Claim Status Prediction for OSIPTEL Using Neural

In recent years, the demand for complaints from users towards mobile operators has increased notably according to OSIPTEL indicators. Only for the year 2017, the operating companies registered 2 million 728 thousand 430 claims, of which 233 thousand 342 claims passed to second instance (Tribunal Adm...

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Autores principales:	Hugo David Calderon Vilca, Kerly J. Quispe Quispe, Anthony B. Puitiza Lopez Anthony B. Puitiza Lopez, Miguel A. Zuniga Yamashita, Flor C. Cardenas-Marino, Reynaldo Sucari Leon
Formato:	article
Lenguaje:	EN
Publicado:	FRUCT 2021
Materias:	neural networks prediction claims mobile telephony telecommunications Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/d84ce80354e0412e9f3593007f3e5a8b
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spelling	oai:doaj.org-article:d84ce80354e0412e9f3593007f3e5a8b2021-11-20T15:59:33ZClaim Status Prediction for OSIPTEL Using Neural2305-72542343-073710.5281/zenodo.5639757https://doaj.org/article/d84ce80354e0412e9f3593007f3e5a8b2021-10-01T00:00:00Zhttps://www.fruct.org/publications/acm30/files/Cal.pdfhttps://doaj.org/toc/2305-7254https://doaj.org/toc/2343-0737In recent years, the demand for complaints from users towards mobile operators has increased notably according to OSIPTEL indicators. Only for the year 2017, the operating companies registered 2 million 728 thousand 430 claims, of which 233 thousand 342 claims passed to second instance (Tribunal Administrativo de Solucion de Reclamo - TRASU of OSIPTEL), putting OSIPTEL in big trouble. This research seeks to solve this problem by implementing a system to predict the meaning of the claim, making use of neural networks. It was decided to implement a Multilayer Perceptron, as a learning algorithm, Backpropagation of the error was chosen. As for the architecture of the Perceptron, several were tested, where the changing factor was the neurons in the hidden layer. The results show that the system has 86.969% accuracy.Hugo David Calderon VilcaKerly J. Quispe QuispeAnthony B. Puitiza Lopez Anthony B. Puitiza LopezMiguel A. Zuniga YamashitaFlor C. Cardenas-MarinoReynaldo Sucari LeonFRUCTarticleneural networkspredictionclaimsmobile telephonytelecommunicationsTelecommunicationTK5101-6720ENProceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 30, Iss 2, Pp 316-323 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	neural networks prediction claims mobile telephony telecommunications Telecommunication TK5101-6720
spellingShingle	neural networks prediction claims mobile telephony telecommunications Telecommunication TK5101-6720 Hugo David Calderon Vilca Kerly J. Quispe Quispe Anthony B. Puitiza Lopez Anthony B. Puitiza Lopez Miguel A. Zuniga Yamashita Flor C. Cardenas-Marino Reynaldo Sucari Leon Claim Status Prediction for OSIPTEL Using Neural
description	In recent years, the demand for complaints from users towards mobile operators has increased notably according to OSIPTEL indicators. Only for the year 2017, the operating companies registered 2 million 728 thousand 430 claims, of which 233 thousand 342 claims passed to second instance (Tribunal Administrativo de Solucion de Reclamo - TRASU of OSIPTEL), putting OSIPTEL in big trouble. This research seeks to solve this problem by implementing a system to predict the meaning of the claim, making use of neural networks. It was decided to implement a Multilayer Perceptron, as a learning algorithm, Backpropagation of the error was chosen. As for the architecture of the Perceptron, several were tested, where the changing factor was the neurons in the hidden layer. The results show that the system has 86.969% accuracy.
format	article
author	Hugo David Calderon Vilca Kerly J. Quispe Quispe Anthony B. Puitiza Lopez Anthony B. Puitiza Lopez Miguel A. Zuniga Yamashita Flor C. Cardenas-Marino Reynaldo Sucari Leon
author_facet	Hugo David Calderon Vilca Kerly J. Quispe Quispe Anthony B. Puitiza Lopez Anthony B. Puitiza Lopez Miguel A. Zuniga Yamashita Flor C. Cardenas-Marino Reynaldo Sucari Leon
author_sort	Hugo David Calderon Vilca
title	Claim Status Prediction for OSIPTEL Using Neural
title_short	Claim Status Prediction for OSIPTEL Using Neural
title_full	Claim Status Prediction for OSIPTEL Using Neural
title_fullStr	Claim Status Prediction for OSIPTEL Using Neural
title_full_unstemmed	Claim Status Prediction for OSIPTEL Using Neural
title_sort	claim status prediction for osiptel using neural
publisher	FRUCT
publishDate	2021
url	https://doaj.org/article/d84ce80354e0412e9f3593007f3e5a8b
work_keys_str_mv	AT hugodavidcalderonvilca claimstatuspredictionforosiptelusingneural AT kerlyjquispequispe claimstatuspredictionforosiptelusingneural AT anthonybpuitizalopezanthonybpuitizalopez claimstatuspredictionforosiptelusingneural AT miguelazunigayamashita claimstatuspredictionforosiptelusingneural AT florccardenasmarino claimstatuspredictionforosiptelusingneural AT reynaldosucarileon claimstatuspredictionforosiptelusingneural
_version_	1718419453279993856

Claim Status Prediction for OSIPTEL Using Neural

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