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Forecasting incomin...
Forecasting incoming call volumes in call centers with recurrent Neural Networks
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- Ebadi Jalal, Mona (författare)
- K. N. Toosi University of Technology
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- Hosseini, Monireh (författare)
- K. N. Toosi University of Technology
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- Karlsson, Stefan (författare)
- Lund University,Lunds universitet,Förpackningslogistik,Institutionen för designvetenskaper,Institutioner vid LTH,Lunds Tekniska Högskola,Packaging Logistics,Department of Design Sciences,Departments at LTH,Faculty of Engineering, LTH
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K N. Toosi University of Technology Förpackningslogistik (creator_code:org_t)
- Elsevier BV, 2016
- 2016
- Engelska 4 s.
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Ingår i: Journal of Business Research. - : Elsevier BV. - 0148-2963. ; 69:11, s. 4811-4814
- Relaterad länk:
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http://dx.doi.org/10...
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https://lup.lub.lu.s...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Researchers apply Neural Networks widely in model prediction and data mining because of their remarkable approximation ability. This study uses a prediction model based on the Elman and NARX Neural Network and a back-propagation algorithm for forecasting call volumes in call centers. The results can help determine the optimal number of agents necessary to reduce waiting time for customers, enabling profit maximization and reduction of unnecessary costs. This study also compares the performance of the Elman-NARX Neural Network model with the time-lagged feed-forward Neural Network in addressing the same problem. The experimental results indicate that the proposed method is efficient in forecasting the call volumes of call centers.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Call center
- Forecasting
- Model prediction
- Neural Networks
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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