Senior Project Advisor
Brian Hutchinson
Document Type
Project
Publication Date
Spring 2025
Keywords
multi-sector dynamics model, emulator, deep neural network, input space, energy, water, land
Abstract
Multi-sector dynamics (MSD) models are capable of predicting the evolution of highly complex human-earth interactions. The nuanced relationship between these interactions requires sophisticated modeling. This sophistication poses difficulty for researchers performing exploratory analysis, as it increases the time and computational power necessary to run the model. Previous work created a deep neural network emulator of one popular MSD model, with significantly reduced runtime. However, one of the limitations of the emulator is the limited scope of inputs that it accepts compared to the full MSD model. This paper describes work extending this previous emulator to accept an expanded input space – 233 inputs, as opposed to the original 12 inputs – as a step toward more comprehensive emulation of MSD models. In our work we demonstrate that our emulator is highly accurate, obtaining R2 metrics over 0.98 on a heldout test set, mirroring the successful results of past work despite the greater complexity of the emulation problem.
Department
Computer Science
Recommended Citation
Cox, Cooper, "Honors Capstone Report: Emulating the Global Change Analysis Model with an Expanded Input Space" (2025). WWU Honors College Senior Projects. 932.
https://cedar.wwu.edu/wwu_honors/932
Type
Text
Rights
Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.
Language
English
Format
application/pdf