Today’s sharing is: 2025 Smart Water Management Development and Solutions (55-page PPT) Smart Water Management: Solving Urban ...

Data management tools that provide contextualization, governance and accessibility are the backbone of effective AI-driven ...

Abstract: Data-driven techniques are reshaping blast furnace iron-making process (BFIP) modeling, but their “black-box” nature often obscures interpretability and accuracy. To overcome these ...

Streamflow drought—when substantially less water than usual moves through rivers—can seriously disrupt the welfare of nearby ...

The landscape of disaster response is rapidly evolving, driven by the increasing complexity, frequency, and scale of emergencies. To meet these challenges, ...

It proved to be an incredibly straightforward day for the bond market. Trading levels were roughly unchanged in early trading. Friendly Fed comments provided a modest boost, but it was the JOLTS data ...

SCE-UA is a lightweight Python package implementing the Shuffled Complex Evolution (SCE-UA) algorithm for global optimization. Designed primarily for hydrological model calibration, it leverages NumPy ...

Hydrological models are essential tools for water resource management and for mitigating extreme hydrological events risks. Although they are crucial for flood forecasting, these models often exhibit ...

Abstract: The temporal correlation of renewable energy generation is inherently influenced by atmospheric systems. To capture its time-varying characteristics, a data-driven modeling framework is ...

A Model Context Protocol (MCP) implementation for Financial Modeling Prep, enabling AI assistants to access and analyze financial data, stock information, company fundamentals, and market insights.