https://journal.50sea.com/index.php/IJIST/article/view/1078/1629
Journal Title: International Journal of Innovations in Science and Technology - Year 2024, Vol 6, Issue 7
Abstract
The cryptocurrency market has evolved in unprecedented ways over the past decade. However, due to the high price volatility associated with cryptocurrencies, predicting their prices remains an attractive research topic. While many researchers have focused on predicting cryptocurrency prices, there has been relatively little attention given to the latest trend in blockchain applications, specifically non-fungible tokens (NFTs). In this study, we have prepared a dataset comprising NFT sales and transaction data, along with information from other cryptocurrencies. This dataset is utilized to forecast the future price of Bitcoin using several machines learning models, including Linear Regression, Random Forest, and XG Boost. The results highlight the prediction accuracy of these models. Among the three, the Random Forest regressor demonstrates the highest accuracy, followed closely by the XG Boost regressor and Linear Regression. These findings may assist investors in making informed decisions when investing in cryptocurrencies.
Authors and Affiliations
Saeed Arshad, Zeeshan Ali Khan, Ubaid Abbasi
Keywords
Related Articles
- EP ID EP760720
- DOI -
- Views 13
- Downloads 0
Predictive Maintenance in Industrial Internet of Things: Current Status
Introduction/Importance of Study: Predictive Maintenance (PdM) is a key challenge within the Industrial Internet of Things (IIoT). It aims to enhance system operations by minimizing equipment failures, leading to smoot...
Human Factors and Risk Analysis in Conventional System of Marble Mining: Using HFACS Framework and Structural Equation Modeling Technique
ccidents in mines can occur due to sources of hazards that lead to the loss of hundreds of precious lives every year. Among these sources, human error is considered one of the significant sources that contribute to hum...
Image Compression Exploration using Discrete Wavelets Transform Families and Level
This analysis paper is based on Discrete Wavelets Transform (DWT) for image compression using wavelets families and levels. The DW transforms the image or data into frequency components that match its resolution scale...
Deep Learning Based Identification and Categorization of Various Phases of Diabetic Retinopathy
Diabetic Retinopathy is a growing disease that affects the human retina of diabetic patients, leading to loss of vision if left untreated. Early diagnosis and accurate classification of various stages of DR are crucial...
Prediction of Elective Patients and Length of Stay in Hospital
The efficient management of hospital resources and the optimization of patient care are critical tasks in healthcare systems worldwide. One of the key challenges in hospital management is predicting the duration of a p...