Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
ARTIFICIAL ANALYSIS OF MOLECULAR MARKER LOCI LINKED TO TREE RESISTANCE RESPONSE BY AN ARTIFICIAL NEURAL NETWORK
Year:2015
Research Areas
  • Artificial intelligence,
  • Artificial intelligence (neuronal nets, expert systems, etc),
  • Engineering
Information
Abstract
One of the biggest challenges that software developers face is to make an accurate estimate of the project effort. Radial basis function neural networks have been used to software effort estimation in this work using NASA dataset. This paper evaluates and compares radial basis function versus a regression model. The results show that radial basis function neural network have obtained less Mean Square Error than the regression method.
International
Si
JCR
No
Title
International Journal "Information Content and Processing", Volume 2, Number 1
ISBN
23675128
Impact factor JCR
Impact info
Volume
2/2015
Journal number
From page
43
To page
51
Month
SIN MES
Ranking
Participants
  • Autor: Angel Luis Castellanos Peñuela (UPM)
  • Autor: Juan Bautista Castellanos Peñuela (UPM)
  • Autor: Jorge Fernández (Universidad Complutense)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Computación Natural
  • Departamento: Inteligencia Artificial
  • Departamento: Matemática Aplicada
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)