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Artificial intelligence and its impact on the pbkp_rediction of economic indicators

Abstract:

Economic indicators are key statistics based on economy, some examples of economic indicators are inflation rate, gross domestic product (GDP), unemployment rate, consumer price indices (CPI), interest rate, exports, consumption of energy, among others. Most of the published studies are focused on contextualizing and pbkp_redict a particular economic indicator without considering the current general situation on how non-linear models have been used in pbkp_redicting some of the economic indicators. This article, has analyzed in the scientific production the artificial intelligence methods mostly used in the development of pbkp_rediction models of economic indicators. The study was carried out by means of a systematic literature review (SLR) using the Web of Science (WOS), Scopus and Google Scholar bibliographic databases (BD) as resources. The documents and general information analyzed qualitatively are filtered between the range of years 2015 to 2019 to which an adequate set of quality and selection criteria were applied. The approach of the research questions allowed to describe the outcomes in categories where the studies by pbkp_redicted economic indicator and applied artificial intelligence method have been successfully included. The outcomes that have been obtained in this article represent a starting point for researchers, academics and professionals who wish to carry out studies related to the pbkp_rediction of economic indicators using some artificial intelligence (AI) methods. In conclusion, some of the artificial intelligence methods used to pbkp_redict economic indicators are artificial neural networks (ANN), adaptive systems of diffuse neuro inference (ANFIS), genetic programming (GP), support vector regression (SVR), machines extreme learning and other machine learning (ML) techniques.