| Summary: | 碩士 === 國立交通大學 === 管理學院碩士在職專班工業工程與管理組 === 95 === The purpose of this research is to construct a forecasting model for cash withdrawals from ATM by using Artificial Neural Network (ANN). In order to provide the better cash withdrawals service, we need a more accurate forecasting model for cash withdrawals from ATM. It will help the company to enhance the cash management and reduce the cost.
ANN has error tolerance ability, learning ability, high-speed computational ability, and high-volume memorizing ability. It also considers both linear and nonlinear relationship at the same time. This research aims to construct a forecasting model for cash withdrawals from ATM by using software Qnet2000 that is designed for ANN with Back-Propagation algorithm. First, we define the input and output nodes and set up the parameters and follow the training procedure of Back-Propagation Neural Network (BPN). Then, we construct a forecasting model of cash withdrawals from ATM by using the BPN. A real case was presented to demonstrate the methodology and the results revealed that the BPN could provide an acceptable accuracy for the forecasting model of cash withdrawals from ATM.
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