Research Papers
Published research and technical papers on neural networks, AI, and machine learning.
PublishedImpact Factor: 6.1
Vellaichamy U
Bulletin For Technology And History (BTH)
Volume 26, Issue 1, January 2026
ISSN: 0391-6715
DOI Serial Number: 10.37326
Paper ID: BTH/3515
Vels Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai 600 117
Abstract
This paper presents a comprehensive approach to stock price prediction using neural network architectures. The study explores various neural network models including feedforward networks, recurrent neural networks (RNN), and LSTM networks for time-series forecasting of stock market prices. The research demonstrates significant improvements in prediction accuracy compared to traditional statistical methods.
ScopusGoogle ScholarCrossRefUGC Approved
Accepted for Publication
Vellaichamy U
Journal of Harbin Engineering University (JHEU)
Manuscript ID: JHEU-2026-1021
Paper ID: JHEU-2026-1021
Abstract
This paper investigates the application of General Regression Neural Networks (GRNN) for stock market prediction. GRNN offers advantages over traditional backpropagation networks including faster learning, convergence to optimal regression surfaces, and the ability to handle sparse data in multidimensional measurement spaces. The study evaluates GRNN performance against conventional prediction methods.
Published
Vellaichamy U
International Journal of Analytical, Experimental and Modal Analysis (IJAEMA)
Volume XII, Issue IX, September 2020
ISSN: 0886-9367
Paper ID: 134-IJAEMA-SEPTEMBER-2020
Abstract
This paper presents a comparative study of various machine learning techniques applied to stock market prediction. The research evaluates the performance of different algorithms including Support Vector Machines, Random Forests, and Neural Networks for financial time-series forecasting, providing insights into model selection for trading applications.
UGC ApprovedGoogle Scholar
