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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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