Journal of Networking Technology
Artur Moroz, Illia Solohubov, Mariia Yu. Tiahunova, Halyna H. Kyrychek  and Stepan Skrupsky
Journal of Networking Technology, Vol. 15, No. 3, 2024.
DOI: https://doi.org/10.6025/jnt/2024/15/3/93-104
Link: https://www.dline.info/jnt/fulltext/v15n3/jntv15n3_3.pdf
Abstract:
This research explores artificial neural networks, focusing on their application in a digital tourist information system. The investigation starts by examining the basic principles that govern neural networks, their differences from conventional programming methods, and their advantages in such systems. It also looks into the work of OpenAI and their creation of ChatGPT, showcasing the wide range of applications for neural networks in practical situations. The research evaluates how neural networks compare to static programming in terms of their capabilities, and how these methods affect the efficiency of system creation and the variety of possible settings. Additionally, the research covers the use of neural networks on the Node.js platform, highlighting the practical benefits of this method through specific case studies of handling unexpected questions that cannot be easily programmed for. The study also reviews current tourist information systems and the creation of a prototype system. Furthermore, it includes a comparison of the outcomes from various experiments, supporting neural networks benefitâ€™s in surpassing traditional static programmingâ€™s limitations in improving digital tourist services.