软计算在大数据问题中的分析方法

T. Anand, Rekha Pal, S. Dubey
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引用次数: 1

摘要

随着大数据计算的兴起,大数据的处理日益成为一个问题。分析、可视化和管理这些大量的数据会导致传统技术无法解决的问题和挑战。因此,需要创新的技术或方法来解决问题和挑战。本文的主要目的是探讨大数据与软计算相结合的有效性,以便在更短的时间内更有效地克服问题和挑战。这里重点介绍了三种主要的软计算技术,即神经网络、模糊逻辑和遗传算法,用于最小化大数据相关问题。本文在2004-2015年期间也为此形成了研究问题,作为初步研究,有助于研究者今后的相关研究。
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Analytical approach of soft computing in big data issues
As big data computing is in emergence, therefore handling of large amount of data becoming a problematic day by day. Analyzing, visualizing, and managing this massive amount of data causing remarkable issues and challenges which are not even resolve through traditional technologies. Therefore it requires innovative technologies or methods to resolve issues and challenges. The main aim of this paper is to explore the effectiveness of combination of big data with soft computing to overcome the issues and challenges more efficiently and in less time. Here emphasis is given on three main soft computing techniques namely neural network, fuzzy logic and genetic for minimizing big data related problems. Research questions are also formed for this purpose in the present paper from 2004-2015 as primary study that will help the researchers in future in their related study.
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