Time series forecasting by generalized regression neural networks trained with multiple series

HIGHLIGHTS

• who: With Multiple Series and collaborators from the Department of Computer Science, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Jau00e9n, Jau00e9n, Spain have published the article: Time Series Forecasting by Generalized Regression Neural Networks Trained With Multiple Series, in the Journal: (JOURNAL)
• what: If the null hypothesis (i.e., the average rank of all the approaches over the test sets are the same) is rejected, the post-hoc Nemenyi test is used to see whether there are differences between any two models.
• how: Several approaches are proposed including . . .
  

   

  

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