2023

Постійне посилання на фонд

https://ela.kpi.ua/handle/123456789/57991

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Перегляд 2023 за Ключові слова "303.732.4, 519.816"

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    Ptimization of route distance using k-nn algorithm for on-demand food delivery
    (КПІ ім. Ігоря Сікорського, 2023) Paithane, Pradip M.; Wagh, Sarita Jibhau; Kakarwal, Sangeeta N.
    Customers are now more able to purchase goods over the phone or the Internet, and the ability for those purchases to be delivered safely to the customer’s location is proliferating. On-request meal delivery, where customers submit their food orders online, and riders deliver them, is growing in popularity. The cuttingedge urban food application necessitates incredibly efficient and adaptable continuous delivery administrations toward quick delivery with the shortest route. However, signing up enough food parcels and training them to use such food-seeking frameworks is challenging. This article describes a publicly supported web-based food delivery system. IoT (Internet of Things) and 3G, 4G, or 5G developments can attract public riders to act as publicly sponsored riders delivering meals using shared bikes or electric vehicles. The publicly funded riders are gradually distributed among several food suppliers for food delivery. This investigation promotes an online food ordering system and uses K-Nearest Neighbor calculations to address the Traveling Salesman Problem (TSP) in directing progress. The framework also uses the Global Positioning System (GPS) on Android-compatible mobile devices and the TOMTOM Routing API to obtain coordinates for planning purposes. To evaluate the presentation of the proposed approach, recreated limited scope and certifiable enormous scope on-request food delivery occurrences are used. Compared to the conventional methodology, the proposed strategy reduces the delay time. Each rider will receive the most direct route to the order delivery address. The delivery delay time is reduced by approximately 10–15 minutes for every order. The food supplier can determine whether an item is available to the rider; thus, the food supplier can add an order to the rider having the shortest way.
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    Study of the underground tunnel planning. Cognitive modelling
    (КПІ ім. Ігоря Сікорського, 2023) Pankratova, N.D.; Musiienko, D.I.
    A study of the underground tunnel planning reliability for megacities is proposed based on the use of foresight and cognitive modeling methodologies. Using the foresight methodology allows, with the help of expert estimation procedures, to identify critical technologies and build alternatives of scenarios with quantitative characteristics. For the justified implementation of a particular scenario, cognitive modeling is used, which allows to build causal relationships based on knowledge and experience, understand and analyze the behavior of a complex system for a strategic perspective with a large number of interconnections and interdependencies. The suggested study allows the reliability planning of underground tunnels on the basis of reasonable scenarios selection and justification of their creation priority.