Financial time series forecasting with deep learning: A systematic literature review: 2005–2019
Financial time series forecasting is undoubtedly the top choice of computational intelligence
for finance researchers in both academia and the finance industry due to its broad …
for finance researchers in both academia and the finance industry due to its broad …
A survey of forex and stock price prediction using deep learning
Predictions of stock and foreign exchange (Forex) have always been a hot and profitable
area of study. Deep learning applications have been proven to yield better accuracy and …
area of study. Deep learning applications have been proven to yield better accuracy and …
Deep learning for financial applications: A survey
Computational intelligence in finance has been a very popular topic for both academia and
financial industry in the last few decades. Numerous studies have been published resulting …
financial industry in the last few decades. Numerous studies have been published resulting …
A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions
A Thakkar, K Chaudhari - Expert Systems with Applications, 2021 - Elsevier
The stock market has been an attractive field for a large number of organizers and investors
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
[HTML][HTML] Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges
The current expansion of theory and research on artificial intelligence in management and
organization studies has revitalized the theory and research on decision-making in …
organization studies has revitalized the theory and research on decision-making in …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Multi-DQN: An ensemble of Deep Q-learning agents for stock market forecasting
The stock market forecasting is one of the most challenging application of machine learning,
as its historical data are naturally noisy and unstable. Most of the successful approaches act …
as its historical data are naturally noisy and unstable. Most of the successful approaches act …
Study on the prediction of stock price based on the associated network model of LSTM
G Ding, L Qin - International Journal of Machine Learning and …, 2020 - Springer
Stock market has received widespread attention from investors. It has always been a hot
spot for investors and investment companies to grasp the change regularity of the stock …
spot for investors and investment companies to grasp the change regularity of the stock …
Fibre-optic sensor and deep learning-based structural health monitoring systems for civil structures: A review
UMN Jayawickrema, H Herath, NK Hettiarachchi… - Measurement, 2022 - Elsevier
Structural health monitoring (SHM) systems in civil engineering structures have been a
growing focus of research and practice. Over the last few decades, optical fibre sensor (OFS) …
growing focus of research and practice. Over the last few decades, optical fibre sensor (OFS) …
MLP-based Learnable Window Size for Bitcoin price prediction
Over the past few years, Bitcoin price prediction has been changed to a big challenge for
investors on cryptocurrencies. In this regard, Neural Networks as a strong structure for …
investors on cryptocurrencies. In this regard, Neural Networks as a strong structure for …