Title
Evolutionary Computation And Big Data: Key Challenges And Future Directions
Abstract
Over the past few years, big data analytics has received increasing attention in all most all scientific research fields. This paper discusses the synergies between big data and evolutionary computation (EC) algorithms, including swarm intelligence and evolutionary algorithms. We will discuss the combination of big data analytics and EC algorithms, such as the application of EC algorithms to solving big data analysis problems and the use of data analysis methods for designing new EC algorithms or improving the performance of EC algorithms. Based on the combination of EC algorithms and data mining techniques, we understand better the insights of data analytics, and design more efficient algorithms to solve real-world big data analytics problems. Also, the weakness and strength of EC algorithms could be analyzed via the data analytics along the optimization process, a crucial entity in EC algorithms. Key challenges and future directions in combining big data and EC algorithms are discussed.
Year
DOI
Venue
2016
10.1007/978-3-319-40973-3_1
DATA MINING AND BIG DATA, DMBD 2016
Keywords
Field
DocType
Big data analytics, Data science, Evolutionary algorithms, Evolutionary computation, Swarm intelligence
Evolutionary algorithm,Data analysis,Computer science,Swarm intelligence,Evolutionary computation,Artificial intelligence,Big data,Machine learning,Scientific method
Conference
Volume
ISSN
Citations 
9714
0302-9743
2
PageRank 
References 
Authors
0.36
0
5
Name
Order
Citations
PageRank
Shi Cheng131.11
Bin Liu2429.60
Yuhui Shi34397435.39
Yaochu Jin46457330.45
B. Li582.57