چکیده مقاله
Data science, stem from statistical science, has emerged to make the best use of extant data It is known as one of the popular branches in the industrial engineering In view the fact that a large number of data have generated in the various businesses, data science can substantially assist the managers to find specific patterns for prediction In this regard, this paper applies the k means approach to achieve the optimal cluster for the considered data Likewise, the neural network algorithm is employed to forecast the future result Using a regression model, the important factors for transaction success is also determined, Ultimately, the best marketing strategies have suggested Eventually, a case study in one of the branches of Bank Melli Iran is conducted, through which important managerial insights are extracted
کلیدواژهها
نویسندگان
Sajjad Fakheri
Iran University of Science and Technology IUST Tehran, Iran
Mir Saman Pishvaee
Iran University of Science and Technology IUST Tehran, Iran
Ahmad Makui
Iran University of Science and Technology IUST Tehran, Iran
Ehsan Dehghani
Iran University of Science and Technology IUST Tehran, Iran
شیوه ارجاع
Fakheri, Sajjad and pishvaee, mir saman and Makui, Ahmad and Dehghani, Ehsan,1398,Data mining of an ATM machine in 24 hours exploiting clustering and forecasting models for marketing strategies: A case study in one of the branches of Bank Melli Iran,5th International Conference on Industrial and Systems Engineering,Mashhad
ارائهشده در
مجموعه مقالات پنجمین کنفرانس بین المللی مهندسی صنایع و سیستمها (ICISE ۲۰۱۹)13 شهریور 1398 · مشهد