Estimating shopping center visitor numbers based on a new hybrid fuzzy prediction method

Companies started to determine their strategies based on intelligent data analysis due to stagey enhance data production. Literature reviews show that the number of resources where demand estimation, location analysis, and decision-making technique applied together with the machine learning method is low in all sectors and almost none in the shopping mall domain. Within this study’s scope, a new hybrid fuzzy prediction method has been developed that will estimate the customer numbers for shopping malls. This new methodology is applied to predict the number of visitors of three shopping malls on the Anatolian side of Istanbul. The forecasting study for corresponding shopping malls is made by using the daily signaling data from indoor base stations of large-scale technology and telecommunications services provider and the features to be used in machine learning models is determined by fuzzy multi criteria decision making method. Output revealed by the application of the fuzzy multi criteria decision making method enables the prioritization of features.

Fuzzy sets theory and applications in engineering economy

Engineering economics is an essential issue in investments and can be quietly difficult to make decisions especially in indefinite, vague and incomplete environments because of human thought. Usage of fuzzy sets gives better solutions in vagueness. Fuzzy sets could be an agreeable tool when no probabilities are accessible for states of nature and decisions are given under incompleteness. In this study, fuzzy engineering economics studies are summarized for showing fuzzy sets usage in engineering economics applications and finding gaps for future studies. The possible suggested are given in conclusion.