Introduction
My name is Momo Hirose, and I am Class of 2024 double-majoring in Computer Science and Global Management.
Abstract
The implementation of policy tech tools that leverage artificial intelligence to improve decision making is gaining attention in public policy. However, tools that not only evaluate historical data and policies, but also propose and simulate policies based on them, have not been fully developed. This study focuses on the research and development of an algorithm for proposing efficient Japan’s national budget allocation for the following year, using neural networks and genetic algorithm methods.
Data Architecture
Poster
Video
Gitlab
https://code.cs.earlham.edu/mhirose20/momo_senior-capstone/-/tree/main