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Quantifying and Rejecting Outliers: The Grubbs Test01:02

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Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
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Statically Indeterminate Problem Solving01:16

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
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The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
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Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
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一种基于模糊逻辑的显式解集群技术.

Khan Muhammad1, Hylke J Glass2

  • 1Intelligent Information Processing Lab, National Centre of Artificial Intelligence and Department of Mining Engineering, University of Engineering and Technology Peshawar 25000, Pakistan.

Heliyon
|July 24, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种用于地质科学资源估计的新型分类技术. 它通过在集群样本中考虑空间和属性相似性来提高准确性,从而导致不偏见的统计分布.

关键词:
解集群是指解集群的方式.模糊的逻辑 模糊的逻辑模糊-c-意思是模糊-c-的意思.全球估计全球估计

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科学领域:

  • 地质科学 地质科学
  • 地质统计学 在地质统计学
  • 数据科学数据科学数据科学

背景情况:

  • 地理科学资源的空间估计依赖于准确的统计分布.
  • 优选抽样导致资源估计中的参数偏差.
  • 传统的分类方法忽略了空间集群中的属性相似性.

研究的目的:

  • 开发一种分类技术,以考虑空间和属性相似性.
  • 提高资源估计中的统计分布的准确性.
  • 为条件模拟和不确定性建模提供一种公正的方法.

主要方法:

  • 模糊c-means算法用于将样品分类为空间和地化学集群.
  • 基于Mamdani的模糊推理系统,用于导出分类权重.
  • 在GSLib和沃克湖数据集上的应用和验证.

主要成果:

  • 拟议的分类技术明确考虑了空间和属性分类.
  • 模糊的聚类和模糊的推理系统有效地获得了分类权重.
  • 这种新方法与传统的细胞分类相比,显示出更高的准确性.

结论:

  • 开发的分类方法通过解决样本属性相似性来提高资源估计的准确性.
  • 这种方法提供了一种更强大的方法来模拟空间分布的地质科学变量中的不确定性.
  • 该技术比传统的分类方法提供了显著的改进.