A study and analysis on nowcasting: Forms of precipitation using improvised random forest classifier

C. Kishor Kumar Reddy, Pilly Ashritha, Thandiwe Sithole

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Weather forecasting is the utilization of science and technology to foresee the conditions of the atmosphere for a given location and time. Weather forecasting is under high priority since it helps to settle future climate changes and provide information on critical weather conditions. As the weather has a great impact on various aspects of human life, aquatic life, aviation industry, and others, efforts have been made for decades to improve the efficiency of weather forecasting to ensure a better life and to reduce economic loss, but the result is not much precise than expected. The present research focuses on improving the efficiency of weather forecasting, focusing on various forms of precipitation such as rain, snow, hail storms, and snowflakes by making use of historical numerical weather datasets across the globe. The efficiency in terms of performance measures has been compared with existing models.

Original languageEnglish
Title of host publicationCognitive Machine Intelligence
Subtitle of host publicationApplications, Challenges, and Related Technologies
PublisherCRC Press
Pages290-308
Number of pages19
ISBN (Electronic)9781040097083
ISBN (Print)9781032647432
DOIs
Publication statusPublished - 28 Aug 2024

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering
  • General Energy
  • General Environmental Science

Fingerprint

Dive into the research topics of 'A study and analysis on nowcasting: Forms of precipitation using improvised random forest classifier'. Together they form a unique fingerprint.

Cite this