Metaheuristics in Big Data: An Approach to Railway Engineering

被引：0
作者：
Nunez, Silvia Galvan [1 ]
Attoh-Okine, Nii [1 ]
机构：
[1] Univ Delaware, Dept Civil & Environm Engn, Newark, DE 19716 USA
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2014年
关键词：
Big Data; Metaheuristics; Railway; DATA ANALYTICS; SYSTEM; INTELLIGENCE; ALGORITHM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Big data is becoming increasingly important in various fields; railway engineering is no exception. The use of advanced analysis tools will lead to improved reliability and safety in railway systems. This paper addresses how metaheuristics can be used as an optimization technique to accurately analyze large data in railway engineering. Contributions in both optimization and application in railway engineering are also mentioned. Also, future research towards data analysis in real-life problems is discussed.
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页数：6
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