Abstract
In this paper we propose a new model of a Modular Neural Network (MNN) with fuzzy integration based on granular computing. The topology and parameters of the model are optimized with a Hierarchical Genetic Algorithm (HGA). The model was applied to the case of human recognition to illustrate its applicability. The proposed method is able to divide the data automatically into sub modules, to work with a percentage of images and select which images will be used for training. We considered, to test this method, the problem of human recognition based on ear, and we used a database with 77 persons (with 4 images each person for this task).
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References
Azamm, F.: Biologically Inspired Modular Neural Networks, PhD thesis, Virginia Polytechnic Institute and State University, Blacksburg, Virginia (2000)
Bargiela, A., Pedrycz, W.: The roots of granular computing. In: Proc. IEEE Granular Computing Conf., p. 741 (2006)
Castillo, O., Melin, P.: Type-2 Fuzzy Logic Theory and Applications, pp. 29–43. Springer, Berlin (2008)
Castro, J.R., Castillo, O., Melin, P.: An Interval Type-2 Fuzzy Logic Toolbox for Control Applications. In: FUZZ-IEEE 2007, pp. 1–6 (2007)
Castro, J.R., Castillo, O., Melin, P., Rodriguez-Diaz, A.: Building Fuzzy Inference Systems with a New Interval Type-2 Fuzzy Logic Toolbox. Transactions on Computational Science 1, 104–114 (2008)
Database Ear Recognition Laboratory from the University of Science & Technology Beijing (USTB). Found on the Web page, http://www.ustb.edu.cn/resb/en/index.htmasp (accessed September 21, 2009)
Garro, B.A., Sossa, H., Vazquez, R.A.: Design of Artificial Neural Networks using a Modified Particle Swarm Optimization Algorithm. In: International Joint Conference on Neural Networks (IJCNN 2009), Atlanta, GE, USA, June 14-19, pp. 938–945 (2009)
Garro, B.A., Sossa, H., Vázquez, R.A.: Design of Artificial Neural Networks Using Differential Evolution Algorithm. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds.) ICONIP 2010, Part II. LNCS, vol. 6444, pp. 201–208. Springer, Heidelberg (2010)
Garro, B.A., Sossa, H., Vázquez, R.A.: Evolving Neural Networks: A Comparison Between Differential Evolution and Particle Swarm Optimization. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds.) ICSI 2011, Part I. LNCS, vol. 6728, pp. 447–454. Springer, Heidelberg (2011)
Gutiérrez, L., Melin, P., López, M.: Modular Neural Network for Human Recognition From Ear Images Using Wavelets. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds.) Soft Computing for Recognition Based on Biometrics. SCI, vol. 312, pp. 121–135. Springer, Heidelberg (2010)
Hidalgo, D., Castillo, O., Melin, P.: Optimization with genetic algorithms of modular neural networks using interval type-2 fuzzy logic for response integration: The case of multimodal biometry. In: IJCNN 2008, pp. 738–745 (2008)
Hidalgo, D., Castillo, O., Melin, P.: Type-1 and Type-2 Fuzzy Inference Systems as Integration Methods in Modular Neural Networks for Multimodal Biometry and Its Optimization with Genetic Algorithms. In: Soft Computing for Hybrid Intelligent Systems, pp. 89–114 (2008)
Hidalgo, D., Melin, P., Licea, G., Castillo, O.: Optimization of Type-2 Fuzzy Integration in Modular Neural Networks Using An Evolutionary Method With Applications in Multimodal Biometry. In: Aguirre, A.H., Borja, R.M., Garciá, C.A.R. (eds.) MICAI 2009. LNCS, vol. 5845, pp. 454–465. Springer, Heidelberg (2009)
Hobbs, J.R.: Granularity. In: Proceedings of the 9th International Joint Conference on Artificial Intelligence, pp. 432–435 (1985)
Huang, J., Wechsler, H.: Eye Location Using Genetic Algorithm. Department of Computer Science, George Mason University, Washington, DC (1999)
Khan, A., Bandopadhyaya, T., Sharma, S.: Classification of Stocks Using Self Organizing Map. International Journal of Soft Computing Applications 4, 19–24 (2009)
Lin, T.Y.: Granular computing, Announcement of the BISC Special Interest Group on Granular Computing (1997)
Mendel, J.: Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall, Upper Saddle River (2001)
Nawa, N., Takeshi, F., Hashiyama, T., Uchikawa, Y.: A study on the discovery of relevant fuzzy rules using pseudo-bacterial genetic algorithm. Laboratory of Bio-Electronics, Department of Information Electronics, School of Engineering, Nagoya University, Japan (1999)
Pedrycz, W.: Granular Computing: An Emerging Paradigm. Physica-Verlag, Heidelberg (2001)
Whitley, D.: A genetic algorithm tutorial. Statistics and Computing 4, 65–85 (1994)
Yao, J.T.: A ten-year review of granular computing. In: Proceedings of the 3rd IEEE International Conference on Granular Computing (2007)
Yao, J.T.: Information granulation and granular relationships. In: Proceedings of 2005 IEEE Conference on Granular Computing, Beijing, China, pp. 326–329 (2005)
Yao, Y.Y.: Granular computing: basic issues and possible solutions. In: Proceedings of the 5th Joint Conferences on Information Sciences, New Jersey, USA, pp. 186–189 (2000)
Yao, Y.: A Partition Model of Granular Computing. In: Peters, J.F., Skowron, A., Grzymała-Busse, J.W., Kostek, B.z., Świniarski, R.W., Szczuka, M.S. (eds.) Transactions on Rough Sets I. LNCS, vol. 3100, pp. 232–253. Springer, Heidelberg (2004)
Zadeh, L.A.: Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems 19, 111–127 (1997)
Zadeh, L.A.: Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems. Soft Computing 2, 23–25 (1998)
Zhang, L., Zhang, B.: The Quotient Space Theory of Problem Solving. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds.) RSFDGrC 2003. LNCS (LNAI), vol. 2639, pp. 11–15. Springer, Heidelberg (2003)
Zhang, L., Zhang, B.: Theory and Application of Problem Solving. Elsevier Science Publishers, North- Holland (1992)
Zhang, Z., Zhang, C.: An Agent-Based Hybrid Intelligent System for Financial Investment Planning. In: Ishizuka, M., Sattar, A. (eds.) PRICAI 2002. LNCS (LNAI), vol. 2417, pp. 355–364. Springer, Heidelberg (2002)
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Sánchez, D., Melin, P., Castillo, O. (2011). A New Model of Modular Neural Networks with Fuzzy Granularity for Pattern Recognition and Its Optimization with Hierarchical Genetic Algorithms. In: Batyrshin, I., Sidorov, G. (eds) Advances in Soft Computing. MICAI 2011. Lecture Notes in Computer Science(), vol 7095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25330-0_29
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DOI: https://doi.org/10.1007/978-3-642-25330-0_29
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