NotFYCEX: A Simulation Based Price Prediction and Notification System Using Continuous Machine Learning Method

E. N. Osegi, V.ı. Ani̇reh, J.ı. Mgbeafuli̇ke
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Abstract

This research study presents NotFyCEX - a price notification systems model based on Internet of Things (IoT) and Blockchain technology for reporting important trends in a Cryptocurrency Exchange (CRYPTEX) market. The system is simulated in near real time using a co-simulator approach including web-based PHP server-side application for emulating price fluctuations, a dynamic neural network model application integrated within the MATLAB/SIMULINK software environment and ArduinoUNO hardware for continual physical signalling/alerting. Dynamic simulation results showed exact matches between synthesized price state representations and the predicted pattern states. Thus, we consider NotFyCEX a novel effort that can effectively serve as a notification and price prediction system to the end-user or cryptocurrency trader in a given CRYPTEX market.
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NotFYCEX:使用连续机器学习方法的基于仿真的价格预测和通知系统
本研究介绍了 NotFyCEX - 一种基于物联网(IoT)和区块链技术的价格通知系统模型,用于报告加密货币交易所(CRYPTEX)市场的重要趋势。该系统采用联合模拟器方法进行了近乎实时的模拟,其中包括用于模拟价格波动的基于网络的 PHP 服务器端应用程序、集成在 MATLAB/SIMULINK 软件环境中的动态神经网络模型应用程序以及用于持续物理信号/警报的 ArduinoUNO 硬件。动态模拟结果显示,合成的价格状态表示与预测的模式状态完全吻合。因此,我们认为 NotFyCEX 是一项新颖的工作,可以有效地为特定 CRYPTEX 市场的最终用户或加密货币交易商提供通知和价格预测系统。
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