Performance measurement with high performance computer of HW-GA anomaly detection algorithms for streaming data

Author:

Fondaj Jakup,Hasani ZirijeORCID,Krrabaj Samedin

Abstract

Anomaly detection is very important in every sector as health, education, business, etc. Knowing what is going wrong with data/digital system help peoples from every sector to take decision. Detection anomalies in real time Big Data is nowadays very crucial. Dealing with real time data requires speed, for this reason the aim of this paper is to measure the performance of our previously proposed HW-GA algorithm compared with other anomaly detection algorithms. Many factors will be analyzed which may affect the performance of HW-GA as visualization of result, amount of data and performance of computers. Algorithm execution time and CPU usage are the parameters which will be measured to evaluate the performance of HW-GA algorithm. Also, another aim of this paper is to test the HW-GA algorithm with large amount of data to verify if it will find the possible anomalies and the result to compare with other algorithms. The experiments will be done in R with different datasets as real data Covid-19 and e-dnevnik data and three benchmarks from Numenta datasets. The real data have not known anomalies but in the benchmark data the anomalies are known this is in order to evaluate how the algorithms work in both situations. The novelty of this paper is that the performance will be tested in three different computers which one of them is high performance computer.

Publisher

AGHU University of Science and Technology Press

Subject

Artificial Intelligence,Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Computer Vision and Pattern Recognition,Modeling and Simulation,Computer Science (miscellaneous)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3