Development and Comparison of Two Novel Hybrid Neural Network Models for Hourly Solar Radiation Pred...
Development and Comparison of Two Novel Hybrid Neural Network Models for Hourly Solar Radiation Prediction
About this item
Full title
Author / Creator
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
There are a lot of developing countries with inadequate meteorological stations to measure solar radiation. This has been a major drawback for solar power applications in these countries as the performance of the solar-powered system cannot be accurately forecasted. In this study, two novel hybrid neural networks namely; convolutional neural networ...
Alternative Titles
Full title
Development and Comparison of Two Novel Hybrid Neural Network Models for Hourly Solar Radiation Prediction
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_f573a2247b9545cd8103ef1a86daaf5a
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f573a2247b9545cd8103ef1a86daaf5a
Other Identifiers
ISSN
2076-3417
E-ISSN
2076-3417
DOI
10.3390/app12031435
