Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Neural Computing and Applications
Published in: Neural Computing and Applications 8/2010

01-11-2010 | Original Article

The effect of mid-term estimation on back propagation for time series prediction

Author: Taeho Jo

Published in: Neural Computing and Applications | Issue 8/2010

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This research proposes estimation of mid-terms in a time series for improving the prediction performance of back propagation. In this research, the process of estimating mid-terms is called VTG (virtual term generation) and schemes for doing that are called VTG schemes. This research proposes three VTG schemes: mean method, 2nd Lagrange method, and 1st Taylor method. We adopt only back propagation as prediction model, since the goal of this research is to improve its prediction performance and back propagation is used most popular for regression among supervised neural networks. By implementing the VTG schemes as preprocessing of time series prediction, it will be observed that the prediction performance of back propagation is improved through experiments of Sect. 5.
previous article Pose invariant face recognition based on hybrid-global linear regression
next article Hybrid neural modeling for groundwater level prediction

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Abu-Mustafa YS (1993) A method for learning from hints. Adv Neural Inf Process Syst 5:73–80
2.
Abu-Mustafa YS (1995) Financial application of learning from hints. Adv Neural Inf Process Syst 7:411–418
3.
An G (1996) The effect of adding noise during back propagation training on generalization performance. Neural Computation 7:643–674CrossRef
4.
Box GEP, Jekins GM, Reinsel GC (1994) Time series analysis. Prentice Hall, Englewood Cliffs
5.
Brownstone D (1996) Using percentage accuracy to measure neural network predictions in stock market movements. Neurocomputing 10(3):237–250CrossRef
6.
Cho S, Jang M, Chang S (1996) Virtual sample generation using a population of neural networks. Neural Proc Lett 5:83–89
7.
Faires I, Douglas J (1993) Numerical analysis. PWS
8.
Ghosn J, Bengio Y (1997) Multi-task learning for stock selection. Neural Inf Process Syst 9:947–952
9.
Grandvalet Y, Canu S, Boucheron S (1997) Noise injection: theoretical prospects. Neural Comput 9(5):1093–1108CrossRef
10.
Jo T (1997) MLP training with noise optimized by genetic algorithm. In workshop of EUROGEN 97
11.
Kohzhadi N, Boyd MS, Kermanshani B, Kaastra I (1996) A comparison of artificial neural network and time series models forecasting commercial commodities. Neurocomputing 10:169–181CrossRef
12.
Levin AU (1996) Stock selection via nonlinear multilayer factor models. Neural Inf Proc Syst 8:966–977
13.
Malliaris M, Salchenberger L (1996) Using neural networks to forecast the S & P 100 implied volatility. Neurocomputing 10(2):183–195CrossRef
14.
Rumelhart DE, McClelland JL (1986) Parallel distributed processing: exploration in the microstructure of cognition. MIT Press, Cambridge
15.
Master T (1995) Neural, novel & hybrid algorithms for time series prediction. Wiley, New York
16.
Wan EA (1994) Time Series prediction by using a connectionist network with internal delay lines. In: Weigend AS, Gershenfeld NA (eds) Time series prediction: forecasting the future and understanding the past. Addison-Wesley, Reading, pp 195–217
17.
Weigend AS, Huberman BA, Rumelhart DE (1990) Predicting the future: a connectionist approach. International Journal of Neural Systems 193–209
18.
Weigend AS, Rumelhart DE (1991) Generalization through minimal networks with application to forecasting. The proceedings of 23rd symposium interface. pp 362–370
Metadata
Title
The effect of mid-term estimation on back propagation for time series prediction
Author
Taeho Jo
Publication date
01-11-2010
Publisher
Springer-Verlag
Published in
Neural Computing and Applications / Issue 8/2010
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-010-0352-1

Other articles of this Issue 8/2010

Neural Computing and Applications 8/2010 Go to the issue

Original Article

Real-time removal of ocular artifacts from EEG based on independent component analysis and manifold learning

Original Article

Analysis of international debt problem using artificial neural networks and statistical methods

AIS

Immunocomputing for intelligent signal processing

Original Article

Hybrid neural modeling for groundwater level prediction

AIS

A graph-based immune-inspired constraint satisfaction search

Original Article

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

Premium Partner

    Image Credits