Title: A hybrid meta-heuristic algorithm with fuzzy clustering method for IoT smart electronic applications

Authors: Liejiang Huang; Sichao Chen; Dilong Shen; Yuanjun Pan; Jixing Yang; Yuanchao Hu

Addresses: Hangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou 310000, China ' Hangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou 310000, China ' Hangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou 310000, China ' Hangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou 310000, China ' Hangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou 310000, China ' School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China

Abstract: Nowadays, decision support systems and recommendation systems are emerging methodologies in the internet of things (IoT) environments for optimising smart electronic services such as smart tourist, smart logistics, smart transportation and smart home services. This paper proposes a smart recommendation system in the smart tourism application. Then, a content-based filtering method is proposed for improving search-based attributes in clustering. In addition, fuzzy C-means clustering is used to cluster the existing data in terms of the users' requests and recommend the optimised choice. Also, bat optimisation algorithm (BOA), which is a well-known meta-heuristic algorithm, is provided to improve the accuracy of the clustering to 98%, which is better than other state-of-the-art case studies. In addition, precision and recall are evaluated for predicting decision-making aspects in smart tourist applications. The results achieved are compared with those of the similar research studies and is superiority is shown.

Keywords: smart recommendation system; fuzzy logic; intelligent recommendation; internet of things; IoT; data mining; bat optimisation algorithm; BOA.

DOI: 10.1504/IJES.2023.134120

International Journal of Embedded Systems, 2023 Vol.16 No.1, pp.57 - 66

Received: 29 Oct 2022
Accepted: 13 Mar 2023
Published online: 11 Oct 2023 *

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