Implementation of Apriori Algorithm for a New Flood Area Prediction System

被引：2

作者：

Harun, Nur Ashikin ^{[1
]}

Makhtar, Mokhairi ^{[1
]}

Abd Aziz, Azwa ^{[1
]}

Mohamad, Mumtazimah ^{[1
]}

Zakaria, Zahrahtul Amani ^{[1
]}

机构：

[1] Univ Sultan Zainal Abidin, Fac Informat & Comp, Tembila Campus, Besut 22200, Terengganu, Malaysia

来源：

ADVANCED SCIENCE LETTERS | 2017年 / 23卷 / 06期

关键词：

Association Rules; Apriori Algorithm; Flood Area Prediction; System Development;

D O I：

10.1166/asl.2017.7390

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Frequent pattern mining, known as Apriori algorithm is a simple yet powerful mining algorithm that can be applied in databases to find the frequent itemsets. This paper implements the Apriori algorithm for predicting flood in the study area in Terengganu which contains 7 districts, each has attributes and instances that need to test. The attributes which are flood area, water level and flood status are supplied by the Malaysian Drainage and Irrigation Department from 2009 until 2014, for the month if November until March. The best rules generated from the datasets using Data Mining tools (WEKA) is then indicated to develop a new flood area prediction system. This research aims to help people especially in risky areas to get early warnings and save life and valuable belongings.

引用

页码：5419 / 5422

页数：4

共 17 条

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