Title: Flood areas prediction in Bangladesh using Apriori algorithm

Authors: N. Narayanan Prasanth; Anushree Karajgi; Adiksha Sood; S.P. Raja

Addresses: School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India ' School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India ' School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India ' Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamilnadu, India

Abstract: Floods often turn out to be a major natural disaster in some parts of world due to overflow of water which submerges land that is usually dry. This leads to loss of life and vast damage to economy; therefore, it becomes extremely important to have systematic and dynamic prediction of flood areas so that people are more aware and better prepared for the impending disaster. The aim of the paper is to develop a comprehensive model for the prediction of flood area using Apriori algorithm. Our primary focus is to assess the spatial dataset of Bangladesh which provides hazard data of various risks including the risk of flooding. The various factors resulting in flooding such as water level and flood area have been analysed and the possible relations have been developed using the association rules.

Keywords: Apriori; association rules; Bangladesh; flood; data mining.

DOI: 10.1504/IJHI.2023.129298

International Journal of Hybrid Intelligence, 2023 Vol.2 No.2, pp.119 - 127

Received: 27 Apr 2020
Accepted: 26 Sep 2020
Published online: 06 Mar 2023 *

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