Modeling a Neutron Yield Model

B2FIND2026-04-28 收录

中子产额预测

物理机器学习

数据链接：

https://b2find.eudat.eu/dataset/cde94876-4ffc-5536-826f-cb0a0132cf61 数据链接链接失效反馈

官方服务：

资源简介：

Models and scripts to calculate an artifical neural network model for neutron production yields.

用于计算中子产额的人工神经网络（Artificial Neural Network, ANN）模型及其配套脚本

Pre-processed data - Git Repo - HSM

蛋白质-肽相互作用预测

物理机器学习

Pre-processed data associated with the git repository - https://github.com/aqlaboratory/hsm. This repo supports the following publication. Reference:Cunningham JM, Koytiger G, Sorger PK, AlQuraishi M

NIAID Data Ecosystem130

PGML Dataset

电磁场模拟

物理机器学习

Matlab mat files containing datasets for PGML training and validation Each filename describes both its resolution (lowRes, medRes, highRes) and the plasma wavelength of the metallic ma

Figshare2025-02-21 更新80

Datasets and models of paper "A large SPH Collision Database and Machine Learning Framework for Predicting Post-Impact Remnants: Implications for Super-Mercury Formation"

行星碰撞模拟

物理机器学习

Dataset and models from the paper: ```Dou J., Carter P. J., Leinhardt Z. M., 2025 "A large SPH Collision Database and Machine Learning Framework for Predicting Post-Impact Remnants: Implications f

Zenodo2026-06-18 更新20

eirikfagerbakke/zk

数值模拟

物理机器学习

Zakharov–Kuznetsov方程数据集包含了解该方程数值解的数据，该方程是Korteweg–de Vries方程的多维推广，用于模拟磁化等离子体中的非线性波传播。数据通过六阶Gauss–Legendre时间积分器和六阶中心有限差分法生成，并在128×128的空间网格上离散化，直到最终时间T=2。每个轨迹包含32个均匀分布的时间快照。初始条件包括两个相互作用波，它们的位置和振幅随机化，适用于

Hugging Face2025-11-10 更新90

Prediction of heat transfer parameters of nuclear reactor based on physical information machine learning algorithm

核反应堆热工水力

物理机器学习

The accurate prediction of the heat transfer coefficient (HTC) under extremely high parameter conditions in nuclear reactors is crucial for reactor design and operation. However, this involves complex

科学数据银行2024-08-29 更新70

Modeling a Neutron Yield Model

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