Wired

AI Models Are Starting to Learn by Asking Themselves Questions

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...
IEEE

Enhanced privacy in Real time Data offloading using Federated Hybrid MLP and LSTM approach for Optimized solutions

Abstract: Using a privacy-preserving federated hybrid architecture that combines Long Short-Term Memory (LSTM) and Multilayer Perceptron networks (MLP), the research suggests a novel method. Our ...
C&EN

Research on Remaining Useful Life Prediction of PEMWE Stack Based on the LSTM-iTransformer Model

In the context of global energy shortages, traditional energy sources face issues of limited reserves and high prices. As a result, the importance of energy storage technology is increasingly ...
devdiscourse

AI-powered forecasting boosts retail efficiency: LSTM outshines traditional models

In a new comparative analysis of artificial intelligence applications in retail, researchers have revealed that advanced deep learning models can dramatically enhance the accuracy of demand ...
GitHub

mohansree14/Bayesian-Deep-Learning-for-Probabilistic-Financial-Forecasting

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
Frontiers

A hybrid LSTM–transformer model for accurate remaining useful life prediction of lithium-ion batteries

With the widespread application of lithium-ion batteries in electric vehicles and energy storage systems, health monitoring and remaining useful life prediction have become critical components of ...
GitHub

Stock Price Prediction Model

The goal of this project is to predict future stock prices by training on historical stock data. Please describe the specific objective here, such as: [e.g., to predict the closing price for a ...
Frontiers

Forecasting sea level rise using enhanced deep learning models

Climate change has significantly impacted vulnerable communities globally, with rising temperatures caused by greenhouse gas emissions accelerating global Sea Level Rise (SLR), threatening coastal ...
Scientific Research Publishing

Kim, H., & Won, C. (2018). Forecasting the Volatility of Stock Price Index: A Hybrid Model Integrating LSTM with Multiple GARCH-Type Models. Computational Economics, 51, 29-49.

ABSTRACT: The application of artificial intelligence in stock price forecasting is an important area of research at the intersection of finance and computer science, with machine learning techniques ...
Scientific Research Publishing

Kulshreshtha, S., & Vijayalakshmi, A. (2020). An ARIMA-LSTM Hybrid Model for Stock Market Prediction Using Live Data. Journal of Engineering Science and Technology Review, 13 ...

ABSTRACT: The application of artificial intelligence in stock price forecasting is an important area of research at the intersection of finance and computer science, with machine learning techniques ...