Scientific Research Publishing

A Hybrid CNN-LSTM Variational Autoencoder for Treatment Response Prediction in Synthetic Psychiatric Data ()

Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of conventional ...
devdiscourse

AI for Energy Security: Study Compares LSTM and FFNN in Solar Grid Anomaly Detection

The study “Smart Grid Cybersecurity: Anomaly Detection in Solar Power Systems Using Deep Learning” is the joint effort of researchers from Noida International University and Dayananda Sagar University ...
Dark Reading

MathWorks, Creator of MATLAB, Confirms Ransomware Attack

MathWorks, a mathematical computing software company headquartered in Natick, Mass., disclosed a ransomware attack in an update to its website on Monday. MathWorks is known for creating the MATLAB ...
IEEE

Deep Transfer Learning Based on Hybrid Swin Transformers With LSTM for Intrusion Detection Systems in IoT Environment

Abstract: Extensive growth in the number of Internet Of Things (IoT) devices has significantly increased susceptibility to various cyber-attacks and hence emphasized the need for robust intrusion ...
Scientific Research Publishing

Xu, Y., Hu, C., Wu, Q., Jian, S., Li, Z., Chen, Y. et al. (2022). Research on Particle Swarm Optimization in LSTM Neural Networks for Rainfall-Runoff Simulation. Journal of ...

ABSTRACT: Accurate precipitation forecasting is crucial for mitigating the impacts of extreme weather events and enhancing disaster preparedness. This study evaluates the performance of Long ...
IEEE

LSTM neural network for current prediction and harmonic analysis in solar power system

Abstract: Distributed energy resources (DERs) are increasingly integrated with the power grid, affecting its operation, stability, and reliability. This decentralized generation influences the ...