SHORT-RANGE VISIBILITY FORECAST BY MEANS OF NEURAL-NETWORK MODELING - A CASE-STUDY

被引：27

作者：

PASINI, A

POTESTA, S

机构：

[1] Servizio Meterologico dell'Aeronautica, 2o CMR Aeroporto De Bernardi, Pratica di Mare (Roma), I-00040, Via di Pratica di Mare

来源：

NUOVO CIMENTO DELLA SOCIETA ITALIANA DI FISICA C-GEOPHYSICS AND SPACE PHYSICS | 1995年 / 18卷 / 05期

关键词：

Meteorology;

D O I：

10.1007/BF02506781

中图分类号：

学科分类号：

摘要：

A neural-network approach to a hetero-associative prognostic problem in the field of meteorology is presented. In particular, the application to the short-range visibility forecast of a neural back-propagation model with adaptive training and test procedures is considered. Our case-study leads to the following results: we achieve a better theoretical understanding of the behaviour of neural networks handling meteorological data (for example, the phenomenon of ''network overfitting'' and a seasonal-change influence on the performance of the model are recognised); the forecast performances of the network are always better than the persistence and subjective forecasts (in particular, the forecast of the visibility tendency is very good).

引用

页码：505 / 516

页数：12

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