Planning workforce management for bank operation centers with neural networks
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Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wseas
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
A bank operation center provides a revolutionary efficiency to reduce operational workload of branches. In this way, offering faster, more accurate and high quality service is aimed to increase service quality. Service quality is also based on predicting transactions counts before time to make employee planning properly. In this paper, transactions of bank operation centers are considered as time series problem and a model is proposed for forecasting the transaction counts for different operation types with artificial neural networks. This model was simulated for forecasting Money Order and EFT operations which are the most active transactions of operation centers
Açıklama
Anahtar Kelimeler
Machine Learning, Artificial Neural Networks (ANN), Multilayer Perceptron (MLP), Time Series Forecasting, Predictive Analytics, Employee Assignment
Kaynak
Proceedings of the 15th International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED '16)
