Homeland Security Today

Beyond the Fog: AI-Powered Plume Modeling for Crisis Readiness and Response

The landscape of emergency management is continually evolving, and the ability to predict and respond to airborne hazards in ...
IEEE

Skill Gap Analysis Through Time Series Forecasting: A Literature Survey on LSTM and Related Models

Abstract: This literature review explores the use of Long Short-Term Memory (LSTM) networks to analyze, identify, and predict skill gaps in colleges catering to the needs of the industry. The rapid ...
Daily Excelsior

Machine Learning Methods Used for Portfolio Optimization and Risk Management

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
GitHub

QuantumStock - Advanced AI Stock Price Prediction System

QuantumStock is a cutting-edge, AI-powered stock price prediction system that harnesses the power of quantum-inspired algorithms and advanced LSTM neural networks with attention mechanisms. This ...
Wall Street Journal

Consumers Power Strongest U.S. Economic Growth in Two Years

After tariffs rose to the highest levels in centuries, the U.S. lost tens of thousands of manufacturing jobs this year. As part of our video series on Trump’s second term, The Wall Street Journal’s ...
GitHub

Time Series Forecasting Engine

Time Series Forecasting Engine is a comprehensive, production-ready Python framework for advanced time series forecasting. It combines statistical models (ARIMA), machine learning approaches (Prophet) ...
IEEE

Dilated Convolution LSTM for Time Series Forecasting in the Field of Energy Consumption

Abstract: The forecast models of energy consumption cover a lot of ground, such as energy storage, abnormal detection, energy management system, and control applications. There are still many problems ...