@article{JIA2026, 
author = {Xiaowen JIA and Haiying FAN},
title = {RESEARCH ON SOLVING THE BRACHISTOCHRONE PROBLEM USING NEURAL NETWORK MODEL ALGORITHM},
year = {2026},
journal = {Physics and Engineering},
volume = {36},
number = {2},
pages = {173-178},
keywords = {neural network, brachistochrone, TensorFowl},
url = {https://www.sciopen.com/article/10.26599/PHYS.2026.9320227},
doi = {10.26599/PHYS.2026.9320227},
abstract = {The basic algorithmic approach of neural network models for solving the brachisto-chrone problem was analyzed. The Tensor Fowl deep learning framework's neural network module was utilized to numerically solve the brachistochrone problem, with specific solution steps provided and the impact of neural network hyperparameters on the solution results discussed. Unlike traditional neural network applications, this study explored the application of neural network models in variational function fitting, offering references and insights for applying neural networks and other large AI models to university physics teaching, experiments, and research.}
}