Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping

Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Podrobná bibliografie
Hlavní autoři:	Zaman, Md. Sayeed Ibne, Kamal, Mir Ishraq, Ishan, Samiu Mostafa, Khan, Shafayat Zamil, Hossain, Samiha
Další autoři:	Esfar-E-Alam
Médium:	Diplomová práce
Jazyk:	English
Vydáno:	Brac University 2022
Témata:	Cryptocurrency LSTM Bitcoin Litecoin Ethereum Cryptocurrency price prediction Forecasting Long short-term memory SimpleRNN Random forest Machine learning Digital currency
On-line přístup:	http://hdl.handle.net/10361/17208

Podobné jednotky

Blockchain based e-voting system with homomorphic encryption and threshold signature
Autor: Probor, Mushfique Nasir, a další
Vydáno: (2023)

A sustainable Bitcoin architecture
Autor: Monem, Maruf
Vydáno: (2022)

Physical currency or crypto currency, which one will be better for our economy?
Autor: Rohan, Raian Kibria, a další
Vydáno: (2024)

Efficient blockchain system based on proof of segmented work
Autor: Ahmed, Rashad, a další
Vydáno: (2020)

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations
Autor: Rabbi, Md. Nafis
Vydáno: (2024)

Time-Series Forecasting of Ethereum Price using Long Short-Term Memory (LSTM) Networks
Autor: Al-Wasee, Mohammad Samin, a další
Vydáno: (2022)

ROBB: recurrent proximal policy optimization reinforcement learning for optimal block formation in bitcoin blockchain network
Autor: Dutta, Amit
Vydáno: (2024)

coinBD: an enhanced version of proof of work with less computational power
Autor: Hossain, Mohammad Badrul, a další
Vydáno: (2019)

Conversion of Bengali speech to text using long short-term memory(LSTM)
Autor: Chowdhury, Mohammad Fahim, a další
Vydáno: (2021)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
Autor: Maliha, Miftahul Zannat, a další
Vydáno: (2023)

Deep learning based predictive analytics for decentralized content caching in hierarchical edge networks
Autor: Chakraborty, Dhruba, a další
Vydáno: (2022)

Forecasting bitcoin price considering macro economic factors and media influence using bidirectional LSTM and random forest regressor as ensemble model
Autor: Ghose, Swattic, a další
Vydáno: (2023)

Advanced health insurance system using smart contract of ethereum blockchain
Autor: Tushar, Mehedi Hasan, a další
Vydáno: (2023)

Blockchain-based micropayment system for secured cashless small payments
Autor: Siam, Morshed, a další
Vydáno: (2022)

Share market forecasting with LSTM neural network and sentimental trend prediction
Autor: Rony, Ismail Hossain, a další
Vydáno: (2020)

Human sentiment analysis using natural language processing
Autor: Shamya, Md. Shamiul Haque Khan, a další
Vydáno: (2024)

Towards devising a fund management system using blockchain
Autor: Bente Rashid, Nibula, a další
Vydáno: (2022)

Accelerating ggplot2 based projection on r-map using NVIDIA GPU
Autor: Islam, Md. Zahidul, a další
Vydáno: (2016)

Bangla hate speech detection on social media using attention-based recurrent neural network
Autor: Das, Amit Kumar, a další
Vydáno: (2022)

Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning
Autor: Arafat, Sheikh Mohammad, a další
Vydáno: (2021)

Bitcoin price forecasting based on historical data
Autor: Roy, Shaily, a další
Vydáno: (2018)

Modelling and forecasting energy demand of Bangladesh using AI based algorithms
Autor: Mahmud, Booshra Nazifa, a další
Vydáno: (2019)

Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security
Autor: Fiha, Yeamin Jahan, a další
Vydáno: (2022)

The influence of neuromarketing: machine learning based empirical analysis
Autor: Muktadir, MD. Abdullah Al, a další
Vydáno: (2024)

Analyzing area-wise air pollution level using machine learning for a better future
Autor: Sihan, Sk. Atik Tajwar, a další
Vydáno: (2021)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
Autor: Hossain, Shoumik, a další
Vydáno: (2022)

The Use of Encompassing Tests for Forecast Combinations /
Autor: Kisinbay, Turgut
Vydáno: (2007)

Demand forecasting on supply chain using ML and NN
Autor: Hridi, Naoshin Anzum, a další
Vydáno: (2023)

Revolutionizing microfinance: a blockchain-driven decentralized finance (DeFi) model for collateral-free loans
Autor: Tasin, Md. Ishmam, a další
Vydáno: (2023)

Analysis of financial data on the time series using data from the stock market
Autor: Shachcha, Ifad Bhuiyan, a další
Vydáno: (2022)

Cryptocurrency price prediction using Social Media Data Mining and Epidemic Modeling
Autor: Safa, Bushra, a další
Vydáno: (2023)

Bangla speech recognition using 1D CNN and LSTM with different dimension reduction techniques
Autor: Nirjhor, S M Mahsanul Islam, a další
Vydáno: (2019)

Short term load forecasting based on Internet of Things (IoT)
Autor: Uz Zaman, Mahdi, a další
Vydáno: (2018)

RED-LSTM: Real time emotion detection using LSTM
Autor: Labiba, Mansura Rahman, a další
Vydáno: (2023)

Stock Market Price movement prediction using RNN and Point-weight Sentiment
Autor: Uddin, S. M. Rageeb Noor, a další
Vydáno: (2022)

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
Autor: Morshed, Atique, a další
Vydáno: (2021)

Ensure security in supply chain with blockchain technology
Autor: Tarannum, Fairuz, a další
Vydáno: (2023)

Leveraging sequential deep learning models for detecting multitude of human action categories
Autor: Pranta, Kazi Al Refat, a další
Vydáno: (2024)

Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA
Autor: Chakraborty, Pranjal
Vydáno: (2019)

The unloved dollar standard
Autor: McKinnon, Ronald I.