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

Cagatay Ozdemir*, Sezi Cevik Onar, Selami Bagriyanik, Cengiz Kahraman, Burak Zafer Akalin, Başar Öztayşi

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1 Atıf (Scopus)

Özet

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.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)63-76
Sayfa sayısı14
DergiJournal of Intelligent and Fuzzy Systems
Hacim42
Basın numarası1
DOI'lar
Yayın durumuYayınlandı - 2022
Harici olarak yayınlandıEvet

Bibliyografik not

Publisher Copyright:
© 2022 - IOS Press. All rights reserved.

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