We present a knowledge‐guided machine learning framework for operational hydrologic forecasting at the catchment scale. Our approach, a Factorized Hierarchical Neural Network (FHNN), has two main ...

Hugo Marques explains how to navigate Java concurrency at scale, moving beyond simple frameworks to solve high-throughput IO ...

Abstract: One of the most important and lethal natural disasters of this century is flooding. The deficiency of a comprehensive flood forecasting system has resulted in significant losses of life and ...

Prime Minister Anutin Charnvirakul has set up a special committee to study the lessons learned from the 2011 and 2023 floods, aiming to prevent future disasters and improve flood prevention strategies ...

PeakPicker uses machine learning to automate the identification of flood peaks in river gage streamflow data. The system is trained on manually selected peaks and can: Train models on gages with known ...

Eli Bieri has received funding from philanthropic agencies to support his PhD research. Jodi Rowley is the Lead Scientist of the Australian Museum's citizen science project, FrogID. She has received ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Community driven content discussing all aspects of software development from DevOps to design patterns. The AWS Machine Learning Associate certification validates your ability to configure, build, and ...

Floods represent the most frequent natural hazard, generating significant impacts on people as well as considerable economic and environmental losses worldwide. These events are particularly ...

The reconstruction of flood-devastated rural Punjab demands a radical departure from conventional donor-driven aid models. Grounded in the transformative praxis of Paulo Freire, this framework ...