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2016 | OriginalPaper | Buchkapitel

Evolutionary Computation and Big Data: Key Challenges and Future Directions

verfasst von : Shi Cheng, Bin Liu, Yuhui Shi, Yaochu Jin, Bin Li

Erschienen in: Data Mining and Big Data

Verlag: Springer International Publishing

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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.

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Titel: Evolutionary Computation and Big Data: Key Challenges and Future Directions
verfasst von: Shi Cheng
Bin Liu
Yuhui Shi
Yaochu Jin
Bin Li
Verlag: Springer International Publishing
Buch: Data Mining and Big Data
Print ISBN: 978-3-319-40972-6

Electronic ISBN: 978-3-319-40973-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-40973-3_1

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