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Survey on data science with population-based algorithms

机译:基于人口算法的数据科学调查

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This paper discusses the relationship between data science and population-based algorithms, which include swarm intelligence and evolutionary algorithms. We reviewed two categories of literature, which include population-based algorithms solving data analysis problem and utilizing data analysis methods in population-based algorithms. With the exponential increment of data, the data science, or more specifically, the big data analytics has gained increasing attention among researchers. New and more efficient algorithms should be designed to handle this massive data problem. Based on the combination of population-based 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 population-based algorithms could be analyzed via the data analytics along the optimization process, a crucial entity in population-based algorithms.
机译:本文讨论了数据科学与基于人口的算法之间的关系,其中包括群体智能和进化算法。我们回顾了两类文献,包括解决数据分析问题的基于人群的算法和基于人群的算法中的数据分析方法。随着数据的指数级增长,数据科学,或更具体地说,大数据分析越来越受到研究人员的关注。应该设计出更高效的新算法来处理这种海量数据问题。基于人口算法和数据挖掘技术的结合,我们可以更好地理解数据分析的见解,并设计出更有效的算法来解决现实世界中的大数据分析问题。同样,可以通过沿着优化过程的数据分析来分析基于种群的算法的弱点和优势,优化过程是基于种群的算法中的关键实体。

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