AZoM

Berkeley Lab Uses Advanced Machine Learning to Optimize Chiral Perovskites

Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the ...
IEEE

CNN and MLP neural network ensembles for packet classification and adversary defense

Abstract: Machine learning techniques such as artificial neural networks are seeing increased use in the examination of communication network research questions. Central to many of these research ...
IEEE

Enhancing Accessibility Through Machine Learning: A Review on Visual and Hearing Impairment Technologies

Abstract: Assistive technologies powered by machine learning are transforming the way sensory impairments are addressed, offering innovative solutions for individuals with hearing and visual ...
Frontiers

Modeling ring current proton distribution using MLP, CNN, LSTM, and transformer networks

This study aims at developing ring current proton flux models using four neural network architectures: a multilayer perceptron (MLP), a convolutional neural network (CNN), a long short-term memory ...
GitHub

sekocha/lammps-polymlp-package

A polynomial MLP represents the potential energy as a polynomial function of linearly independent polynomial invariants of the O(3) group. Developed polynomial MLPs are available in Polynomial Machine ...
Scientific Research Publishing

Weytjens, H., Lohmann, E., & Kleinsteuber, M. (2021). Cash Flow Prediction: MLP and LSTM Compared to ARIMA and Prophet. Electronic Commerce Research, 21, 371-391.

ABSTRACT: This paper explores the transformative role of artificial intelligence (AI) in financial risk management practices within financial institutions. By leveraging machine learning and large ...
Scientific Research Publishing

Maqbool, J., Aggarwal, P., Kaur, R., Mittal, A. and Ganaie, I.A. (2023) Stock Prediction by Integrating Sentiment Scores of Financial News and MLP-Regressor: A Machine Learning ...

ABSTRACT: Accurate prediction of stock prices remains a fundamental challenge in financial markets, with substantial implications for investment strategies and decision making. Although machine ...
GitHub

Deep Neural Network Based Fault Classification and Location Detection in Power Transmission Lines

This project investigates the application of Deep Neural Networks (DNNs) for automated fault classification and fault location in power transmission lines. Using data generated from a simulated 4-bus ...
Quanta Magazine

Novel Architecture Makes Neural Networks More Understandable

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...