Items where Author is "Rajasekar, M."

Article

Rukmani Devi, S. and Selvaraju, P. and Padma, R. and Balamurugan, A. G. and Pandiarajan, T. and Rajasekar, M. (2025) Data Science Applications Using Extreme Gradient Boosting (XGBoost) and Random Forest for Predictive Analytics in Financial Sectors: Algorithm Optimization, Intelligent Systems, Blockchain, Cryptography and Cybersecurity. Mathematical Methods in Artificial Intelligence. pp. 223-234.

Legapriyadharshini, N. and Nanthini, S. and Parameswari, R. and Kalarani, P. and Vijayalakshmi, R. and Rajasekar, M. (2025) Predictive Maintenance in Smart Systems with Temporal Convolutional Networks (TCN) and Autoencoders: Algorithm Optimization, Intelligent Systems, Blockchain, Cryptography and Cybersecurity. Mathematical Methods in Artificial Intelligence: Algorithm Optimization, Intelligent Systems, Blockchain, Cryptography and Cybersecurity. pp. 49-62.

Book Section

Rukmani Devi, S. and Selvaraju, P. and Padma., R. and Shaji, Alan and Sasikala, P. and Rajasekar, M. (2025) Deep Learning with Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) for AI-Driven Smart Home Automation. In: Mathematical Methods in Artificial Intelligence. De Gruyter, pp. 153-164. ISBN 9783112234969