, Ibrahim-
dc.contributor.authorAbdullahi, Ibrahim Mohammed-
dc.contributor.authorBalami, Ayuba-
dc.contributor.authorIdah, PA-
dc.contributor.authorOlaniyi, Olayemi Mikail-
dc.date.accessioned2024-05-05T17:38:19Z-
dc.date.available2024-05-05T17:38:19Z-
dc.date.issued2024-04-
dc.identifier.citation1. Abubakar, I, Abdullahi, I. M, Balami, A. A, Idah, P. A, Olaniyi, O. M. (2024). An In-depth Review of Fuzzy Logic Technique for Engineering Applications. In Proceedings of the International Computing and Communication Conference (I3C 2024), pp 1-8. Federal University of Technology, Minna. https://i3c.futminna.edu.ng/en_US
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/27931-
dc.description.abstractFuzzy logic entails information of an unpredicted as opposed to Boolean logic. It is classed as an artificial intelligence technique to model and replace process control and designer/operator expertise. It offers competitive advantage over other methods in the industrial firms seeking technical-economic optimization. It is important to mention that, fuzzy logic does not necessarily replace the conventional control systems, rather it completes such systems. This study aimed at review of the most common fuzzy logic systems and their applications. The review was conducted through identification of current research in industry, agriculture and optimization of processes. Twenty five (25) papers were reviewed on four main areas: industrial application, agronomic application, crop husbandry application and optimization of process control systems. It was found out that fuzzy logic works best as effective feedback system in control systems. It is therefore, recommended for agricultural mechanization.en_US
dc.language.isoenen_US
dc.publisherInternational Computing and Communication Conference, Federal University of Technology, Minnaen_US
dc.relation.ispartofseries1st;-
dc.subjectNeural network,en_US
dc.subjectoptimization,en_US
dc.subjectautomation,en_US
dc.subjectMicrocontroller,en_US
dc.subjectfuzzy logicen_US
dc.titleAn In-depth Review of Fuzzy Logic Technique for Engineering Applicationsen_US
dc.typeArticleen_US
Appears in Collections:Computer Engineering

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