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.

Opis bibliograficzny
Główni autorzy:	Zaman, Md. Sayeed Ibne, Kamal, Mir Ishraq, Ishan, Samiu Mostafa, Khan, Shafayat Zamil, Hossain, Samiha
Kolejni autorzy:	Esfar-E-Alam
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2022
Hasła przedmiotowe:	Cryptocurrency LSTM Bitcoin Litecoin Ethereum Cryptocurrency price prediction Forecasting Long short-term memory SimpleRNN Random forest Machine learning Digital currency
Dostęp online:	http://hdl.handle.net/10361/17208

Podobne zapisy

Blockchain based e-voting system with homomorphic encryption and threshold signature
od: Probor, Mushfique Nasir, i wsp.
Wydane: (2023)

A sustainable Bitcoin architecture
od: Monem, Maruf
Wydane: (2022)

Physical currency or crypto currency, which one will be better for our economy?
od: Rohan, Raian Kibria, i wsp.
Wydane: (2024)

Efficient blockchain system based on proof of segmented work
od: Ahmed, Rashad, i wsp.
Wydane: (2020)

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

Time-Series Forecasting of Ethereum Price using Long Short-Term Memory (LSTM) Networks
od: Al-Wasee, Mohammad Samin, i wsp.
Wydane: (2022)

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

coinBD: an enhanced version of proof of work with less computational power
od: Hossain, Mohammad Badrul, i wsp.
Wydane: (2019)

Conversion of Bengali speech to text using long short-term memory(LSTM)
od: Chowdhury, Mohammad Fahim, i wsp.
Wydane: (2021)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
od: Maliha, Miftahul Zannat, i wsp.
Wydane: (2023)

Deep learning based predictive analytics for decentralized content caching in hierarchical edge networks
od: Chakraborty, Dhruba, i wsp.
Wydane: (2022)

Forecasting bitcoin price considering macro economic factors and media influence using bidirectional LSTM and random forest regressor as ensemble model
od: Ghose, Swattic, i wsp.
Wydane: (2023)

Advanced health insurance system using smart contract of ethereum blockchain
od: Tushar, Mehedi Hasan, i wsp.
Wydane: (2023)

Blockchain-based micropayment system for secured cashless small payments
od: Siam, Morshed, i wsp.
Wydane: (2022)

Share market forecasting with LSTM neural network and sentimental trend prediction
od: Rony, Ismail Hossain, i wsp.
Wydane: (2020)

Human sentiment analysis using natural language processing
od: Shamya, Md. Shamiul Haque Khan, i wsp.
Wydane: (2024)

Towards devising a fund management system using blockchain
od: Bente Rashid, Nibula, i wsp.
Wydane: (2022)

Accelerating ggplot2 based projection on r-map using NVIDIA GPU
od: Islam, Md. Zahidul, i wsp.
Wydane: (2016)

Bangla hate speech detection on social media using attention-based recurrent neural network
od: Das, Amit Kumar, i wsp.
Wydane: (2022)

Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning
od: Arafat, Sheikh Mohammad, i wsp.
Wydane: (2021)

Bitcoin price forecasting based on historical data
od: Roy, Shaily, i wsp.
Wydane: (2018)

Modelling and forecasting energy demand of Bangladesh using AI based algorithms
od: Mahmud, Booshra Nazifa, i wsp.
Wydane: (2019)

Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security
od: Fiha, Yeamin Jahan, i wsp.
Wydane: (2022)

The influence of neuromarketing: machine learning based empirical analysis
od: Muktadir, MD. Abdullah Al, i wsp.
Wydane: (2024)

Analyzing area-wise air pollution level using machine learning for a better future
od: Sihan, Sk. Atik Tajwar, i wsp.
Wydane: (2021)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
od: Hossain, Shoumik, i wsp.
Wydane: (2022)

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

Demand forecasting on supply chain using ML and NN
od: Hridi, Naoshin Anzum, i wsp.
Wydane: (2023)

Revolutionizing microfinance: a blockchain-driven decentralized finance (DeFi) model for collateral-free loans
od: Tasin, Md. Ishmam, i wsp.
Wydane: (2023)

Analysis of financial data on the time series using data from the stock market
od: Shachcha, Ifad Bhuiyan, i wsp.
Wydane: (2022)

Cryptocurrency price prediction using Social Media Data Mining and Epidemic Modeling
od: Safa, Bushra, i wsp.
Wydane: (2023)

Bangla speech recognition using 1D CNN and LSTM with different dimension reduction techniques
od: Nirjhor, S M Mahsanul Islam, i wsp.
Wydane: (2019)

Short term load forecasting based on Internet of Things (IoT)
od: Uz Zaman, Mahdi, i wsp.
Wydane: (2018)

RED-LSTM: Real time emotion detection using LSTM
od: Labiba, Mansura Rahman, i wsp.
Wydane: (2023)

Stock Market Price movement prediction using RNN and Point-weight Sentiment
od: Uddin, S. M. Rageeb Noor, i wsp.
Wydane: (2022)

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
od: Morshed, Atique, i wsp.
Wydane: (2021)

Ensure security in supply chain with blockchain technology
od: Tarannum, Fairuz, i wsp.
Wydane: (2023)

Leveraging sequential deep learning models for detecting multitude of human action categories
od: Pranta, Kazi Al Refat, i wsp.
Wydane: (2024)

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

The unloved dollar standard
od: McKinnon, Ronald I.