摘要
该文把时间序列建模看作是模型结构和参数的优化搜索过程,将遗传规划与遗传算法结合起来对结构和参数共存且相互影响的复杂解空间进行全局最优搜索实现模型结构和参数的共同识别。实例分析表明该方法建立的预测模型具有较高的精度和推广预测能力。
Time series modeling can be considered as optimal search processes of model structures and model parameters.A new genetic evolutionary modeling method,combining genetic programming and genetic algorithms,was proposed for hybrid identification of model structure and model parameters by performing global optimal search in the complex solution space where the structures and parameters coexist and interact.Application results proved the high precision and generalization capacity of the predicting model obtained by the new method.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第5期215-217,共3页
Computer Engineering and Applications
基金
高等学校优秀青年教师教学与科研奖励计划项目资助
关键词
时间序列建模
预测
遗传进化算法
遗传算法
遗传规划
time series modeling,prediction,genetic evolutionary algorithm,genetic algorithm,genetic programming
