Hour-Glass Neural Network Based Daily Money Flow Estimation for Automatic Teller Machines
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- Karungaru Stephen
- Graduate School of Advanced Science and Technology, University of Tokushima
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- Akashi Takuya
- Graduate School of Science and Engineering, University of Yamaguchi
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- Nakano Miyoko
- Tokushukai Medical Corporation
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- Fukumi Minoru
- Graduate School of Advanced Science and Technology, University of Tokushima
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Description
Monetary transactions using Automated Teller Machines (ATMs) have become a normal part of our daily lives. At ATMs, one can withdraw, send or debit money and even update passbooks among many other possible functions. ATMs are turning the banking sector into a ubiquitous service. However, while the advantages for the ATM users (financial institution customers) are many, the financial institution side faces an uphill task in management and maintaining the cash flow in the ATMs. On one hand, too much money in a rarely used ATM is wasteful, while on the other, insufficient amounts would adversely affect the customers and may result in a lost business opportunity for the financial institution. Therefore, in this paper, we propose a daily cash flow estimation system using neural networks that enables better daily forecasting of the money required at the ATMs. The neural network used in this work is a five layered hour glass shaped structure that achieves fast learning, even for the time series data for which seasonality and trend feature extraction is difficult. Feature extraction is carried out using the Akamatsu Integral and Differential transforms. This work achieves an average estimation accuracy of 92.6%.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 129 (7), 1325-1330, 2009
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390282679581335168
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- NII Article ID
- 10025101308
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 10357384
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL Search
- Crossref
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed