Applications of Data Mining in Mitigating Fire Accidents Based on Association Rules

Dublin Core

Title

Applications of Data Mining in Mitigating Fire Accidents Based on Association Rules

Subject

Data Mining
Association Rules
Fire Accidents Analysis
Data Analysis
Data Cleaning

Description

Due to the increased rate of fire accidents which cause many damages and losses to people souls, material, and property in Basra city. The necessity of analyzing and mining the data of the fire accidents became an urgent need to find a solution. The need increased for a solution that helps to mitigate and reduce the number of accidents. In this paper, data mining techniques and applications including data preprocessing, data cleaning, and data exploration have been applied. Data mining applications is performed to analyze and discover the hidden knowledge in ten years of data (fire accidents happened from 2010 – 2019) which is approximately 20k record of accidents. These data mining techniques along with the association rules algorithm is applied on the dataset. The applied approach and techniques resulted in discovering the patterns and the nature of the fire accidents in Basra city. It also helped to reach to recommendations and resolutions for mitigating the fire accidents and its occurrence rate.

Creator

Mahmood, Ibrahim Nasir
Aliedane, Hussein Ali
Abuzaraida, Mustafa Ali

Source

International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 12 (2021); pp. 158-169
1865-7923

Publisher

International Association of Online Engineering (IAOE), Vienna, Austria

Date

2021-06-18

Rights

Copyright (c) 2021 Ibrahim Nasir Mahmood, Hussein Ali Aliedane, Mustafa Ali Abuzaraida

Relation

Format

application/pdf

Language

eng

Type

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article

Identifier

Citation

Ibrahim Mahmood Nasir, Hussein Aliedane Ali and Mustafa Abuzaraida Ali, Applications of Data Mining in Mitigating Fire Accidents Based on Association Rules, International Association of Online Engineering (IAOE), Vienna, Austria, 2021, accessed November 23, 2024, https://igi.indrastra.com/items/show/2020

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