Planning workforce management for bank operation centers with neural networks

Serengil, Şefik İlgin; Özpınar, Alper

Planning workforce management for bank operation centers with neural networks

dc.authorid	0000-0003-1250-5949	en_US
dc.contributor.author	Serengil, Şefik İlgin
dc.contributor.author	Özpınar, Alper
dc.date.accessioned	2019-08-20T09:17:45Z
dc.date.available	2019-08-20T09:17:45Z
dc.date.issued	2016	en_US
dc.department	Fakülteler, Mühendislik Fakültesi	en_US
dc.description.abstract	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	en_US
dc.identifier.endpage	188	en_US
dc.identifier.startpage	184	en_US
dc.identifier.uri	https://hdl.handle.net/11467/2884
dc.language.iso	en	en_US
dc.publisher	Wseas	en_US
dc.relation.ispartof	Proceedings of the 15th International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED '16)	en_US
dc.relation.publicationcategory	Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı	en_US
dc.rights	info:eu-repo/semantics/openAccess	en_US
dc.subject	Machine Learning	en_US
dc.subject	Artificial Neural Networks (ANN)	en_US
dc.subject	Multilayer Perceptron (MLP)	en_US
dc.subject	Time Series Forecasting	en_US
dc.subject	Predictive Analytics	en_US
dc.subject	Employee Assignment	en_US
dc.title	Planning workforce management for bank operation centers with neural networks	en_US
dc.type	Article	en_US