A hybrid machine learning framework by incorporating categorical boosting and manifold learning for financial analysis DOI Creative Commons

Yuyang Zhao,

Zhao Hong

Intelligent Systems with Applications, Journal Year: 2024, Volume and Issue: unknown, P. 200473 - 200473

Published: Dec. 1, 2024

Language: Английский

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm DOI Creative Commons

Khalil A. Alruwaitee

Journal of Radiation Research and Applied Sciences, Journal Year: 2024, Volume and Issue: 17(4), P. 101172 - 101172

Published: Nov. 12, 2024

Language: Английский

Citations

1
Residual temporal convolution network with novel activation function for financial prediction with feature selection procedures DOI

Ahmad YA Bani Ahmad

E-Learning and Digital Media, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 21, 2024

Finance provides a major contribution to countries economic growth. A deep understanding of the financial market helps offer better returns in future. The generates more complications for predicting complicated system dynamics. Different machine learning techniques are implemented execute prediction and they didn’t provide outcomes returns. Predicting stocks yearly phases brings huge profits stock traders make decisions. help predict accuracy market. effectively handled enormous unsupervised unstructured data. In order achieve results, intelligent model is proposed forecasting crisis. Initially, raw data fetched from benchmark datasets. Subsequently, multi-objective-based feature selection process takes place, where features optimally selected by using Updated Random Variable-based Coati Optimization Algorithm (URV-COA). Due this selection, various constraints like correlation, relief score, variance considered formulation. Finally, resultant subjected Residual Temporal Convolutional Network with Novel Activation function (RTCN-NAF) cost. Therefore, experimentation assessed divergent metrics compared other traditional methodologies. On contrary, suggested work achieves results that can prove effectiveness system.

Language: Английский

Citations

0
A hybrid machine learning framework by incorporating categorical boosting and manifold learning for financial analysis DOI Creative Commons

Yuyang Zhao,

Zhao Hong

Intelligent Systems with Applications, Journal Year: 2024, Volume and Issue: unknown, P. 200473 - 200473

Published: Dec. 1, 2024

Language: Английский

Citations

0