Intelligent Method for Forming the Consumer Basket

Lipyanina-Goncharenko, Hrystyna; Wolff, Carsten; Chyzhovska, Zoriana; Sachenko, Anatoliy; Lendyuk, Taras; Grodskyi, Sergii

doi:10.1007/978-3-031-16302-9_17

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…Using the KElbowVisualizer tool [38] (Figure 3), we found the most optimal value of the cluster number for clustering data in the KM model. In this particular case, the number of clusters that best fits the data is four.…”

Section: Resultsmentioning

confidence: 99%

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Intelligent Waste-Volume Management Method in the Smart City Concept

Lipianina-Honcharenko,

Komar,

Osolinskyi

et al. 2023

Smart Cities

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This research paper proposes an innovative approach to urban waste management using intelligent methods of classification, clustering, and forecasting. The application of this approach allows for more efficient waste management and contributes to the sustainable development of the urban environment. The aim of this research is to develop an intelligent method for urban waste management, which includes clustering of waste sources, accurate forecasting of waste volumes, and evaluation of forecast results. To achieve this goal, a real dataset with city characteristics and waste data was used. On account of the war in Ukraine, the authors faced the problem of obtaining open data on waste in Ukraine, so it was decided to use data from another city (Singapore). The results show the high efficiency of the developed method. Comparison of the obtained results with the results of the nearest similar works shows that the main feature of this study is the high accuracy of waste-volume forecasting using the XGBoost model, which reached a level of up to 98%.

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Section: Resultsmentioning

confidence: 99%

“…• K-Means (KM) [38,39] minimizes the squares sum of distances between points (x i ) and their cluster centers c j : ∑ x i -c j 2 ;…”

Section: Proposed Methodsmentioning

confidence: 99%

Intelligent Waste-Volume Management Method in the Smart City Concept

Lipianina-Honcharenko,

Komar,

Osolinskyi

et al. 2023

Smart Cities

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“…he social sphere includes people's attitudes towards culture, art, and tourism [18,19], as well as an assessment of personal safety, the education system and personal education, the healthcare system and personal health, amenities and living conditions [16], and transport.…”

Section: Concept Of An Intelligent Information System For the City's ...mentioning

confidence: 99%

Intelligent information system of the city's socio-economic infrastructure

Lipianina-Honcharenko,

Bodyanskiy,

Sachenko

2023

SRIT

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Urban development is an important problem that can be solved with the help of intelligent information systems. Such systems ensure efficient management of the city’s diverse infrastructure. The researchers developed a concept of such an information system based on a conceptual model and using data flow for intelligent decision-making. The system was tested for 1460 days in the city of Ternopil. The modelling results showed that the city’s central area is stable, with 50% of enterprises in the “growing” state and 70% of people in the “satisfactory” state. People often move to the northeastern and western zones due to higher levels of comfort and more affordable housing. However, the total distance of car trips has increased by 249%, negatively impacting the environment. The condition of enterprises in other zones is less stable with lower “growth” indicators, but there are zones with “stable” and “satisfactory” conditions.

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