DOI

The paper is a continuation of the works [1–4] where has been shown how the technologies of machine learning and online analytical processing (OLAP) could be used in conjunction with the numerical model of convective cloud for forecasting dangerous convective phenomena such as thunderstorm, heavy rainfall and hail. We study specifically the possibility of making predictions via a hybrid approach that combines the predictive numerical model of convective cloud with the modern methods of big data processing. We overview the existing examples of using of machine learning tools for weather forecasting and discuss the range of their applicability.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017
EditorsAna Maria A.C. Rocha, Elena Stankova, Sanjay Misra, Giuseppe Borruso, Alfredo Cuzzocrea, David Taniar, Osvaldo Gervasi, Beniamino Murgante, Carmelo M. Torre, Bernady O. Apduhan
PublisherSpringer Nature
Pages495-504
Number of pages10
ISBN (Print)9783319624037
DOIs
StatePublished - 2017
Event17th International Conference on Computational Science and Its Applications, ICCSA 2017 - Trieste, Italy
Duration: 2 Jul 2017 → 5 Jul 2017
Conference number: 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10408 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Computational Science and Its Applications, ICCSA 2017
Abbreviated titleICCSA 2017
Country/TerritoryItaly
CityTrieste
Period2/07/17 → 5/07/17

    Research areas

  • Data mining, Machine learning, Multidimensional data base, Numerical model of convective cloud, OLAP, Online analytical processing, Thunderstorm, Validation of numerical models, Weather forecasting

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 97812584