title: ÐÐ½Ð¾Ð³Ð¾ÐºÑÐ¸ÑÐµÑÐ¸Ð°Ð»ÑÐ½ÑÐ¹ Ð¿Ð¾Ð¸ÑÐº ÑÑÑÐµÐºÑÐ¸Ð²Ð½ÑÑ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½ÑÐµÑÐºÐ¸Ñ ÑÐµÑÐµÐ½Ð¸Ð¹ Ð´Ð»Ñ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ Ð²ÑÐ¶Ð¸Ð²Ð°ÐµÐ¼Ð¾ÑÑÐ¸ Ð¸ ÑÑÐºÐ¾ÑÐµÐ½Ð¸Ñ ÑÐ¾ÑÑÐ° ÐºÐ¾Ð¼Ð¿Ð°Ð½Ð¸Ð¹ Ð² Ð¸Ð·Ð¼ÐµÐ½ÑÑÑÐ¸Ñ ÑÑ ÑÑÐ½Ð¾ÑÐ½ÑÑ ÑÑÐ»Ð¾Ð²Ð¸ÑÑ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Multi-criteria search for effective management solutions to increase the survival and accelerate the growth of companies in changing market conditions using data analysis and machine learning methods
Creators: name: ÐÐ¸Ð½Ð¸Ð½Ð°, ÐÐ½Ð½Ð°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
ÐÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
ÑÐ»ÑÑÐ°Ð¹Ð½ÑÐ¹ Ð»ÐµÑ
Ð¼Ð¾ÑÐ»
Ð¼Ð½Ð¾Ð¶ÐµÑÑÐ²ÐµÐ½Ð½Ð°Ñ Ð»Ð¸Ð½ÐµÐ¹Ð½Ð°Ñ ÑÐµÐ³ÑÐµÑÑÐ¸Ñ
Ð´ÐµÑÐµÐ²ÑÑ ÑÐµÑÐµÐ½Ð¸Ð¹
random forest
mosl
multiple linear regression
decision trees

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description: The subject of the graduate qualification work is Â«Multi-criteria search for effective management solutions to increase the survival and accelerate the growth of companies in changing market conditions by using data analysis and machine learning methodsÂ». The given work is devoted to studying the dependence of the survival of alliances on various business factors and the construction of an algorithm for multiobjective optimized random forests to identify these dependencies. The research set the following goals: Analysis of existing economic business strategies to find effectivemanagement solutions in changing market conditions. Analysis of initial data, research of the influence of independent externalvariables on the characteristics of survival and growth of companies and alliances, identification of the most important factors. Building a model for a machine learning algorithm that identifies the mosteffective decision trees using the ratio of data on the activities of individual companies and the survival of alliances. Software implementation of the machine learning algorithm. Research the work of the algorithm on real data. The work was made with two main sources - a dataset with information about alliances and a group of datasets from the Bureau van Dijk. Data analysis was made, which clearly showed the impact of business strategies on companies in different time periods. The analysis was carried out using multiple linear regression methods and a modification of the random forest algorithm. As a result, the market of business strategies was analyzed, keywords were identified, and a model of the relationship of SIC-codes was calculated. A model of multiple linear regression was built and the best parameters for p-values ââwere identified. An algorithm and a model for a multiobjective optimized random forest have been developed. Based on the conducted research, independent variables were derived that have a strong impact on the survival of companies. It has also been demonstrated that MORF shows not only important variables, but also their relationships.