Model of the Forecasting Cash Withdrawals in the ATM Network

The Case for RFID-Enabled Traceability in Cash Movements

“…In Automatic Teller Machine (ATM) servicing, researchers have explored several paths to predict the supply of cash availability in these machines and optimize operations [11][12][13][14][15][16][17][18][19].…”

Atm’lerdeki̇ Naki̇te Yöneli̇k Talep Tahmi̇ni̇ Üzeri̇ne Si̇stemati̇k Yazin Anali̇zi̇

“…Referans Başlık (Kumar and Walia, 2006) Cash Forecasting: An Application of ANN in Finance (Simutis et al, 2007) Optimization of Cash Management for ATM Network (Simutis et al, 2008) Cash Demand Forecasting for ATMs using NN and SVR Algorithms (Brentnall et al, 2008) A Statistical Model for the Temporal Pattern of Individuals ATM Withdrawals (Zapranis and Antonis, 2009) Forecasting Cash Money Withdrawals Using Wavelet Analysis and Wavelet Neural Networks (Brentnall et al, 2010a) Predicting the Amount Individuals at ATMs using REMM (Brentnall et al, 2010b (Acuna et al, 2012) Comparing NARX and NARMAX models using ANN and SVM for cash demand forecasting for ATMs (Darwish, 2013) A Methodology to Improve Cash Demand Forecasting for ATM Network (Gurgul and Suder, 2013) Modelling of Withdrawals from Selected ATMs of the "Euro net" Network (Wagner, 2013) Forecasting Daily Demand in Cash Supply Chains (Arora et al, 2014) Approximating Methodology: Managing Cash in ATMs Using Fuzzy ARTMAP Network (Kamini and Ravi, 2014) Chaotic TSA with NN to Forecast Cash Demand in ATMs (Venkatesh et al, 2014) Cash Demand Forecasting in ATMs by Clustering and NN (Catal et al, 2015) Improvement of Demand Forecasting Models with Special Days (Aseev et al, 2016) Forecasting Cash Withdrawals in the ATM Network using a Combined Model based on the HWM and Markov Chains (Nemeshaev and Tsyganov, 2016) Model of the Forecasting Cash Withdrawals in the ATM Network (Khanarsa and Sinapiromsaran, 2017) Multiple ARIMA Subsequences Aggregate TSM to Forecast Cash in ATM Veri serisinin uzunluğu da, çalışmaların incelenmesi gereken önemli bir karakteristiğini yansıtmaktadır. Veri setinin uzunluğu arttıkça, tahmin hassasiyetinin başarısını doğrudan etkilemektedir.…”

“…Teddy and Ng (2011) kendi başına en iyi parametre seçimi ile ilgili bir algoritma uygulamaktadır. Kamini and Ravi (2014) gecikme zamanı ve gömülü boyut gibi kaotik parametreleri modele dâhil etmekte, Nemeshaev and Tsyganov (2016) günlük para çekme miktarından bahsetmekte fakat girdileri detaylandırmamaktadır. et al, 2007;Wichard et al, 2010;Darwish, 2013;Wagner, 2013) izlemektedir.…”