Monitoring of urban freight flows distribution considering the human factor

Davidich, N.; Galkin, Andrii; Iwan, Stanisław; Kijewska, Kinga; Чумаченко, Ігор; Davidich, Yurii

doi:10.1016/j.scs.2021.103168

Cited by 21 publications

(6 citation statements)

References 27 publications

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“…Крім того, при цьому необхідно враховувати зовнішні витрати логістики при організації нової системи доставки товарів . Шум, викиди, використання публічного простору (Davidich, et al 2021), затори на дорогах та безпека, прямі та реверсійні потоки (Galkin et. al., 2022b), негативні соціальні ефекти (5.…”

Section: літератураunclassified

Digital Innovations in the Socio-Economic Sphere

2023

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Section: літератураunclassified

Digital Innovations in the Socio-Economic Sphere

2023

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“…The hypothesis of this research is the specific trip distribution function of residents, which belong to different socio-demographic groups of the urban population. In addition, the personal qualities of urban residents have a great influence on trip attributes [57,58]. These qualities should also be considered when developing an intelligent transport system.…”

Section: Literature Reviewmentioning

confidence: 99%

Intelligent Decision Support System for Modeling Transport and Passenger Flows in Human-Centric Urban Transport Systems

et al. 2022

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Engineering human-centric urban transport systems should be carried out using information technology in forecasting traffic and passenger flows. One of the most important objects of urban transport systems’ progress is modeling patterns of transport flows and their distribution on the road network. These patterns are determined by the subjective choice of city residents of traffic routes using public and private transport. This study aimed to form a sequence of stages of modeling transport and passenger flows in human-centric urban transport systems and passenger flows in the human-centric urban intelligent transport systems and to determine the patterns of change to the gravity function of employees of municipal services. It was revealed that the trip distribution function of workers of urban service enterprises can be described by the attributes of the structure of the city, socio-economic data, and attributes characterizing the zones and its residents.

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“…The global pandemic has stimulated the development of digital transformation in many areas, such as business [6], education [7], and public administration [8]. Digital transformations have not bypassed the healthcare sector [9], including fighting the pandemic.…”

Section: Introductionmentioning

confidence: 99%

Impact of war on COVID-19 pandemic in Ukraine: the simulation study

Chumachenko

Pyrohov

Meniailov

et al. 2022

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The COVID-19 pandemic has posed a challenge to public health systems worldwide. As of March 2022, almost 500 million cases have been reported worldwide. More than 6.2 million people died. The war that Russia launched for no reason on the territory of Ukraine is not only the cause of the death of thousands of people and the destruction of dozens of cities but also a large-scale humanitarian crisis. The military invasion also affected the public health sector. The impossibility of providing medical care, non-compliance with sanitary conditions in areas where active hostilities are occurring, high population density during the evacuation, and other factors contribute to a new stage in the spread of COVID-19 in Ukraine. Building an adequate model of the epidemic process will make it possible to assess the actual statistics of the incidence of COVID-19 and assess the risks and effectiveness of measures to curb the curse of the disease epidemic process. The article aims to develop a simulation model of the COVID-19 epidemic process in Ukraine and to study the results of an experimental study in war conditions. The research is targeted at the epidemic process of COVID-19 under military conditions. The subjects of the study are models and methods for modeling the epidemic process based on statistical machine learning methods. To achieve the study's aim, we used forecasting methods and built a model of the COVID-19 epidemic process based on the polynomial regression method. Because of the experiments, the accuracy of predicting new cases of COVID-19 in Ukraine for 30 days was 97,98%, and deaths of COVID-19 in Ukraine – was 99,87%. The model was applied to data on the incidence of COVID-19 in Ukraine for the first month of the war (02/24/22 - 03/25/22). The calculated predictive values showed a significant deviation from the registered statistics. Conclusions. This article describes experimental studies of implementing the COVID-19 epidemic process model in Ukraine based on the polynomial regression method. The constructed model was sufficiently accurate in deciding on anti-epidemic measures to combat the COVID-19 pandemic in the selected area. The study of the model in data on the incidence of COVID-19 in Ukraine during the war made it possible to assess the completeness of the recorded statistics, identify the risks of the spread of COVID-19 in wartime, and determine the necessary measures to curb the epidemic curse of the incidence of COVID-19 in Ukraine. The investigation of the experimental study results shows a significant decrease in the registration of the COVID-19 incidence in Ukraine. An analysis of the situation showed difficulty in accessing medical care, a reduction in diagnosis and registration of new cases, and the war led to the intensification of the COVID-19 epidemic process.

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Monitoring of urban freight flows distribution considering the human factor

Cited by 21 publications

References 27 publications

Digital Innovations in the Socio-Economic Sphere

Digital Innovations in the Socio-Economic Sphere

Intelligent Decision Support System for Modeling Transport and Passenger Flows in Human-Centric Urban Transport Systems

Impact of war on COVID-19 pandemic in Ukraine: the simulation study

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