In the present work we use the technologies of machine learning and OLAP for more accurate forecasting of such phenomena as a thunderstorm, hail, heavy rain, using the numerical model of convective cloud. Three methods of machine learning: support vector machine, logistic regression and ridge regression are used for making the decision on whether or not a dangerous convective phenomenon occurs at present atmospheric conditions. The OLAP technology is used for development of the concept of multidimensional data base intended for distinguishing the types of the phenomena (thunderstorm, heavy rainfall and light rain). Previously developed complex information system is used for collecting the data about the state of the atmosphere and about the place and at the time when dangerous convective phenomena are recorded.

Original languageEnglish
Pages (from-to)254-266
Number of pages13
JournalInternational Journal of Business Intelligence and Data Mining
Volume14
Issue number1/2
DOIs
StatePublished - 2019

    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

  • Management Information Systems
  • Statistics, Probability and Uncertainty
  • Information Systems and Management

ID: 37246919