Information Technologies and Electronics: Volume 3

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 1388

Special Issue Editor


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Guest Editor
Department of Complex Information Security of Computer Systems, University of Control Systems and Radioelectronics, Lenin Ave, 40, Tomskaya Oblast, 634050 Tomsk, Russia
Interests: theory and practice of complex information security systems; information security, mathematical modeling of difficult systems; algorithms of processing of big data
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Special Issue Information

Dear Colleagues,

This Special Issue is intended as a natural extension of the previous Special Issues, entitled, "Information Technologies and Electronics", and "Information Technologies and Electronics Ⅱ" , aims to highlight recent advances in:

  • mathematical modeling in control systems;
  • information security;
  • the Internet of Things (IoT);
  • robotics;
  • big data;
  • machine learning;
  • artificial intelligence;
  • automated systems for data processing and control;
  • telecommunications;
  • next-generation communication and telecommunication systems;
  • electronics;
  • and other areas of interest associated with Information Technologies and Electronics.

We welcome articles that present good mathematical or experimental outcomes and a strong substantiation of conclusions and results, and analytical reviews of relevant scientific topics. Submissions are expected to contain original content and have clear scientific novelty. 

Prof. Dr. Alexander Shelupanov
Guest Editor

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Published Papers (1 paper)

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Research

34 pages, 10825 KiB  
Article
POI Route Recommendation Model Based on Symmetrical Naive Bayes Classification Spatial Accessibility and Improved Cockroach Swarm Optimization Algorithm
by Xiao Zhou, Zheng Zhang, Xinjian Liang and Mingzhan Su
Symmetry 2024, 16(4), 424; https://doi.org/10.3390/sym16040424 - 3 Apr 2024
Cited by 1 | Viewed by 846
Abstract
The commonly used POI route recommendation methods usually ignore the effects of tourists’ interests and transportation geographical conditions, and so may not output the optimal results. To solve the problems, we propose a POI route recommendation model based on symmetrical Naive Bayes classification [...] Read more.
The commonly used POI route recommendation methods usually ignore the effects of tourists’ interests and transportation geographical conditions, and so may not output the optimal results. To solve the problems, we propose a POI route recommendation model based on symmetrical Naive Bayes classification spatial accessibility (NBCSA) and an improved cockroach swarm optimization algorithm (ICSOA), aiming to recommend POI routes that satisfy tourists’ interests and have the lowest travel costs under tourism transportation geographical conditions. Using the historical POIs visited by tourists as the training set, we construct an improved symmetrical Naive Bayes classification algorithm (NBCA), and the POIs in the destination city are divided into categories by tourists’ preferences. Then we propose an improved NBCSA model to calculate the spatial accessibility field strength (SAFS) for each category’s POIs. Based on the recommended POIs, we propose the ICSOA to recommend optimal POI routes. The experiment verifies that the proposed algorithm can effectively classify the POIs and recommend POIs that best match the tourists’ interests and produce the lowest travel costs. Compared with the TCA and GDA method, the proposed algorithm can output the POI routes with lower travel costs and has higher algorithm execution efficiency. Among the output optimal routes, the proposed algorithm can reduce costs by 5.62% at the lowest and 52.25% at the highest. Full article
(This article belongs to the Special Issue Information Technologies and Electronics: Volume 3)
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