A Cryptocurrency Price Prediction Study Using Deep Learning and Machine Learning

Title

A Cryptocurrency Price Prediction Study Using Deep Learning and Machine Learning

Creator

Siddharth D.; Kaushik J.

Description

A cryptocurrency is a network-based computerized exchange that makes imitation and double-spending pretty much impossible. Many cryptocurrencies are built on distributed networks based on blockchain technology, which is a distributed ledger enforced by a network of computers. Thanks to blockchain technology, transactions are secure, transparent, traceable, and immutable. As a result of these traits, cryptocurrency has increased in popularity, especially in the financial industry. This research looks at a few of the most popular and successful deep learning algorithms for predicting bitcoin prices. LSTM and Random Forest outperform our generalized regression neural architecture benchmarking system in terms of prediction. Bitcoin and Ethereum are the only cryptocurrencies supported. The approach can be used to calculate the value of a number of different cryptocurrencies. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Cognitive Science and Technology, pp. 669-677.

Date

2023-01-01

Publisher

Springer

Subject

Bitcoin; Cryptocurrency; Ethereum; Long short-term memory; Price prediction; Random forest; Time series

Coverage

Siddharth D., Department of Data Science, CHRIST (Deemed to be University), Bengaluru, India; Kaushik J., Department of Data Science, CHRIST (Deemed to be University), Bengaluru, India, MIT-ADT University, Maharashtra, Pune, India

Rights

Restricted Access

Relation

ISSN: 21953988

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1007/978-981-19-8086-2_64

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149993794&doi=10.1007%2f978-981-19-8086-2_64&partnerID=40&md5=7ce9a8a08383177eaf78446e83edd875