A telecommunications call volume forecasting system based on a recurrent fuzzy neural network
dc.conference.information | Dallas, U.S.A., August 4-9, 2013 | el |
dc.conference.name | IEEE International Joint Conference on Neural Networks | el |
dc.contributor.author | Mastorocostas, P. A. | |
dc.contributor.author | Hilas, C. S. | |
dc.contributor.author | Varsamis, D. N. | |
dc.contributor.author | Dova, S. C. | |
dc.date.accessioned | 2015-06-28T16:04:56Z | |
dc.date.accessioned | 2024-09-27T18:12:07Z | |
dc.date.available | 2015-06-28T16:04:56Z | |
dc.date.available | 2024-09-27T18:12:07Z | |
dc.date.issued | 2013 | |
dc.description.abstract | The problem of telecommunications call volume forecasting is addressed to in this work. In particular, a foreacasting system is proposed, that is based on a dynamic fuzzy-neural model, where the consequent parts of the fuzzy rules are small Block-Diagonal Recurrent Neural Networks with internal feedback. The forecasting characteristics are highlighted and the prediction performance is evaluated by use of real-world telecommunications data. An extensive comparative analysis with a series of existing forecasters is conducting, including both traditional models as well as fuzzy and neurofuzzy approaches. | en |
dc.format.extent | 6 | el |
dc.identifier.doi | 10.1109/IJCNN.2013.6707102 | |
dc.identifier.other | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6707102&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6707102 | el |
dc.identifier.uri | https://repository2024.ihu.gr/handle/123456789/1544 | |
dc.language.iso | en | el |
dc.publication.category | Απαγόρευση δημοσίευσης - Βιβλιογραφική αναφορά | el |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject.keyword | Computational modeling | el |
dc.subject.keyword | Forecasting | el |
dc.subject.keyword | Market research | el |
dc.subject.keyword | Neurons | el |
dc.subject.keyword | Predictive models | el |
dc.subject.keyword | Recurrent neural networks | el |
dc.subject.keyword | Telecommunications | el |
dc.title | A telecommunications call volume forecasting system based on a recurrent fuzzy neural network | en |
dc.type | Άρθρο σε επιστημονικό συνέδριο | el |
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