• Corpus ID: 124045151

PENERAPAN GLOBAL RIDGE-REGRESSION PADA PERAMALAN DATA TIME SERIES NON LINEAR STUDI KASUS : PEMODELAN NILAI TUKAR US DOLAR TERHADAP RUPIAH

@inproceedings{Zuliana2012PENERAPANGR,
  title={PENERAPAN GLOBAL RIDGE-REGRESSION PADA PERAMALAN DATA TIME SERIES NON LINEAR STUDI KASUS : PEMODELAN NILAI TUKAR US DOLAR TERHADAP RUPIAH},
  author={Sri Utami Zuliana},
  year={2012}
}
  • S. Zuliana
  • Published 1 October 2012
  • Computer Science, Mathematics
Time series modelling has two types i.e. linear and non-linear. Feed Forward Neural Networks (FFNN) has modelled linear time series well but has found difficulties to model non-linear time series. Radial Basis Function Neural Networks (RBFNN) give an alternative to model non-linear time series. This network has Radial Basis Function in the hidden layer that provides non-linear functions. The RBFNN output is a linear combination of Radial Basis Functions and output weights. An optimal… 

ANALISIS METODE RBF-NN DENGAN OPTIMASI ALGORITMA GENETIKA PADA PERAMALAN MATA UANG EUR/USD

This paper discuss about EUR/USD forex forecasting using RBF-NN (Radial Basis Function – Neural Network) method without optimization and RBF-NN optimized by 3models of Genetic Algorithm (GA) and

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