Literature Review On Models, Software Architectures And Software Design Patterns For Building A Sales Forecasting Module For Improved Decision Making

Jorge ESPINOZA ESPINOZA and Igor AGUILAR ALONSO

National Technological University of South Lima, Peru

Abstract

Nowadays the business world is very dynamic so making the right decision on a strategy is very relevant on the future of it. Forecasting has been widely used in various fields to know how to predict uncertain events in the future and to use the information that already exists to project an uncertain future. The objective of this article is to review the results of the models found for the improvement of decision making, projection and model combinations. A brief literature review was conducted to analyze articles published in prestigious journals during the last four years. As a result, 93 potential articles were found and 30 articles were selected. From the results it is concluded that the use of projections can improve decision making because it allows us to predict uncertain events in the future of the company.

Keywords: forecasting, decision making, arima algorithm, lstm
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