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

Ibrahim Nasir Mahmood, Hussein Ali Aliedane, Mustafa Ali Abuzaraida


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.


Data Mining, Association Rules, Fire Accidents Analysis, Data Analysis, Data Cleaning

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International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923
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