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3 8 ANN 9 ( (SARIMA 6 SARIMA Seasonal Autoregressive Moving Integrated Average Model POS PinPad

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17 AR MA SARIMA AR roots MA roots ( t ( ( ( ( C AR( SAR( MA( SMA( 4 F R DW F F 5 F (DW 0 F R F 75 Akaike info criterion Inverse Roots Ramsey Reset test 4 BreuschGodfrey

18 MA AR 9 8 ANN ( MSE RMSE MAPE MAD U R SARIMA ( ( R U MAD MAPE RMSE MSE ANN SARIMA ( SARIMA ANN (4 Simulation

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23 ( (8 (89 (90 ( (7 ( (88 (90 (8 (ANN 597 (84 ( (POS ATM (89 ATM Adam, Christopher (000 The Transactions Demand for Money in Chile, Research Department of the Central Bank of Chile

24 Chauvin, Y and Rumelhart DE (995 Backpropagation Theory architectures, and applications, Hillsdale, NJ Erlbaum Egan, Bob and George Tubin and Charul Vyas (007 US Mobile Banking Forecast 0070, wwwtowergroupcom 4 Engle, Robert F and Jeffrey R Russell (994 Forecasting Transactions Rates The Autoregressive Conditional Duration Model, Working Papers, National Bureau of Economic Research, Cambridge 5 Gan, Christopher and Mike Clemes and Visit Limsombunchai and Amy Weng (005, Consumer Choice Prediction Artificial Neural Networks versus Logistic Model, Commerce Division, Lincoln University Canterbury, No 04 6 Haykin, Simon S (994 Neural Networks A Comprehensive Foundation, Macmillan College Publishing 7 Howard, Demuth and Mark Beale (007 Neural Network Toolbox User s Guide, wwwmathworkscom 8 Maass, Peter and Torsten Koehler and Jan Kalden and Roza Costa and Ulrich Parlitz and Christian Merkwirth and Jörg Wichard (00 Mathematical methods for forecasting bank transaction data, Zentrum für Technomathematik 9 Paul, Justin and Anirban Mukherjee (00 ATMs and Cash Demand Forecasting A Study of Two Commercial Banks, Journal of Regional Development, vol, no, pp Sharda, R and RB Patil (99 Connectionist approach to time series prediction An empirical test, Journal of Intelligent Manufacturing, pp 7 Simutis, Rimvydas and Darius Dilijonas and Lidija Bastina (008 Cash Demand Forecasting for ATM Using Neural Networks and Support Vector Regression Algorithms, 0 th EURO Mini Conference Continuous Optimization and KnowledgeBased Technologies, Vilnius, Lithuania, pp 46 4 Snellman, Jussi and Jukka Vesala (999 Forecasting the Electronification of Payments with Learning Curves The Case of Finland, Discussion Papers, Bank of Finland, Research Department Tang, Zaiyong and and Fishwick Paul A (99, Feedforward Neural Nets as Models for Time Series Forecasting, Journal on Computing, vol5, no4, pp Zhang, G and B Eddy Patuwo and Michael Hu (998 Forecasting with artificial neural network the state of art, International Journal of Forecasting, vol4, pp 56 5 Zhang, Peter G (00 Time series forecasting using a hybrid ARIMA and neural network model, Neuro Computing, vol50, pp 5975

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