Understanding Multivariate Models: Forecasting Investment Outcomes

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...

NOAA says new AI-driven weather models improve forecast speed, accuracy

The National Oceanic and Atmospheric Administration has introduced a new suite of weather forecasting models that are driven by Artificial Intelligence and are expected to deliver faster and more ...
Android Central on MSN

Gemini's deep research transforms reports with dynamic visuals and interactive simulations

Gemini's Deep Research feature can now build interactive visual reports from its findings, but only for Google AI Ultra ...
United States Army

Leveraging Digital Engineering to Modernize Munition Production

Digital engineering and modeling and simulation (M&S) are transformative approaches that enable precision, efficiency and ...
Opinion

2026 S&P 500 Outlook: The Party Is Not Over

Discover why the S&P 500 could reach 7900 by 2026, driven by AI and policy support. Learn market risks and where future opportunities may emerge.
Scientific Research Publishing

Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms ()

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.
GitHub

STRIDE Threat Analysis Framework with MITRE ATT&CK Integration

This project is a Python-based, end-to-end STRIDE threat modeling and analysis framework with MITRE ATT&CK mapping. It enables you to: ...

Can AI help forecasters better predict destructive hurricanes?

AI-assisted weather models were put to the test this past hurricane season, with some experts saying they will become a ...
Open Knowledge Repository - World Bank

The World Bank's MFMod Framework in Python with Modelflow

MFMod is the World Bank’s work-horse macro-structural economic modeling framework. It exists both as a linked system of 184 ...
IEEE

TSB-Forecast: A Short-Term Load Forecasting Model in Smart Cities for Integrating Time Series Embeddings and Large Language Models

Abstract: In smart cities, energy management systems are essential for efficient resource utilization, enhanced operational efficiency, and sustainability promotion. This work presents a novel load ...
IEEE

Variational Hierarchical N-BEATS Model for Long-Term Time-Series Forecasting

Abstract: Long-term time-series forecasting (LTSF) is gaining increasing attention due to its significant challenges and real-world applications. However, existing studies underexplore the role of ...