Журнал основ возобновляемой энергии и приложений
Открытый доступ

Абстрактный

Soft-Computing: A Fundamental Approach in Analyzing Big Data

Christopher Ejiofor and Mgbeafuluike IJ

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.