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2015 | OriginalPaper | Buchkapitel

Hybrid BFO-PSO and Kernel FCM for the Recognition of Pilot Performance Influenced by Simulator Movement Using Diffusion Maps

verfasst von : Jia Bo, Yin-Bo Zhang, Lu Ding, Bi-Ting Yu, Qi Wu, Shan Fu

Erschienen in: Digital Human Modeling. Applications in Health, Safety, Ergonomics and Risk Management: Ergonomics and Health

Verlag: Springer International Publishing

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Abstract

This paper proposed a novel data reduction and classification method to analyze high-dimensional and complicated flight data. This method integrated diffusion maps and kernel fuzzy c-means algorithm (KFCM) to recognize two types of simulator modes at different tasks. To optimize the unknown parameters of the KFCM, a hybrid bacterial foraging oriented (BFO) and particle swarm optimization (PSO) algorithm was also presented in this paper. This algorithm increased the possibility of finding the optimal values within a short computational time and avoided to be trapped in the local minima. By using the proposed approach, this paper obtained meaningful clusters respecting the intrinsic geometry of the standard data set, and illustrated the phenomenon that the pilots vestibular influenced pilot performance and control system under the Manual departure task.

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Literatur
1.
2.
Zurück zum Zitat Torrence, C., Compo, G.P.: A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79(1), 61–78 (1998)CrossRef Torrence, C., Compo, G.P.: A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79(1), 61–78 (1998)CrossRef
3.
Zurück zum Zitat Coifman, R.R., Lafon, S., Lee, A.B., Maggioni, M., Nadler, B., Warner, F., Zucker, S.W.: Geometric diffusions as a tool for harmonic analysis and structure definition of data: diffusion maps. Proc. Nat. Acad. Sci. U.S.A. 102(21), 7426–7431 (2005)CrossRef Coifman, R.R., Lafon, S., Lee, A.B., Maggioni, M., Nadler, B., Warner, F., Zucker, S.W.: Geometric diffusions as a tool for harmonic analysis and structure definition of data: diffusion maps. Proc. Nat. Acad. Sci. U.S.A. 102(21), 7426–7431 (2005)CrossRef
4.
Zurück zum Zitat Jaakkola, M.S.T., Szummer, M.: Partially labeled classification with markov random walks. Adv. Neural Inform. Proc. Syst. (NIPS) 14, 945–952 (2002) Jaakkola, M.S.T., Szummer, M.: Partially labeled classification with markov random walks. Adv. Neural Inform. Proc. Syst. (NIPS) 14, 945–952 (2002)
5.
Zurück zum Zitat Nadler, B., Lafon, S., Coifman, R.R., Kevrekidis, I.G.: Diffusion maps, spectral clustering and reaction coordinates of dynamical systems. Appl. Comput. Harmonic Anal. 21(1), 113–127 (2006)MathSciNetCrossRef Nadler, B., Lafon, S., Coifman, R.R., Kevrekidis, I.G.: Diffusion maps, spectral clustering and reaction coordinates of dynamical systems. Appl. Comput. Harmonic Anal. 21(1), 113–127 (2006)MathSciNetCrossRef
6.
Zurück zum Zitat Kim, D.-W., Lee, K.Y., Lee, D., Lee, K.H.: Evaluation of the performance of clustering algorithms in kernel-induced feature space. Pattern Recogn. 38(4), 607–611 (2005)CrossRef Kim, D.-W., Lee, K.Y., Lee, D., Lee, K.H.: Evaluation of the performance of clustering algorithms in kernel-induced feature space. Pattern Recogn. 38(4), 607–611 (2005)CrossRef
7.
Zurück zum Zitat Graves, D., Pedrycz, W.: Performance of kernel-based fuzzy clustering. Electron. Lett. 43(25), 1445–1446 (2007)CrossRef Graves, D., Pedrycz, W.: Performance of kernel-based fuzzy clustering. Electron. Lett. 43(25), 1445–1446 (2007)CrossRef
8.
Zurück zum Zitat Graves, D., Pedrycz, W.: Kernel-based fuzzy clustering and fuzzy clustering: a comparative experimental study. Fuzzy Sets Syst. 161(4), 522–543 (2010)MathSciNetCrossRef Graves, D., Pedrycz, W.: Kernel-based fuzzy clustering and fuzzy clustering: a comparative experimental study. Fuzzy Sets Syst. 161(4), 522–543 (2010)MathSciNetCrossRef
9.
Zurück zum Zitat Zhang, D.-Q., Chen, S.-C.: A novel kernelized fuzzy c-means algorithm with application in medical image segmentation. Artif. Intell. Med. 32(1), 37–50 (2004)CrossRef Zhang, D.-Q., Chen, S.-C.: A novel kernelized fuzzy c-means algorithm with application in medical image segmentation. Artif. Intell. Med. 32(1), 37–50 (2004)CrossRef
10.
Zurück zum Zitat Maulik, U., Bandyopadhyay, S.: Genetic algorithm-based clustering technique. Pattern Recogn. 33(9), 1455–1465 (2000)CrossRef Maulik, U., Bandyopadhyay, S.: Genetic algorithm-based clustering technique. Pattern Recogn. 33(9), 1455–1465 (2000)CrossRef
11.
Zurück zum Zitat Premalatha, K., Natarajan, A.: A new approach for data clustering based on pso with local search. Comput. Inform. Sci. 1(4), p. 139 (2008) Premalatha, K., Natarajan, A.: A new approach for data clustering based on pso with local search. Comput. Inform. Sci. 1(4), p. 139 (2008)
12.
Zurück zum Zitat Wan, M., Li, L., Xiao, J., Wang, C., Yang, Y.: Data clustering using bacterial foraging optimization. J. Intell. Inf. Syst. 38(2), 321–341 (2012)CrossRef Wan, M., Li, L., Xiao, J., Wang, C., Yang, Y.: Data clustering using bacterial foraging optimization. J. Intell. Inf. Syst. 38(2), 321–341 (2012)CrossRef
13.
Zurück zum Zitat Selim, S.Z., Alsultan, K.: A simulated annealing algorithm for the clustering problem. Pattern Recognit. 24(10), 1003–1008 (1991)MathSciNetCrossRef Selim, S.Z., Alsultan, K.: A simulated annealing algorithm for the clustering problem. Pattern Recognit. 24(10), 1003–1008 (1991)MathSciNetCrossRef
Metadaten
Titel
Hybrid BFO-PSO and Kernel FCM for the Recognition of Pilot Performance Influenced by Simulator Movement Using Diffusion Maps
verfasst von
Jia Bo
Yin-Bo Zhang
Lu Ding
Bi-Ting Yu
Qi Wu
Shan Fu
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-21070-4_24

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