Bitcoin Price Prediction

Abstract

Abstract: In this paper, we have proposed to predict the value of Bitcoin accurately considering the various parameters that affect the value of Bitcoin. Collecting information from various references and using papers in real time, I discovered the advantages and disadvantages of predicting the price of Bitcoin. Each paper has its own set of ways to predict the price of Bitcoin. Many papers have an accurate value but some do not, but time complexity is high in those predictions, so to reduce the complexity of the time here in this paper we use an algorithm linked to artificial intelligence called LASSO (at least one opt-out operator. Some papers have used different algorithms such as SVM (support vector machine), GLM, CNN (Convolutional Neural Networks), and RNN (Recurrent neural networks) which do not have good time management, but LASSO acquisition of results on a larger website is faster and faster so for this purpose, we find comparisons between other algorithms and the LASSO algorithm, this test paper helps future researchers to make an impact on their papers. The process takes place in the first paper moment of research, we aim to understand and discover everyday trends in the Bitcoin market while gaining insight into the relevant features surrounding Bitcoin price. Our data set contains various features related to the value of Bitcoin and the payment network throughout the years, which are recorded daily. We previously processed data, using other data mining techniques to reduce data noise. Then for the second minute of our study, we use available information, and we will predict the daily price change signal with the highest accuracy.