Cognitive Computational Model Using Machine Learning Algorithm in Artificial Intelligence Environment

dc.contributor.author Liu, Shangyi
dc.contributor.author Spiridonidis, Constantin-Viktor
dc.contributor.author Abdulrazzqa, Mohammed
dc.date.accessioned 2022-02-14T16:10:55Z
dc.date.available 2022-02-14T16:10:55Z
dc.date.copyright © 2021
dc.date.issued 2022
dc.description This article is not available at CUD collection. The version of scholarly record of this article is published in Applied Mathematics and Nonlinear Sciences (2022), available online at: https://doi.org/10.2478/amns.2021.2.00112 en_US
dc.description.abstract In order to explore the application of machine learning algorithm to intelligent analysis of big data in an artificial intelligence (AI) environment, make cognitive computing meet the requirements of AI and better assist humans to carry out data analysis, first, the theoretical basis of machine learning algorithm is elaborated. Then, a cognitive computational model based on the machine learning algorithm is proposed, including the essence, principle, function, training method of deep belief network (DBN) algorithm, as well as the joint use of DBN algorithm and multilayer perceptron. Finally, the proposed algorithm is simulated. The results show that under the same parameter conditions, the accuracy rate of the DBN algorithm combined with multilayer perceptron is higher than that of the DBN algorithm; when the number of units is >40, the accuracy rate of the DBN algorithm combined with multilayer perceptron is significantly higher than that of the DBN algorithm; when the number of units is 30, the best effect can be obtained, and the error rate is <0.05, but the DBN algorithm cannot achieve this effect alone; when the number of network layers is specified as four, the error rate of the DBN algorithm combined with multilayer perceptron is <0.05, forming the optimal level. In the AI environment, the performance of the cognitive computational model based on the DBN algorithm and multilayer perceptron can reach the highest level, which makes the computer become a handy intelligent auxiliary tool for human beings. © 2021 Liu et al., published by Sciendo. en_US
dc.identifier.citation Liu, S., Spiridonidis, C. -., & Abdulrazzqa, M. (2022). Cognitive computational model using machine learning algorithm in artificial intelligence environment. Applied Mathematics and Nonlinear Sciences, https://doi.org/10.2478/amns.2021.2.00112 en_US
dc.identifier.issn 24448656
dc.identifier.uri https://doi.org/10.2478/amns.2021.2.00112
dc.identifier.uri http://hdl.handle.net/20.500.12519/511
dc.language.iso en en_US
dc.publisher Sciendo en_US
dc.relation Authors Affiliations : Liu, S., University of Science and Technology Liaoning, Anshan, 114051, China; Spiridonidis, C.-V., Department of Architecture, Faculty of Architecture and Interior Design, Canadian University Dubai, Dubai, United Arab Emirates; Abdulrazzqa, M., Department of Business Administration, Faculty of Administration Sciences, Applied Science University, Al Eker, Bahrain
dc.relation.ispartofseries Applied Mathematics and Nonlinear Sciences;
dc.rights Creative Commons Attribution 4.0 International License.
dc.rights.holder Copyright : © 2021 Liu et al., published by Sciendo.
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject 92B20 en_US
dc.subject artificial intelligence en_US
dc.subject cognitive computational model en_US
dc.subject DBN algorithm en_US
dc.subject machine learning en_US
dc.subject multilayer perceptron en_US
dc.title Cognitive Computational Model Using Machine Learning Algorithm in Artificial Intelligence Environment en_US
dc.type Article en_US
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