Abstract
The aim of the paper was to describe analyzing influence of meteoparameters on production process. We compiled proposal for collecting data and recommendations for researchers solving similar problems in the future. The first part defines terms related to the topic (Big Data, Knowledge Discovery in Databases, and Data Mining) and analyze the chosen topic via opinions of experts. Weather influences production process mostly via human factor, so this part describes influence that meteoparameters have on human health, behavior and job performance. The second part deals with two types of input data – meteoparameters (parameters of weather) and data from production process. It describes the data, their cleaning, integration and selection, and generating of an additional dataset. The third part focuses on acquiring knowledge from the data via several data mining methods. It describes statistical analysis and consequent corrections of the data, building of data mining model, and compares individual methods. That results in proposal for collecting data and recommendations, both of which are based on problems that had arisen in the process of the analysis. The fourth, final part concludes with summarizing sequence of steps of the process.
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Acknowledgement
This publication is the result of implementation of the project: “Increase of Power Safety of the Slovak Republic” (ITMS: 26220220077) supported by the Research & Development Operational Programme funded by the ERDF and project VEGA 1/0272/18: “Holistic approach of knowledge discovery from production data in compliance with Industry 4.0 concept” supported by the VEGA.
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Abasova, J., Tanuska, P. (2019). Preparing Influence Analysis of Meteoparameters on Production Process. In: Silhavy, R. (eds) Software Engineering and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 763. Springer, Cham. https://doi.org/10.1007/978-3-319-91186-1_13
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DOI: https://doi.org/10.1007/978-3-319-91186-1_13
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