Modeling of Entrepreneurship Activity Crisis Management by Support Vector Machine
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Modeling of Entrepreneurship Activity Crisis Management by Support Vector Machine Vojo Lakovic1 Received: 9 March 2020 / Revised: 9 April 2020 / Accepted: 13 April 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The main goal of the study was to analyze the total and male entrepreneurial activity. Since it is the highly nonlinear task in this study was applied soft computing approach. Intelligent soft computing scheme support vector regression (SVR) was implemented. The performance of the proposed estimator was confirmed with the simulation results. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR compared to other soft computing methodologies. The new optimization methods benefit from the soft computing capabilities of global optimization and multi-objective optimization rather than choosing a starting point by trial and error. A systematic approach was carried to predict the entrepreneurial activity by the SVR methodology. The performance of the SVR approaches compared to the results from ANN and GP showed interesting improvements in the prediction system. SVR predictions with the polynomial kernel function are superior to other methodologies in terms of root-mean-square error and coefficient of error. Keywords SVR · Forecasting · Male entrepreneurial activity · Business
1 Introduction Entrepreneurship is a multilevel and complex phenomenon that gained importance in the global economy as a result of changes in employee qualifications, work contents, and psychological contracts in the employment field. Entrepreneurship contributes to economic growth in being a conveyor of new or existing knowledge spillover and creative ideas that might otherwise not be utilized and realized for the benefit of all. Linking entrepreneurship to economic growth means linking the individual level to the aggregate levels. The most significant contribution of small businesses and entrepreneurial activity is their ability to innovate.
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Vojo Lakovic [email protected] Fakultet društvenih znanosti dr. Milenka Brki´ca, Bijakovi´ci, Bosnia and Herzegovina
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Annals of Data Science
Entrepreneurship has attracted increasing attention in recent years in light of concrete evidence of the importance of new business creation for economic growth and development. Not only does entrepreneurship contribute to economic growth and employment creation, but it is increasingly recognized to also enhance the diversity of entrepreneurship in any economic system. These benefits are rarely leveraged in a systematic way. Various studies show that entrepreneurs contribute to economic development, job creation, and different aspects of wellbeing through creative destruction [1]. Results in [2] were indicated specific ways of constructing gender identity which result in gendered practices: how women act as entrepreneurs by ‘doing’ and ‘redoing’ gender. The degree at which entrepreneurship affects the economy depends on numerous factors, including the quality, gender com
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