Bitcoin cryptocurrency price prediction using artificial neural network optimized by meta-heuristic optimization algorithms
aidin aboutalebi
1
(
Science and Research Branch, Tehran, Iran
)
kambiz peykarjoo
2
(
Science and Research Branch, Tehran, Iran
)
ebrahim Rezaei
3
(
Science and Research Branch, Tehran, Iran
)
رحیم خانیزاد
4
(
Iran University of Science and Technology, Tehran, Iran
)
Keywords: Cryptocurrency price prediction, Artificial neural network, Bitcoin, Meta-heuristic optimization algorithms,
Abstract :
Cryptocurrencies are digital currencies that use cryptographic technology to secure and control the creation of new units. These currencies operate independently of banks and governments and are usually based on blockchain technology. Blockchain is a distributed ledger that records and verifies all transactions. Some of the most well-known cryptocurrencies include Bitcoin, Ethereum, and Litecoin. Cryptocurrencies are used as a means of exchanging value, investing and even conducting online transactions. Cryptocurrency price forecasting refers to the process of analyzing and evaluating historical data and factors affecting the market with the aim of estimating the future price of these assets. This forecast can help investors and traders make better buying and selling decisions. Participation in financial markets requires having sufficient expertise and knowledge; For this reason, investors have long been looking for solutions that can more accurately predict the price of cryptocurrencies, especially Bitcoin. Due to the increasing progress of computers and the increase in their processing power, the use of artificial intelligence methods, especially artificial neural networks, has become a tool for predicting the price of cryptocurrencies. In this research, Bitcoin price prediction in short-term (10-day) and long-term (30-day) intervals is conducted using an artificial neural network optimized by six metaheuristic optimization algorithms: (PO), (HBO), (SPO), (GPC), (FHO) and (FOX). The results of these six cases were compared with each other.
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