Abstract
A new point-tree data structure genetic programming (PTGP) method is proposed. For the discontinuous function regression problem, the proposed method is able to identify both the function structure and discontinuities points simultaneously. It is also easy to be used to solve the continuous function’s regression problems. The numerical experiment results demonstrate that the point-tree GP is an efficient alternative way to the complex function identification problems.
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Foundation item: Supported by the National Natural Science Foundation (60173046) and the Natural Science Foundation of Hubei Province (2002AB040)
Biography: Xiong Sheng-wu (1966-), male, Associate professor, research direction: evolutionary computing, parallel computing.
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Sheng-wu, X., Wei-wu, W. Point-tree structure genetic programming method for discontinuous function’s regression. Wuhan Univ. J. of Nat. Sci. 8, 323–326 (2003). https://doi.org/10.1007/BF02899503
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DOI: https://doi.org/10.1007/BF02899503