Parameter adaptation for GP forecasting applications

Studies in Computational Intelligence

Volumn 54, Issue , 2007, Pages 295-309

  Wagner, Neal ^a   Michalewicz, Zbigniew ^b,c,d  

^a AUGUSTA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF ADELAIDE   (Australia)

^c INSTITUTE OF COMPUTER SCIENCE   (Poland)

^d POLISH JAPANESE INSTITUTE OF INFORMATION TECHNOLOGY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34147157901     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-69432-8_15     Document Type: Article

References (42)

1. Andrew M. and Prager R. 'Genetic programming for the acquistion of double auction market strategies.' Advances in Genetic Programming vol. 1 (1994), pg. 355-368.
2. Angeline P. 'Genetic programming and emergent intelligence.' Advances in Genetic Programming, vol. 1 (1994), pg. 75-98.
3. Banzhaf W. and Langdon W. 'Some considerations on the reason for bloat.' Genetic Programming and Evolvable Machines, vol. 3 (2002), pg. 81-91.
4. Chambers L., editor. Practical Handbook of Genetic Algorithms: Applications. CRC Press, 1995.
5. Chen S. and Yeh C. 'Toward a computable approach to the efficient market hypothesis: An application of genetic programming.' Journal of Economics Dynamics and Control, vol. 21 (1996), pg. 1043-1063.
6. Chen S., Yeh C., and Lee W. 'Option pricing with genetic programming.' Genetic Programming 1998: Proceedings of the Third Annual Conference vol. 1 (1998), pg. 32-37.
7. Chiraphadhanakul S., Dangprasert P., and Avatchanakorn V. 'Genetic algorithms in forecasting commercial banks deposit.' Proceedings of the IEEE International Conference on Intelligent Processing Systems, vol. 1 (1997), pg. 557-565.
8. Deboeck G., editor. Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic and Financial Markets. John Wiley and Sons, Inc., 1994.
9. Diebold F. Elements of Forecasting. International Thomson Publishing, 1998.
10. Fernandez T. and Evett M. 'Training period size and evolved trading systems.' Genetic Programming 1997: Proceedings of the Second Annual Conference, vol. 1 (1997), pg. 95.
11. Gately E. Neural Networks for Financial Forecasting. John Wiley and Sons, Inc., 1996.
12. Gathercole C. and Ross P. 'Small populations over many generations cand beat large populations over few generations in genetic programming.' Genetic Programming 1997: Proceedings of the Second Annual Conference vol. 1 (1997), pg. 111-118.
13. Goto Y., Yukita K., Mizuno K., and Ichiyanagi K. 'Daily peak load forecasting by structured representation on genetic algorithms for function fitting.' Transactions of the Institute of Electrical Engineers of Japan, vol. 119 (1999), pg. 735-736.
14. Hiden H., McKay B., Willis M., and Tham M. 'Non-linear partial least squares using genetic programming.' Genetic Programming 1998: Proceedings of the Third Annual Conference, vol. 1 (1998), pg. 128-133.
15. Iba H. and Sasaki T. 'Using genetic programming to predict financial data.' Proceedings of the Congress of Evolutionary Computation, vol. 1 (1999), pg. 244-251.
16. Iba H. and Nikolaev N. 'Genetic programming polynomial models of financial data series.' Proceedings of the 2000 Congress of Evolutionary Computation, vol. 1 (2000), pg. 1459-1466.
17. Jeong B., Jung H., Park N. 'A computerized causal forecasting system using genetic algorithms in supply chain management.' The Journal of Systems and Software, vol. 60 (2002), pg. 223-237.
18. de Jong E., Watson R., and Pollack J. 'Reducing bloat and promoting diversity using multi-objective methods.' Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), vol. 1 (2001), pg. 11-18.
19. Jonsson P. and Barklund J. 'Characterizing signal behavior using genetic programming.' Evolutionary Computing: Lecture Notes in Computer Science, vol. 1143 (1996), pg. 62-72.
20. Ju Y., Kim C., and Shim J. 'Genetic based fuzzy models: Interest rate forecasting problem.' Computers and Industrial Engineering, vol. 33 (1997), pg. 561-564.
21. Kaboudan M. 'Forecasting with computer-evolved model specifications: A genetic programming application.' Computer and Operations Research vol. 30 (2003), pg. 1661-1681.
22. Kaboudan M. 'Genetically evolved models and normality of their residuals.' Journal of Economics Dynamics and Control, vol. 25 (2001), pg. 1719-1749.
23. Kaboudan M. 'Forecasting stock returns using genetic programming in C++.' Proceedings of 11th Annual Florida Artificial Intelligence International Research Symposium, vol. 1 (1998), pg. 502-511.
24. Kaboudan M. 'Genetic programming prediction of stock prices.' Computational Economics, vol. 6 (2000), pg. 207-236.
25. Kaboudan M. 'Genetic evolution of regression models for business and economic forecasting.' Proceedings of the Congress of Evolutionary Computation, vol. 2 (1999), pg. 1260-1268.
26. Kaboudan M. 'A measure of time series' predictability using genetic programming applied to stock returns.' Journal of Forecasting, vol. 18 (1999), pg. 345-357.
27. Kim D. and Kim C. 'Forecasting time series with genetic fuzzy predictor ensemble.' IEEE Transactions on Fuzzy Systems, vol. 5 (1997), pg. 523-535.
28. Kitchen J. and Monaco R. 'Real-time forecasting in practice.' Business Economics: The Journal of the National Association of Business Economists, vol. 38 (2003), pg. 10-19.
29. Koza J. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, 1992.
30. Langdon W. 'The evolution of size in variable length representations.' 1998 IEEE International Conference of Evolutionary Computation, vol. 1 (1998), pg. 633-638.
31. Langdon W. and Poli R. 'Fitness causes bloat.' Soft Computing in Engineering Design and Manufacturing, vol. 1 (1997), pg. 13-22.
32. Lee D., Lee B., and Chang S. 'Genetic programming model for long-term forecasting of electric power demand.' Electric Power Systems Research, vol. 40 (1997), pg. 17-22.
33. Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, 1992.
34. Eiben A., Hinterding R., and Michalewicz Z. 'Parameter control in evolutionary algorithms.' IEEE Transactions on Evolutionary Computation, vol. 3 (1999), pg. 124-141.
35. Mulloy B., Riolo R., and Savit R. 'Dynamics of genetic programming and chaotic time series prediction.' Genetic Programming 1996: Proceedings of the First Annual Conference, vol. 1 (1996), pg. 166-174.
36. Neely C. and Weller P. 'Predicting exchange rate volatility: Genetic programming versus GARCH and RiskMetrics™.' The Federal Reserve Bank of St. Louis, (2002).
37. Smith K., Gupta J. Neural Networks in Business: Techniques and Applications. Idea Group Pub., 2002.
38. Trippi R., Turban E., editors. Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance. Irwin Professional Pub., 1996.
39. U.S. Department of Commerce Bureau of Economic Analysis. http://www.bea.doc.gov/bea/glossary/glossary g.htm, 2004.
40. Venkatesan R. and Kumar V. 'A genetic algorithms approach to growth phase forecasting of wireless subscribers.' International Journal of Forecasting, vol. 18 (2002), pg. 625-646.
41. Wagner N. and Michalewicz Z. 'Genetic programming with efficient population control for financial times series prediction.' 2001 Genetic and Evolutionary Computation Conference Late Breaking Papers, vol. 1 (2001), pg. 458-462.
42. Wagner N., Michalewicz Z., Khouja M., and McGregor R. 'Time series forecasting for dynamic environments: The DyFor genetic program model.' To appear in IEEE Transactions on Evolutionary Computation, 2006.