Multistep ahead multiphase production prediction of fractured wells using bidirectional gated recurrent unit and multitask learning

X Li, X Ma, F ** ability, machine learning is found to be efficient and
accurate for production prediction of fractured wells compared with conventional analytical …

Deep transformer-based asset price and direction prediction

AHB Gezici, E Sefer - IEEE Access, 2024 - ieeexplore.ieee.org
The field of algorithmic trading, driven by deep learning methodologies, has garnered
substantial attention in recent times. Within this domain, transformers, convolutional neural …

A novel trading system for the stock market using Deep Q-Network action and instance selection

M Park, J Kim, D Enke - Expert Systems with Applications, 2024 - Elsevier
Stock trading is a complex decision-making process that involves predicting market price
movements. Many investors attempt to buy at low prices and sell at high prices, which can …

BRN: A belief rule network model for the health evaluation of complex systems

C Zhang, Z Zhou, Y Cao, S Tang, P Ning… - Expert Systems with …, 2023 - Elsevier
A belief rule base (BRB) expert system provides a generic inference framework for
approximating the complicated nonlinear relationships between inputs and outputs. Such …

Stock price prediction through GRA-WD-BiLSTM model with air quality and weather factors

B Liu, J Pei, Z Yu - International Journal of Machine Learning and …, 2024 - Springer
Accurately predicting stock prices is crucial for reducing investment-related risks in decision-
making. Contemporary challenges to financial behavior, posed by environmental issues …

An interpretable model for stock price movement prediction based on the hierarchical belief rule base

X Yin, X Zhang, H Li, Y Chen, W He - Heliyon, 2023 - cell.com
Stock price movement prediction is the basis for decision-making to maintain the stability
and security of stock markets. It is important to generate predictions in an interpretable …

Forecasting stock indices: Stochastic and artificial neural network models

NK Pande, A Kumar, AK Gupta - Computational Economics, 2024 - Springer
In recent years, there has been a bloom in the stock investors due to availability of various
platforms that have provided an opportunity even for small scale investors to earn profits …

From interpretation to explanation: An analytical examination of deep neural network with linguistic rule-based model

A Toofani, L Singh, S Paul - Computers and Electrical Engineering, 2024 - Elsevier
Abstract The Deep Learning (DL) models stand out as one of the most popular and widely
adopted machine learning techniques across various applications, owing to their capability …

An Algorithmic Trading Approach Merging Machine Learning With Multi-Indicator Strategies for Optimal Performance

N Sukma, CS Namahoot - IEEE Access, 2024 - ieeexplore.ieee.org
This study investigates the integration of machine learning techniques with multi-indicator
strategies in algorithmic trading to overcome the limitations of traditional trading methods. As …

A multi-model approach to the development of algorithmic trading systems for the Forex market

P Sevastjanov, K Kaczmarek, L Rutkowski - Expert Systems with …, 2024 - Elsevier
In the decade passed, considerable affords were made to develop effective trading systems
based on different assumptions concerned with the market nature, methods for data …