[HTML][HTML] Machine learning techniques and data for stock market forecasting: A literature review

MM Kumbure, C Lohrmann, P Luukka… - Expert Systems with …, 2022 - Elsevier
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 …

Mixture of experts: a literature survey

S Masoudnia, R Ebrahimpour - Artificial Intelligence Review, 2014 - Springer
Mixture of experts (ME) is one of the most popular and interesting combining methods, which
has great potential to improve performance in machine learning. ME is established based on …

Activity recognition with android phone using mixture-of-experts co-trained with labeled and unlabeled data

YS Lee, SB Cho - Neurocomputing, 2014 - Elsevier
As the number of smartphone users has grown recently, many context-aware services have
been studied and launched. Activity recognition becomes one of the important issues for …

A deep neural network for operator learning enhanced by attention and gating mechanisms for long-time forecasting of tumor growth

Q Chen, H Li, X Zheng - Engineering with Computers, 2024 - Springer
Forecasting tumor progression and assessing the uncertainty of predictions play a crucial
role in clinical settings, especially for determining disease outlook and making informed …

Object detection using convolutional neural networks and transformer-based models: a review

S Shah, J Tembhurne - Journal of Electrical Systems and Information …, 2023 - Springer
Transformer models are evolving rapidly in standard natural language processing tasks;
however, their application is drastically proliferating in computer vision (CV) as well …

Accelerating chemical kinetics calculations with physics informed neural networks

A Almeldein, N Van Dam - … of Engineering for …, 2023 - asmedigitalcollection.asme.org
Detailed chemical kinetics calculations can be very computationally expensive, and so
various approaches have been used to speed up combustion calculations. Deep neural …

Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange

R Ebrahimpour, H Nikoo, S Masoudnia… - International Journal of …, 2011 - Elsevier
A new method for forecasting the trend of time series, based on mixture of MLP experts, is
presented. In this paper, three neural network combining methods and an Adaptive Network …

Cross-view and multi-view gait recognitions based on view transformation model using multi-layer perceptron

W Kusakunniran, Q Wu, J Zhang, H Li - Pattern Recognition Letters, 2012 - Elsevier
Gait has been shown to be an efficient biometric feature for human identification at a
distance. However, performance of gait recognition can be affected by view variation. This …

Non-linear heterogeneous ensemble model for permeability prediction of oil reservoirs

T Helmy, SM Rahman, MI Hossain… - Arabian Journal for …, 2013 - Springer
The ensemble computational model, which uses machine learning techniques to learn
partial solutions of a given problem and combines the solutions to obtain a complete …

[PDF][PDF] Diversity and regularization in neural network ensembles

H Chen - 2008 - delta.cs.cinvestav.mx
In this thesis, we present our investigation and developments of neural network ensembles,
which have attracted a lot of research interests in machine learning and have many fields of …