[HTML][HTML] A comprehensive review on multiple hybrid deep learning approaches for stock prediction
Numerous recent studies have attempted to create efficient mechanical trading systems
through the use of machine learning approaches for stock price estimation and portfolio …
through the use of machine learning approaches for stock price estimation and portfolio …
Stock price prediction using deep learning and frequency decomposition
H Rezaei, H Faaljou, G Mansourfar - Expert Systems with Applications, 2021 - Elsevier
Nonlinearity and high volatility of financial time series have made it difficult to predict stock
price. However, thanks to recent developments in deep learning and methods such as long …
price. However, thanks to recent developments in deep learning and methods such as long …
[HTML][HTML] Fine-grained, aspect-based sentiment analysis on economic and financial lexicon
Extracting sentiment from news text, social media and blogs has recently gained increasing
interest in economics and finance. Despite many successful applications of sentiment …
interest in economics and finance. Despite many successful applications of sentiment …
[HTML][HTML] Enhancing multilayer perceptron neural network using archive-based harris hawks optimizer to predict gold prices
The success of the Multi-Layer Perceptron Neural Network (MLP) relies on carefully
configuring its weights and biases to promising values. The gradient descent technique is …
configuring its weights and biases to promising values. The gradient descent technique is …
A cloud 15kV-HDPE insulator leakage current classification based improved particle swarm optimization and LSTM-CNN deep learning approach
TN Da, PN Thanh, MY Cho - Swarm and Evolutionary Computation, 2024 - Elsevier
Real-time insulator leakage current classification is crucial in preventing the pollution
flashover phenomenon and providing appropriate maintenance schedules in high-voltage …
flashover phenomenon and providing appropriate maintenance schedules in high-voltage …
[HTML][HTML] Adversarial attacks and defenses on ML-and hardware-based IoT device fingerprinting and identification
In the last years, the number of IoT devices deployed has suffered an undoubted explosion,
reaching the scale of billions. However, some new cybersecurity issues have appeared …
reaching the scale of billions. However, some new cybersecurity issues have appeared …
Deep learning systems for forecasting the prices of crude oil and precious metals
P Foroutan, S Lahmiri - Financial Innovation, 2024 - Springer
Commodity markets, such as crude oil and precious metals, play a strategic role in the
economic development of nations, with crude oil prices influencing geopolitical relations and …
economic development of nations, with crude oil prices influencing geopolitical relations and …
Commodity Price Prediction for making informed Decisions while trading using Long Short-Term Memory (LSTM) Algorithm
Commodity markets are physical or virtual marketplaces where market players meet to buy
or sell positions in commodities such as crude oil, gold, copper, silver, cotton, and wheat …
or sell positions in commodities such as crude oil, gold, copper, silver, cotton, and wheat …
The random neural network in price predictions
W Serrano - Neural computing and applications, 2022 - Springer
Everybody likes to make a good prediction, in particular, when some sort of personal
investment is involved in terms of finance, energy or time. The difficulty is to make a …
investment is involved in terms of finance, energy or time. The difficulty is to make a …
Hybrid gated recurrent unit bidirectional-long short-term memory model to improve cryptocurrency prediction accuracy
Cryptocurrency is a virtual or digital currency used in financial systems that utilizes
blockchain technology and cryptographic functions to gain transparency, decentralization …
blockchain technology and cryptographic functions to gain transparency, decentralization …