Skip to main content

2016 | OriginalPaper | Buchkapitel

3. Problem Statement and Development

verfasst von : Fernando Gaxiola, Patricia Melin, Fevrier Valdez

Erschienen in: New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The proposed approach in this book has the goal of generalizing the backpropagation algorithm using type-1 fuzzy sets and type-2 fuzzy sets to allow the neural network to handle data with uncertainty. In the type-2 fuzzy sets, it will be necessary vary the footprint of uncertainty (FOU) of the membership functions using an optimization method to make it automatically or vary it manually for the corresponding applications [14].

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

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!

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!

Literatur
1.
Zurück zum Zitat Pedrycz, W.: Granular Computing: Analysis and Design of Intelligent Systems. CRC Press/Francis Taylor, Boca Raton (2013)CrossRef Pedrycz, W.: Granular Computing: Analysis and Design of Intelligent Systems. CRC Press/Francis Taylor, Boca Raton (2013)CrossRef
2.
Zurück zum Zitat Tung, S.W., Quek, C., Guan, C.: eT2FIS: an evolving type-2 neural fuzzy inference system. Inf. Sci. 220, 124–148 (2013)CrossRef Tung, S.W., Quek, C., Guan, C.: eT2FIS: an evolving type-2 neural fuzzy inference system. Inf. Sci. 220, 124–148 (2013)CrossRef
3.
Zurück zum Zitat Zarandi, M.H.F., Torshizi, A.D., Turksen, I.B., Rezaee, B.: A new indirect approach to the type-2 fuzzy systems modeling and design. Inf. Sci. 232, 346–365 (2013)CrossRef Zarandi, M.H.F., Torshizi, A.D., Turksen, I.B., Rezaee, B.: A new indirect approach to the type-2 fuzzy systems modeling and design. Inf. Sci. 232, 346–365 (2013)CrossRef
5.
Zurück zum Zitat Biglarbegian, M., Melek, W., Mendel, J.: On the robustness of type-1 and interval type-2 fuzzy logic systems in modeling. Inf. Sci. 181(7), 1325–1347 (2011)MathSciNetCrossRefMATH Biglarbegian, M., Melek, W., Mendel, J.: On the robustness of type-1 and interval type-2 fuzzy logic systems in modeling. Inf. Sci. 181(7), 1325–1347 (2011)MathSciNetCrossRefMATH
6.
Zurück zum Zitat Monirul Islam, Md., Murase, K.: A new algorithm to design compact two-hidden-layer artificial neural networks. Neural Netw. 14(9), 1265–1278 (2001) Monirul Islam, Md., Murase, K.: A new algorithm to design compact two-hidden-layer artificial neural networks. Neural Netw. 14(9), 1265–1278 (2001)
8.
Zurück zum Zitat Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-Fuzzy and Soft Computing: a Computational Approach to Learning and Machine Intelligence. Ed. Prentice Hall, p. 614 (1997) Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-Fuzzy and Soft Computing: a Computational Approach to Learning and Machine Intelligence. Ed. Prentice Hall, p. 614 (1997)
9.
Zurück zum Zitat Haupt, R., Haupt, S.: Practical Genetic Algorithms, p. 272. Ed. John Wiley and Sons, Inc., Hoboken, New Jersey (2004) Haupt, R., Haupt, S.: Practical Genetic Algorithms, p. 272. Ed. John Wiley and Sons, Inc., Hoboken, New Jersey (2004)
11.
Zurück zum Zitat Ma, L., Wang, Y., Tan, T.: Iris recognition based on multichannel Gabor filtering. In: Melbourne, Australia, ACCV2002. 5th Asian Conference on Computer Vision, vol. 1, pp. 279–283 (2002) Ma, L., Wang, Y., Tan, T.: Iris recognition based on multichannel Gabor filtering. In: Melbourne, Australia, ACCV2002. 5th Asian Conference on Computer Vision, vol. 1, pp. 279–283 (2002)
12.
Zurück zum Zitat Muron, A., Pospisil, J.: The human iris structure and its usages. Czech Republic, Physica, pp. 89–95 (2000) Muron, A., Pospisil, J.: The human iris structure and its usages. Czech Republic, Physica, pp. 89–95 (2000)
13.
Zurück zum Zitat Mackey, M.C.: Adventures in Poland: having fun and doing research with Andrzej Lasota. Mat. Stosow 5–32 (2007) Mackey, M.C.: Adventures in Poland: having fun and doing research with Andrzej Lasota. Mat. Stosow 5–32 (2007)
14.
Zurück zum Zitat Mackey, M.C., Glass, L.: Oscillation and chaos in physiological control systems. Science 197, 287–289 (1997)CrossRef Mackey, M.C., Glass, L.: Oscillation and chaos in physiological control systems. Science 197, 287–289 (1997)CrossRef
15.
Zurück zum Zitat Melin, P., Castillo, O., Gonzalez, S., Cota, J., Trujillo, W., Osuna, P.: Design of Modular Neural Networks with Fuzzy Integration Applied to Time Series Prediction, vol. 41, pp. 265–273. Springer, Berlin (2007) Melin, P., Castillo, O., Gonzalez, S., Cota, J., Trujillo, W., Osuna, P.: Design of Modular Neural Networks with Fuzzy Integration Applied to Time Series Prediction, vol. 41, pp. 265–273. Springer, Berlin (2007)
18.
Zurück zum Zitat Castillo, O., Melin, P.: A review on the design and optimization of interval type-2 fuzzy controllers. Appl. Soft Comput. 12(4), 1267–1278 (2012)CrossRef Castillo, O., Melin, P.: A review on the design and optimization of interval type-2 fuzzy controllers. Appl. Soft Comput. 12(4), 1267–1278 (2012)CrossRef
19.
Zurück zum Zitat Melin, P.: Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition, pp. 1–204. Springer (2012) Melin, P.: Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition, pp. 1–204. Springer (2012)
20.
Zurück zum Zitat Hagras, H.: Type-2 fuzzy logic controllers: a way forward for fuzzy systems in real world environments. In: IEEE World Congress on Computational Intelligence, pp. 181–200 (2008) Hagras, H.: Type-2 fuzzy logic controllers: a way forward for fuzzy systems in real world environments. In: IEEE World Congress on Computational Intelligence, pp. 181–200 (2008)
21.
Zurück zum Zitat Sepúlveda, R., Castillo, O., Melin, P., Montiel, O.: An efficient computational method to implement type-2 fuzzy logic in control applications. Analysis and Design of Intelligent Systems using Soft Computing Techniques, pp. 45–52 (2007) Sepúlveda, R., Castillo, O., Melin, P., Montiel, O.: An efficient computational method to implement type-2 fuzzy logic in control applications. Analysis and Design of Intelligent Systems using Soft Computing Techniques, pp. 45–52 (2007)
22.
Zurück zum Zitat Castro, J., Castillo, O., Melin, P., Rodríguez-Díaz, A.: A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks. Inf. Sci. 179(13), 2175–2193 (2009)CrossRefMATH Castro, J., Castillo, O., Melin, P., Rodríguez-Díaz, A.: A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks. Inf. Sci. 179(13), 2175–2193 (2009)CrossRefMATH
23.
Zurück zum Zitat Hidalgo, D., Melin, P., Castillo, O.: An optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty using genetic algorithms. Expert Syst. Appl. 39, 4590–4598 (2012)CrossRef Hidalgo, D., Melin, P., Castillo, O.: An optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty using genetic algorithms. Expert Syst. Appl. 39, 4590–4598 (2012)CrossRef
24.
Zurück zum Zitat Montiel, O., Castillo, O., Melin, P., Sepúlveda, R.: The evolutionary learning rule for system identification. Appl. Soft Comput. 3(4), 343–352 (2003)CrossRef Montiel, O., Castillo, O., Melin, P., Sepúlveda, R.: The evolutionary learning rule for system identification. Appl. Soft Comput. 3(4), 343–352 (2003)CrossRef
Metadaten
Titel
Problem Statement and Development
verfasst von
Fernando Gaxiola
Patricia Melin
Fevrier Valdez
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-34087-6_3