Skip to main content

2016 | OriginalPaper | Buchkapitel

Fuzzy C-Means and Fuzzy TLBO for Fuzzy Clustering

verfasst von : P. Gopala Krishna, D. Lalitha Bhaskari

Erschienen in: Proceedings of the Second International Conference on Computer and Communication Technologies

Verlag: Springer India

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

search-config
loading …

Abstract

The choice of initial center plays a great role in achieving optimal clustering results in all partitional clustering approaches. Fuzzy C-means is a widely used approach but it also gets trapped in local optima values due to sensitiveness to initial cluster centers. To alleviate this issue, a new approach of using an evolutionary technique known as Teaching–Learning-Based Optimization (TLBO) is used hybridized with fuzzy approach. The proposed approach is able to deal with the sensitiveness of cluster centers. Results presented are very encouraging.

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.
2.
Zurück zum Zitat Selim, S.Z., Alsultan, K.: A simulated annealing algorithm for the clustering problem. Pattern Recogn. 24(10), 1003–1008 (1991)MathSciNetCrossRef Selim, S.Z., Alsultan, K.: A simulated annealing algorithm for the clustering problem. Pattern Recogn. 24(10), 1003–1008 (1991)MathSciNetCrossRef
3.
Zurück zum Zitat Al-Sultan, K.S.: A tabu search approach to the clustering problem. Pattern Recogn. 28(9), 1443–1451 (1995)CrossRef Al-Sultan, K.S.: A tabu search approach to the clustering problem. Pattern Recogn. 28(9), 1443–1451 (1995)CrossRef
4.
Zurück zum Zitat Hall, L.O., Ozyurt, I.B., Bezdek, J.C.: Clustering with a genetically optimized approach. IEEE Trans. Evol. Comput. 3(2), 103–112 (1999)CrossRef Hall, L.O., Ozyurt, I.B., Bezdek, J.C.: Clustering with a genetically optimized approach. IEEE Trans. Evol. Comput. 3(2), 103–112 (1999)CrossRef
5.
Zurück zum Zitat Bandyopadhyay, S., Maulik, U.: An evolutionary technique based on k-means algorithm for optimal clustering in rn. Inf. Sci. 146(1–4), 221–237 (2002)MATHMathSciNetCrossRef Bandyopadhyay, S., Maulik, U.: An evolutionary technique based on k-means algorithm for optimal clustering in rn. Inf. Sci. 146(1–4), 221–237 (2002)MATHMathSciNetCrossRef
6.
Zurück zum Zitat Lili, L., Xiyu, L., Mingming, X.: A novel fuzzy clustering based on particle swarm optimization. In: First IEEE International Symposium on Information Technologies and Applications in Education, ISITAE, pp. 88–90 (2007) Lili, L., Xiyu, L., Mingming, X.: A novel fuzzy clustering based on particle swarm optimization. In: First IEEE International Symposium on Information Technologies and Applications in Education, ISITAE, pp. 88–90 (2007)
7.
Zurück zum Zitat Kanade, P.M., Hall, L.O.: Fuzzy ants and clustering. IEEE Trans. Syst. Manage. Cybern. Part A 37(5), 758–769 (2007)CrossRef Kanade, P.M., Hall, L.O.: Fuzzy ants and clustering. IEEE Trans. Syst. Manage. Cybern. Part A 37(5), 758–769 (2007)CrossRef
8.
Zurück zum Zitat Maulik, U., Saha, I.: Modified differential evolution based fuzzy clustering for pixel classification in remote sensing imagery. Pattern Recogn. 42(9), 2135–2149 (2009)MATHCrossRef Maulik, U., Saha, I.: Modified differential evolution based fuzzy clustering for pixel classification in remote sensing imagery. Pattern Recogn. 42(9), 2135–2149 (2009)MATHCrossRef
9.
Zurück zum Zitat Paterlini, S., Krink, T.: Differential evolution and particle swarm optimisation in partitional clustering. Comput. Stat. Data Anal. 50(5), 1220–1247 (2006)MATHMathSciNetCrossRef Paterlini, S., Krink, T.: Differential evolution and particle swarm optimisation in partitional clustering. Comput. Stat. Data Anal. 50(5), 1220–1247 (2006)MATHMathSciNetCrossRef
10.
Zurück zum Zitat Rao, R.V., Savsani, V.J., Vakharia, D.P.: Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput. Aided Des. 43, 303–315 (2011)CrossRef Rao, R.V., Savsani, V.J., Vakharia, D.P.: Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput. Aided Des. 43, 303–315 (2011)CrossRef
11.
Zurück zum Zitat Rao, R.V., Savsani, V.J.: Mechanical design optimization using advanced optimization techniques. Springer, London (2012)CrossRef Rao, R.V., Savsani, V.J.: Mechanical design optimization using advanced optimization techniques. Springer, London (2012)CrossRef
12.
Zurück zum Zitat Satapathy, S.C., Naik, A.: Data clustering based on teaching-learning-based optimization. In: Swarm, Evolutionary, and Memetic Computing. Lecture Notes in Computer Science, vol. 7077, pp. 148–156. Springer, Berlin (2011) Satapathy, S.C., Naik, A.: Data clustering based on teaching-learning-based optimization. In: Swarm, Evolutionary, and Memetic Computing. Lecture Notes in Computer Science, vol. 7077, pp. 148–156. Springer, Berlin (2011)
14.
Zurück zum Zitat Satapathy, S.C., Naik, A., Parvathi, K.: Teaching learning based optimization for neural networks learning enhancement. In: LNCS, vol. 7677, pp. 761–769. Springer, Berlin (2012) Satapathy, S.C., Naik, A., Parvathi, K.: Teaching learning based optimization for neural networks learning enhancement. In: LNCS, vol. 7677, pp. 761–769. Springer, Berlin (2012)
15.
Zurück zum Zitat Satapathy, S.C., Naik, A., Parvathi, K.: 0–1 Integer Programming For Generation maintenance Scheduling in Power Systems based on Teaching Learning Based Optimization (TLBO), CCIS 306, pp. 53–63. Springer, Berlin (2012) Satapathy, S.C., Naik, A., Parvathi, K.: 0–1 Integer Programming For Generation maintenance Scheduling in Power Systems based on Teaching Learning Based Optimization (TLBO), CCIS 306, pp. 53–63. Springer, Berlin (2012)
16.
Zurück zum Zitat Satapathy, S.C., Naik, A., Parvathi, K.: Improvement of initial cluster center of c-means using Teaching learning based optimization. Elsevier, Procedia Technology 6(2012), 428–435 (2012) Satapathy, S.C., Naik, A., Parvathi, K.: Improvement of initial cluster center of c-means using Teaching learning based optimization. Elsevier, Procedia Technology 6(2012), 428–435 (2012)
17.
Zurück zum Zitat Naik, A., Parvathi, K., Satapathy, S.C., Nayak, R., Panda, B.S.: QoS Multicast Routing Using Teaching Learning Based Optimization, pp. 49–55. Springer, Berlin (2012) Naik, A., Parvathi, K., Satapathy, S.C., Nayak, R., Panda, B.S.: QoS Multicast Routing Using Teaching Learning Based Optimization, pp. 49–55. Springer, Berlin (2012)
Metadaten
Titel
Fuzzy C-Means and Fuzzy TLBO for Fuzzy Clustering
verfasst von
P. Gopala Krishna
D. Lalitha Bhaskari
Copyright-Jahr
2016
Verlag
Springer India
DOI
https://doi.org/10.1007/978-81-322-2517-1_46