[HTML][HTML] Machine learning techniques and data for stock market forecasting: A literature review
In this literature review, we investigate machine learning techniques that are applied for
stock market prediction. A focus area in this literature review is the stock markets …
stock market prediction. A focus area in this literature review is the stock markets …
Comprehensive review on twin support vector machines
Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly
emerging efficient machine learning techniques which offer promising solutions for …
emerging efficient machine learning techniques which offer promising solutions for …
Financial time series forecasting model based on CEEMDAN and LSTM
J Cao, Z Li, J Li - Physica A: Statistical mechanics and its applications, 2019 - Elsevier
In order to improve the accuracy of the stock market prices forecasting, two hybrid
forecasting models are proposed in this paper which combine the two kinds of empirical …
forecasting models are proposed in this paper which combine the two kinds of empirical …
Bayesian optimization based dynamic ensemble for time series forecasting
Among various time series (TS) forecasting methods, ensemble forecast is extensively
acknowledged as a promising ensemble approach achieving great success in research and …
acknowledged as a promising ensemble approach achieving great success in research and …
Literature review: Machine learning techniques applied to financial market prediction
BM Henrique, VA Sobreiro, H Kimura - Expert Systems with Applications, 2019 - Elsevier
The search for models to predict the prices of financial markets is still a highly researched
topic, despite major related challenges. The prices of financial assets are non-linear …
topic, despite major related challenges. The prices of financial assets are non-linear …
Forecasting stock prices with long-short term memory neural network based on attention mechanism
The stock market is known for its extreme complexity and volatility, and people are always
looking for an accurate and effective way to guide stock trading. Long short-term memory …
looking for an accurate and effective way to guide stock trading. Long short-term memory …
Forecasting and trading cryptocurrencies with machine learning under changing market conditions
H Sebastião, P Godinho - Financial Innovation, 2021 - Springer
This study examines the predictability of three major cryptocurrencies—bitcoin, ethereum,
and litecoin—and the profitability of trading strategies devised upon machine learning …
and litecoin—and the profitability of trading strategies devised upon machine learning …
Deep learning in medical imaging: general overview
The artificial neural network (ANN)–a machine learning technique inspired by the human
neuronal synapse system–was introduced in the 1950s. However, the ANN was previously …
neuronal synapse system–was introduced in the 1950s. However, the ANN was previously …
Applications of machine learning methods in port operations–A systematic literature review
Ports are pivotal nodes in supply chain and transportation networks, in which most of the
existing data remain underutilized. Machine learning methods are versatile tools to utilize …
existing data remain underutilized. Machine learning methods are versatile tools to utilize …
Stock price prediction using DEEP learning algorithm and its comparison with machine learning algorithms
M Nikou, G Mansourfar… - Intelligent Systems in …, 2019 - Wiley Online Library
Security indices are the main tools for evaluation of the status of financial markets. Moreover,
a main part of the economy of any country is constituted of investment in stock markets …
a main part of the economy of any country is constituted of investment in stock markets …