Numerical Framework for Data Driven Predictive Modeling of Complex Systems

Abstract

The emergence of modern machine learning (ML) techniques has offered the potential to radically improve our scientific research. It is now possible to employ deep learning methods, particularly deep neural network (DNN), to enable more informed predictions and decision making. This project serves as one effort to spearhead in this direction, with a particular focus on modeling of complex systems where no reliable mathematical models are available. The major objective of the proposed project is to develop a mathematical and numerical framework for data driven predictive modeling of complex systems using modern deep learning methods.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 07, 2023
Source ID
FA95502210011

Entities

People

  • Dongbin Xiu

Organizations

  • Air Force Office of Scientific Research
  • Ohio State University
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Computational Fluid Dynamics (CFD)
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks