Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abraham A., Business Intelligence from Web Usage Mining, Journal of Information and Knowledge Management (JIKM), World Scientific Publishing Co., Singapore, Volume 2, No. 4, pp. 1–15, 2003.
Abraham A., EvoNF: A Framework for Optimization of Fuzzy Inference Systems Using Neural Network Learning and Evolutionary Computation, 2002 IEEE International Symposium on Intelligent Control (ISIC’02), Canada, IEEE Press, pp. 327–332, 2002.
Abraham A., i-Miner: A Web Usage Mining Framework Using Hierarchical Intelligent Systems, The IEEE International Conference on Fuzzy Systems FUZZIEEE’03, IEEE Press, pp. 1129–1134, 2003.
Abraham A., Neuro-Fuzzy Systems: State-of-the-Art Modeling Techniques, Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence, LNCS 2084, Mira J. and Prieto A. (Eds.), Springer-Verlag Germany, pp. 269–276, 2001.
Abraham A., Intelligent Systems: Architectures and Perspectives, Recent Advances in Intelligent Paradigms and Applications, Abraham A., Jain L. and Kacprzyk J. (Eds.), Studies in Fuzziness and Soft Computing, Springer Verlag Germany, Chap. 1, pp. 1–35, 2002.
Abraham A., Meta-Learning Evolutionary Artificial Neural Networks, Neurocomputing Journal, Elsevier Science, Netherlands, Vol. 56c, pp. 1–38, 2004.
Abraham A. and Nath B., Evolutionary Design of Fuzzy Control Systems — An Hybrid Approach, The Sixth International Conference on Control, Automation, Robotics and Vision, (ICARCV 2000), CD-ROM Proceeding, Wang J.L. (Ed.), ISBN 9810434456, Singapore, 2000.
Abraham A. and Nath B., Evolutionary Design of Neuro-Fuzzy Systems — A Generic Framework, In Proceedings of The 4-th Japan-Australia JointWorkshop on Intelligent and Evolutionary Systems, Namatame A. et al (Eds.), Japan, pp. 106–113, 2000.
Bezdek J.C., Pattern Recognition with Fuzzy Objective Function Algorithms, New York: Plenum Press, 1981.
Cordón O., Herrera F., Hoffmann F., and Magdalena L., Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, World Scientific Publishing Company, Singapore, 2001.
Edwards R., Abraham A. and Petrovic-Lazarevic S., Export Behaviour Modeling Using EvoNF Approach, The International Conference on Computational Science (ICCS 2003), Springer Verlag, Lecture Notes in Computer Science-Volume 2660, Sloot P.M.A. et al (Eds.), pp. 169–178, 2003.
Hall L.O., Ozyurt I.B., and Bezdek J.C., Clustering with a Genetically Optimized Approach, IEEE Transactions on Evolutionary Computation, Vol. 3, No. 2, pp. 103–112, 1999.
Jang J.S.R., ANFIS: Adaptive-Network-BasedFuzzy Inference System, IEEE Transactions in Systems Man and Cybernetics, Vol. 23, No. 3, pp. 665–685, 1993.
Jayalakshmi G.A., Sathiamoorthy S. and Rajaram, An Hybrid Genetic Algorithm — A New Approach to Solve Traveling Salesman Problem, International Journal of Computational Engineering Science, Vol. 2, No. 2, pp. 339–355, 2001.
Kandel A. and Langholz G. (Eds.), Hybrid Architectures for Intelligent Systems, CRC Press, 1992.
Lotfi A., Learning Fuzzy Inference Systems, PhD Thesis, Department of Electrical and Computer Engineering, University of Queensland, Australia, 1995.
Medsker L.R., Hybrid Intelligent Systems, Kluwer Academic Publishers, 1995.
Pedrycz W. (Ed.), Fuzzy Evolutionary Computation, Kluwer Academic Publishers, USA, 1997.
Procyk T.J. and Mamdani E.H., A Linguistic Self Organising Process Controller, Automatica, Vol. 15, no. 1, pp. 15–30, 1979.
Sanchez E., Shibata T. and Zadeh L.A. (Eds.), Genetic Algorithms and Fuzzy Logic Systems: Soft Computing Perspectives, World Scientific Publishing Company, Singapore, 1997.
Stepniewski S.W. and Keane A.J., Pruning Back-propagation Neural Networks Using Modern Stochastic Optimization Techniques, Neural Computing & Applications, Vol. 5, pp. 76–98, 1997.
Sugeno M. and Tanaka K., Successive Identification of a Fuzzy Model and its Applications to Prediction of a Complex System, Fuzzy Sets Systems, Vol. 42, no. 3, pp. 315–334, 1991.
Wang L.X. and Mendel J.M., Backpropagation Fuzzy System as Nonlinear Dynamic System Identifiers, In Proceedings of the First IEEE International conference on Fuzzy Systems, San Diego, USA, pp. 1409–1418, 1992.
Wang L.X. and Mendel J.M., Generating Fuzzy Rules by Learning from Examples, IEEE Transactions in Systems Man and Cybernetics, Vol. 22, pp. 1414–1427, 1992.
Wang L.X., Adaptive Fuzzy Systems and Control, Prentice Hall Inc, USA, 1994.
Wang X., Abraham A. and Smith K.A, Soft Computing Paradigms for Web Access Pattern Analysis, Proceedings of the 1st International Conference on Fuzzy Systems and Knowledge Discovery, pp. 631–635, 2002.
Zadeh L.A., Roles of Soft Computing and Fuzzy Logic in the Conception, Design and Deployment of Information/Intelligent Systems, Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications, Kaynak O. et al (Eds.), pp. 1–9, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Abraham, A. (2005). Hybrid Intelligent Systems: Evolving Intelligence in Hierarchical Layers. In: Gabrys, B., Leiviskä, K., Strackeljan, J. (eds) Do Smart Adaptive Systems Exist?. Studies in Fuzziness and Soft Computing, vol 173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32374-0_8
Download citation
DOI: https://doi.org/10.1007/3-540-32374-0_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24077-8
Online ISBN: 978-3-540-32374-7
eBook Packages: EngineeringEngineering (R0)