An evolutionary algorithm for controlling chaos: The use of multi–objective fitness functions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2439, Issue , 2002, Pages 308-317

  Richter, Hendrik ^a  

^a FRAUNHOFER INSTITUTE FOR MANUFACTURING ENGINEERING AND AUTOMATION IPA   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

HEALTH;

CONTROLLING CHAOS; DRIVING FORCES; FITNESS FUNCTIONS; LOCAL CONTROL; NUMERICAL RESULTS; OBJECTIVE FUNCTIONS;

EVOLUTIONARY ALGORITHMS;

EID: 84944318273     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45712-7_30     Document Type: Conference Paper

References (17)

1. Bäck, T.: Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press, New York (1996)
2. Baier, G., Klein, M.: Maximum hyperchaos in generalized Hénon maps. Phys. Lett. A151 (1990) 281-284
3. Fletcher, R.: Practical Methods of Optimization. John Wiley, Chichester (1987)
4. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addision-Wesley, Reading MA (1989)
5. Kailath, T.: Linear Systems. Prentice-Hall, Englewood Cliffs NJ (1980)
6. Lin, C.T., Jou, C.P.: Controlling chaos by GA-based reinforcement learning neural network. IEEE Trans. Neural Networks 10 (1999) 846-859
7. Marin, J., Solé, R.V.: Controlling chaos in unidimensional maps using macroevolutionary algorithms. Phys. Rev. E65 (2002) 026207/1-6
8. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. 3rd edn. Springer-Verlag, Berlin Heidelberg New York (1996)
9. Ott, E.: Chaos in Dynamical Systems. Cambridge University Press, Cambridge (1993)
10. Packard, H.N.: A genetic learning algorithm for the analysis of complex data. Complex Systems 4 (1990) 543-572
11. Paterakis, E., Petridis, V., Kehagias, A.: Genetic algorithm in parameter estimation of nonlinear dynamical systems. In: Eiben, A.E., Bäck,T., Schoenauer, M., Schwefel, H.P. (eds.): Parallel Problem Solving from Nature - PPSN V. Springer-Verlag, Berlin Heidelberg New York (1998) 1008-1017
12. Richter, H., Reinschke, K.J.: Local control of chaotic systems: A Lyapunov approach. Int. J. Bifurcation and Chaos 8 (1998) 1565-1573
13. Richter, H., Reinschke, K.J.: Optimization of local control of chaos by an evolutionary algorithms. Physica D144 (2000) 309-334
14. Rodriguez-Vázquez, K., Fleming, P.J.: Multi-objective genetic programming for dynamic chaotic systems modelling. In: Congress on Evolutionary Computation, CEC’99, Washington, D.C., USA, (1999) 22-28
15. Szpiro, G.G.: Forecasting chaotic time series with genetic algorithms. Phys. Rev. E55 (1997) 2557-2568
16. Weeks, E.R., Burgess, J.M.: Evolving artificial neural networks to control chaotic systems. Phys. Rev. E56 (1997) 1531-1540
17. Yadavalli, V.K, Dahulee, R.K., Tambe, S.S., Kulkarni, B.D.: Obtaining functional form of chaotic time series evolution using genetic algorithm. Chaos 9 (1999) 789-794