Predictive Analytics for Disaster Management

  • Anuja Patil
  • Kaustubh Magdum
  • et al.
N/ACitations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

Predictive analytics helps analyze past events to identify and extract patterns and populations vulnerable to natural calamities. Large number of supervised and unsupervised approaches can be used to identify at risk areas and improve predictions of future events. In addition, predictive analytics techniques can also provide insight for understanding the economic and human impact of natural calamities. Heavy rainfall prediction is a major problem for meteorological department and it is closely associated with the economy and human life. Here the natural disasters we will be focusing on are floods and droughts which are encountered by people across the globe every year. One of the leading causes for this is rainfall. Thus, our main focus will be on rainfall prediction with the help of different parameters and how this prediction can further help us .

Cite

CITATION STYLE

APA

Anuja Patil, Kaustubh Magdum, & Atharva Phadke. (2020). Predictive Analytics for Disaster Management. International Journal of Engineering Research And, V9(02). https://doi.org/10.17577/ijertv9is020415

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free