Semi convergent matrix-based neural predictive classifier for big data analytics and prediction in cloud services
by R. Rajasekar; K. Srinivasan
International Journal of Cloud Computing (IJCC), Vol. 11, No. 5/6, 2022

Abstract: Big data analytics is a technique concerning gathering, organising and analysing huge units of records to find out patterns or useful information. Recently, many research works has been designed for large records analytics of climate data. In system in accordance with overcome certain challenge, semi convergent matrix-based neural predictive classifier (SCM-NPC) procedure is recommended that gives productive big data calculation and data partaking in cloud services. Initially, the SCM-NPC technique constructs semi convergent matrix on distributed big data for improving the search accuracy of user requested information, next, the SCM-NPC technique is used neural predictive classifier for improving the prediction rate of climate data on cloud big data. Finally, the SCM-NPC technique applies MapReduce function on neural class that provides efficient predictive analytics about climate data conditions on cloud big data. The proposed SCM-NPC system conducts test takes a shot at parameter, for example, forecast rate, computation time and classification accuracy by using Amazon EC2 cloud big datasets. The results show that SCM-NPC technique is to build the expectation level of atmosphere realities conditions on big data and furthermore decreases the calculation time when contrasted with best in class works.

Online publication date: Thu, 02-Feb-2023

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