A hybrid modified whale optimization algorithm with simulated annealing for terrorism prediction

被引:1
|
作者
Soliman G.M.A. [1 ]
Abou-El-Enien T.H.M. [1 ]
Emary E. [2 ]
Khorshid M.M.H. [1 ]
机构
[1] Faculty of Computers and Artificial Intelligence, Cairo University, Giza
[2] Faculty of Computer Studies, Arab Open University, Cairo
来源
Ingenierie des Systemes d'Information | 2019年 / 24卷 / 03期
关键词
Feature selection; Hybrid algorithms; Memetic algorithm; Spiral path; Tournament selection; Whale optimization algorithm;
D O I
10.18280/isi.240308
中图分类号
学科分类号
摘要
The main purpose of this research is to propose a novel hybrid memetic searching optimization algorithm, the proposed algorithm integrates the modified whale optimization algorithms with simulated annealing algorithm in a novel approach in order to enhance the searching capabilities of the modified whale optimization algorithm with the help of simulated annealing (SA). The proposed algorithm is used to find the minimum feature subset based on hybrid modified whale optimization algorithms and simulated annealing (WOA2SA, WOA3SA), where SA is embedded into the modified WO algorithms to achieve that good balance between (exploitation) and (exploration) capabilities of the modified algorithms. The resulting memetic algorithm improve the performance of the general classification tasks and hence had been used in the prediction of terrorist group (s) which responsible of the terror attacks on Egypt based on GTD terrorism data. The findings of this research can serve as an alarm tool to minimize the terrorist attacks on a certain region (country). © 2019 International Information and Engineering Technology Association. All rights reserved.
引用
收藏
页码:281 / 287
页数:6
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