Evolutionary construction and adaptation of intelligent systems

Expert Systems with Applications

Volumn 37, Issue 12, 2010, Pages 7711-7720

  Font, José M ^a   Manrique, Daniel ^a   Ríos, Juan ^a  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Artificial neural networks; Evolutionary computation; Fuzzy rule based systems; Intelligent systems; Medical prognosis; Rule based systems

Indexed keywords

CONTEXT FREE GRAMMARS; DEEP NEURAL NETWORKS; DIAGNOSIS; EVOLUTIONARY ALGORITHMS; FUZZY INFERENCE; FUZZY RULES; GENETIC ALGORITHMS; GENETIC PROGRAMMING; INTELLIGENT SYSTEMS; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; TIME SERIES ANALYSIS;

CHANGING ENVIRONMENT; EVOLUTIONARY TECHNIQUES; EXPLORATION AND EXPLOITATION; GRAMMAR GUIDED GENETIC PROGRAMMING; INITIALIZATION METHODS; MEDICAL PROGNOSIS; PERFORMANCE ANALYSIS; SELF-ADAPTING SYSTEMS;

FUZZY NEURAL NETWORKS;

EID: 77957847156     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.04.070     Document Type: Article

References (31)

1. Alonso, F., Caraça-Valente, J. P., González, A. L., & Montes, C. (2002). Combining expert knowledge and data mining in a medical diagnosis domain. Expert Systems with Applications, 23, 367-375.
2. Canales, A., Peña, A., Peredo, R., Sossa, H., & Gutiérrez, A. (2007). Adaptive and intelligent web based education system: Towards an integral architecture and framework. Expert Systems with Applications, 33(4), 1076-1089.
3. Chen, W., Tai, P., Wang, M., Deng, W., & Chen, C. (2008). A neural network-based approach for dynamic quality prediction in a plastic injection molding process. Expert Systems with Applications, 35(3), 843-849.
4. Couchet, J., Font, J. M., & Manrique, D. (2008). Using evolved fuzzy neural networks for injury detection from isokinetic curves. In Applications and innovations in intelligent systems XVI, Proceedings of the AI2008 (pp. 223-238). December 2008, Cambridge, UK.
5. Couchet, J., Font, J. M., & Manrique, D. (2009). Rule evolving system for knee lesion prognosis from medical isokinetic curves. In Bioinspired Applications in Artificial and Natural Computation, Proceedings of the IWINAC 2009 (pp. 188-197). June 2009, Spain: Santiago de Compostela.
6. Couchet, J., Manrique, D., & Porras, L. (2007). Grammar-guided neural architecture evolution. In Bio-inspired Modeling of Cognitive Tasks, Proceedings of the IWINAC 2007 (pp. 437-446). June 2007, Spain: La Manga del Mar Menor.
7. Couchet, J., Manrique, D., Ríos, J., & Rodríguez- Patón, A. (2007). Crossover and mutation operators for grammar-guided genetic programming. Soft Computing, 11, 943-955. (Pubitemid 46767700)
8. Crawford-Marks, R., & Spector, L. (2002). Size control via size fair genetic operators in the pushGP genetic programming system. In Proceedings of the genetic and evolutionary computation conference (pp. 733-739). New York, USA.
9. De Jong, K. A. (2006). Evolutionary computation: A unified approach. Cambridge, Massachusetts, USA: The MIT Press.
10. García-Arnau, M., Manrique, D., Ríos, J., & Rodríguez-Patón, A. (2007). Initialization method for grammar-guided genetic programming. Knowledge-Based Systems, 20(2), 127-133.
11. García-Pedrajas, N., Hervás-Martínez, C., & Ortíz-Boyer, D. (2005). Cooperative coevolution of artificial neural network ensembles for patterns classification. IEEE Transactions on Evolutionary Computation, 9(3), 271-302.
12. Gioftsidou, A., Ispirlidis, I., Pafis, G., Malliou, P., Bikos, C., & Godolias, G. (2008). Isokinetic strength training program for muscular imbalances in professional soccer players. Sport Sciences for Health, 2(3), 101-105.
13. Gomez, A., Juristo, N., Montes, C., & Pazos, J. (1997). Ingeniería del Conocimiento. Spain: Centro de Estudios Ramón Areces.
14. Hassoun, M. H. (1995). Fundamental of artificial neural networks. Cambridge, Massachusetts, USA: The MIT Press.
15. Hoai, N. X., & McKay, R. I. (2002). Is ambiguity useful or problematic for grammar guided genetic programminǧ A case of study. In Proceedings of the 4th Asia- Pacific conference on simulated evolution and learning (pp. 449-453). November 2002, Singapore.
16. Holland, J. H. (1992). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. Cambridge, Massachusetts, USA: The MIT Press.
17. Jones, T. (2008). Artificial intelligence: A systems approach. Hingham, Massachusetts, USA: Infinity Science Press LLL.
18. Koza, J. R. (1992). Genetic programming: On the programming of computers by means of natural selection. Cambridge, Massachusetts, USA: The MIT Press.
19. Langdon, W. B., & Poli, R. (2002). Foundations of genetic programming. London, UK: Springer-Verlag.
20. Lee, T., Wu, C., & Wei, H. (2008). KBSLUA: A knowledge-based system applied in river land use assessment. Expert Systems with Applications, 34(2), 889-899.
21. Manrique, D., Ríos, J., & Rodríguez-Patón, A. (2006). Evolutionary system for automatically constructing and adapting radial basis function networks. Neurocomputing, 69(16), 2268-2283.
22. Michal, S., Ivry, T., Schalit-Cohen, O., Sipper, M., & Barash, D. (2007). Finding a common motif of RNA sequences using genetic programming: The GeRNAMo system. IEEE Transactions on Computational Biology and Bioinformatics, 4(4), 596-610.
23. Ohsaki, M., Yokoi, H., Abe, M., Tsumoto, S., & Yamaguchi, T. (2006). Proposal of medical KDD support user interface utilizing rule interestingness measures. In Sixth IEEE international conference on data mining - Workshops, December 2006, Hong-Kong.
24. O'Neil, M., & Ryan, C. (2003). Grammatical evolution: Evolutionary automatic programming on arbitrary language (genetic programming). Norwell, USA: Kluwer Academic Publishers.
25. Panait, L., & Luke, S. (2004). Alternative bloat control methods. Lecture Notes in Computer Science, 3103, 630-641.
26. Podgorelec, V., Kokol, P., Stiglic, M., Hericko, M., & Rozman, I. (2005). Knowledge discovery with classification rules in a cardiovascular dataset. Computer Methods and Programs in Biomedicine, 80, 39-49.
27. Scully, T., Brown, K. N. (2008).Wireless LAN load-balancing with genetic algorithms. In Applications and innovations in intelligent systems XVI, Proceedings of AI2008 (pp. 3-16). December 2008, Cambridge, UK.
28. Turbam, E., Aronson, J. E., & Liang, T. (2004). Decision support systems and intelligent systems (7th ed.). Upper Saddle River, New Jersey, USA: Prentice Hall.
29. Whigham, P. A. (1995). Grammatically-based genetic programming. In Proceedings of the workshop on genetic programming: From theory to real-world applications (pp. 33-41). California, USA.
30. White, C. J., & Lakany, H. (2008). A fuzzy inference system for fault detection and isolation: Application to a fluid system. Expert Systems with Applications, 35(3), 1021-1033.
31. Wong, M. L., & Leung, K. S. (1995). Applying logic grammars to induce sub-functions in genetic programming. Evolutionary Computation, 2, 737-740.