Overview

Original Research

NORMALIZING THE SCALING OF BITCOIN USING THE Q-LEARNING MODEL FOR BUSINESS MANAGEMENT

HARI KRISHNAN ANDI 1, MEHTAB ALAM 2, JENIZA JAMALUDIN 3, LOVINA YOGARAJAN 4, NORMY RAFIDA ABDUL RAHMAN 5, and KOMATHI MUNIYANDI 6.

Vol 18, No 03 ( 2023 )   |  DOI: 10.17605/OSF.IO/FX4C9   |   Author Affiliation: Associate Professor, Centre for Postgraduate Studies 1; PhD student, University of Cyberjaya, Selangor Malyasia 2; Senior Lecturer, Centre for Postgraduate Studies Asia Metropolitan University 3,4,5,6.   |   Licensing: CC 4.0   |   Pg no: 1279-1290   |   Published on: 29-03-2023

Abstract

The normalization of scaling for Bitcoin is the decentralized cryptocurrency that drew much attention for using the solution through the Q learning model. It has been widely deployed for the application and usage of Bitcoin for encountering performance problems of the high and low latency of the transaction. The proof of the work is the experiment and data used for Bitcoin Trading, where results unfolded that the scalability of Bitcoin is effectively managed for the Q learning model in business management and technology research. The comparison between different methods is the potential direction for the scalability normalization of Bitcoin. The training and testing with 87.7% accuracy of the Q-learning model are helpful for the time, scaling, regulating the transactions and transfer of the price, and the desired amount of the data. The prediction of Bitcoin price is based on Q learning with valuable attributes of accuracy and the future price of Bitcoin with verified data attributes. The reinforcement learning algorithms have the advantage of expressing improved performance prediction in similar formats of Cryptocurrencies as Bitcoin. The data extraction is suitable for the performance of the resource efficiency and Bitcoin use in other research of normalizing and scaling solutions.

Keywords

Bitcoin, Scaling, Q-learning, Business Technology