Applications of Symmetry/Asymmetry in Information Technology

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 1967

Special Issue Editor


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Guest Editor
Information Technology and Management Program, Ming Chuan University, Taoyuan City 333, Taiwan
Interests: artificial intelligence; evolutionary computation; wind and solar energy; metaheuristics; pattern recognition; image processing; machine learning; software engineering; computational intelligence; operations research
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Special Issue Information

Dear Colleagues,

“Symmetry” has reach in almost every discipline of information technology. Its elements appear in many applications, for example, object recognition, engineering design, music composition, and market prediction. By using the properties of “symmetry”, intelligent systems, such as the Internet of Things (IoT) and Cyber–Physical Systems (CPS), can be made more efficient and effective. The changes in industry over the last decade as a result of innovative technologies and businesses challenging competitiveness have been overwhelming. These changes are partly due to the emergence of new technologies such as the IoT, CPS, deep learning, self-media, and the shared economy and partly due to the international trade protection, which constrains the development of global supply chain and regional tax-free agreements. The aim of this Special Issue is to call attention to the important trend of using Symmetry/Asymmetry in information technology. We are collaborating with several conferences on this theme and are also open for submissions (research and review articles) covering (though not limited to) the following topics:

  • Symmetry/asymmetry in information technology;
  • Symmetry/asymmetry and heuristics and metaheuristics;
  • Symmetry/asymmetry algorithms.

Prof. Dr. Peng-Yeng Yin
Guest Editor

Manuscript Submission Information

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Keywords

  • symmetry
  • asymmetry
  • Internet of Things (IoT)
  • big data
  • heuristic and metaheuristic
  • information technology

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Published Papers (1 paper)

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Research

42 pages, 6764 KiB  
Article
Navigation Route Planning for Tourism Intelligent Connected Vehicle Based on the Symmetrical Spatial Clustering and Improved Fruit Fly Optimization Algorithm
by Xiao Zhou, Jian Peng, Bowei Wen and Mingzhan Su
Symmetry 2024, 16(2), 159; https://doi.org/10.3390/sym16020159 - 29 Jan 2024
Cited by 2 | Viewed by 1183
Abstract
The intelligent connected vehicle (ICV) decision-making system needs to match tourist interests and search for the route with the lowest travel cost when recommending POIs (Points of Interest) and navigation tour routes. In response to this research objective, we construct a navigation route-planning [...] Read more.
The intelligent connected vehicle (ICV) decision-making system needs to match tourist interests and search for the route with the lowest travel cost when recommending POIs (Points of Interest) and navigation tour routes. In response to this research objective, we construct a navigation route-planning model for tourism intelligent connected vehicles based on symmetrical spatial clustering and improved fruit fly optimization algorithm. Firstly, we construct the POI feature attribute clustering algorithm based on the spatial decision forest to achieve the optimal POI recommendation. Secondly, we construct the POI spatial attribute clustering algorithm based on the SA-AGNES (Spatial Accessibility-Agglomerative Nesting) to achieve the spatial modeling between POIs and ICV clusters. On the basis of POI feature attribute and spatial attribute, we construct the POI recommendation algorithm for the ICV navigation routes based on the attribute weights. On the basis of the recommended POIs, we construct the tourism ICV navigation route-planning model based on the improved fruit fly optimization algorithm. Experiments prove that the proposed algorithm can accurately output POIs that match tourists’ interests and needs, and find out the ICV navigation route with the lowest travel cost. Compared with the commonly used map route-planning methods and traditional route-searching algorithms, the proposed algorithm can reduce the travel costs by 15.22% at most, which can also effectively reduce the energy consumption of the ICV system, and improve the efficiency of sight-seeing and traveling for tourists. Full article
(This article belongs to the Special Issue Applications of Symmetry/Asymmetry in Information Technology)
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