软计算:分析大数据的基本方法

Christopher Ejiofor, Mgbeafuluike Ij
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引用次数: 0

摘要

本文设计了一种新的大数据分析模型:软计算模型。它关注海量数据,同时解决数据速度问题。该模型包括中介器、数据过滤器、收集器、预测器和受体,所有模型组件。使用数据滤波器处理数据量的增强,而使用预测器处理数据速度。统一建模语言(UML)描述了模型的行为功能。该模式所带来的好处将在全面实施后进行探索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soft-Computing: A Fundamental Approach in Analyzing Big Data
This paper has designed a novel model: soft-computing model in analyzing big data. It focuses on voluminous data while addressing data velocity. The model comprises of mediator, data filter, collector, predictor and acceptor, all model components. The enhancement of data volume is handled using data filters while data velocity is handled using predictor. Unified Modeling Language (UML) portrays the behavioral functionalities of the model. The proffered benefit of the model will be explored on full implemented.
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