识别和分析二维图像数据集中的权力规律缩放
Ralph Bulanadi1, Patrycja Paruch1
1Department of Quantum Matter Physics, <a href="https://ror.org/01swzsf04">University of Geneva</a>, 1211 Geneva, Switzerland.
Physical review. E
|July 18, 2024
概括
分析二维图像数据来分析权力定律分布是一项挑战. 新的计算工具准确地从接口跟踪中提取缩放参数,使实验和合成数据集的强大分析成为可能.
科学领域:
- 物理 物理学 物理
- 材料科学 材料科学 材料科学
- 数据分析 数据分析
背景情况:
- 权力定律分布描述了大型事件很少发生的现象.
- 分析二维实验数据的功率定律是困难的,因为事件解释和有限的数据.
研究的目的:
- 开发和比较分析事件分布在二维图像中的技术.
- 从基于图像的数据集中准确地提取缩放参数.
主要方法:
- 在二维图像中的跟踪接口位置.
- 将Hill,moments和内核估计器进行比较,用于缩放参数分析.
- 使用实验和合成图像数据集.
主要成果:
- 接口跟踪精确地从二维图像数据中提取缩放参数.
- 开发的技术可以区分权力法和非权力法行为.
- 介绍了用于2D数据集中的权力法适配的计算工具.
结论:
- 精确提取缩放参数可以实现二维功率定律分析.
- 提出的方法为分析复杂的图像数据提供了强大的工具.
- 可靠地识别缩放参数对于理解自然现象至关重要.
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