Local averaging optimization for chaotic time series prediction
نویسندگان
چکیده
منابع مشابه
Local averaging optimization for chaotic time series prediction
Local models have emerged as one of the most accurate methods of time series prediction, but their performance is sensitive to the choice of user-specified parameters such as the size of the neighborhood, the embedding dimension, and the distance metric. This paper describes a new method of optimizing these parameters to minimize the multi-step cross-validation error. Empirical results indicate...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2002
ISSN: 0925-2312
DOI: 10.1016/s0925-2312(01)00647-6