Koniocortex-Like Network Application to Business Intelligence

Fombedilla, J. and Andina de la Fuente, Diego ORCID: https://orcid.org/0000-0001-7036-2646 (2018). Koniocortex-Like Network Application to Business Intelligence. En: "World Automation Congress (WAC 2018)", 03/06/2018 - 06/06/2018, Stevenson, Washington, USA. pp. 1-6. https://doi.org/10.23919/WAC.2018.8430298.

Descripción

Título: Koniocortex-Like Network Application to Business Intelligence
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: World Automation Congress (WAC 2018)
Fechas del Evento: 03/06/2018 - 06/06/2018
Lugar del Evento: Stevenson, Washington, USA
Título del Libro: World Automation Congress (WAC 2018)
Fecha: 2018
Materias:
ODS:
Palabras Clave Informales: Metaplasticity; Koniocortex; KLN; Business Intelligence; ACAD; Feature Extraction; Competition
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[thumbnail of INVE_MEM_2018_299559.pdf]
Vista Previa
PDF (Portable Document Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (837kB) | Vista Previa

Resumen

Koniocortex-Like Network model is a Bio-Inspired Neural Network structure that tries to replicate the architecture and properties of the biological koniocortex section of the brain. The structure is composed by different kinds of artificial neurons that interplay between them to create a competitive model that can be used to classify patterns. The classification performance obtained is based on different properties like lateral inhibition, metaplasticity and intrinsic plasticity, that allows a natural evolution of the network until obtaining the desired results. This kind of network has been applied to synthetic and real data showing big potential, now the network capabilities are tested using other state-of-the-art real data application: the classification of credit data from the Australian Credit Approval Database.

Más información

ID de Registro: 55154
Identificador DC: https://oa.upm.es/55154/
Identificador OAI: oai:oa.upm.es:55154
Identificador DOI: 10.23919/WAC.2018.8430298
URL Oficial: https://ieeexplore.ieee.org/document/8430298
Depositado por: Memoria Investigacion
Depositado el: 27 May 2019 17:35
Ultima Modificación: 27 May 2019 17:35