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Parallel evolutionary modeling for nonlinear ordinary differential equations

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Wuhan University Journal of Natural Sciences

Abstract

We introduce a new parallel evolutionary algorithm in modeling dynamic systems by nonlinear higher-order ordinary differential equations (NHODEs). The NHODEs models are much more universal than the traditional linear models. In order to accelerate the modeling process, we propose and realize a parallel evolutionary algorithm using distributed CORBA object on the heterogeneous networking. Some numerical experiments show that the new algorithm is feasible and efficient.

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References

  1. Gan Ren-chu.The Statistical Analysis of Dynamic Data. Bei**g: USTB Press, 1991(Ch).

    Google Scholar 

  2. Koza J R.Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, MA: MIT Press, 1992.

    MATH  Google Scholar 

  3. Cao Hong-qing. Evolutionary Modeling of Complex Systems Based on Genetic Programming. [Ph. D. Thesis] Wuhan: wuhan University, 1999(Ch).

    Google Scholar 

  4. Guo Tao. Evolutionary Computation and Optimization. [Ph. D. Thesis], Wuhan: Wuhan University, 1999(Ch).

    Google Scholar 

  5. Liu Pu. PJVM. Object Oriented Parallel and Distributed System Based on Java.Computer Development and Research, 1998,35(6): 491–495.

    Google Scholar 

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Foundation item: Supported by the National Natural Science Foundation of China (No. 70071042 and No. 60073043)

Biography: Kang Zhuo (1970-), male, Lecturer, research interest: network computing and evolutionary computation.

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Zhuo, K., Pu, L. & Li-shan, K. Parallel evolutionary modeling for nonlinear ordinary differential equations. Wuhan Univ. J. Nat. Sci. 6, 659–664 (2001). https://doi.org/10.1007/BF02830279

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  • DOI: https://doi.org/10.1007/BF02830279

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