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相关概念视频

Outliers and Influential Points01:08

Outliers and Influential Points

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An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
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Local Attraction01:22

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Local attraction refers to disturbances in compass readings caused by magnetic influences from nearby objects such as metal fences, buried pipes, vehicles, buildings, power lines, or natural iron ore deposits. Small items like wristwatches, steel tools, or belt buckles can also interfere with the compass by creating local magnetic fields that distort the Earth's natural magnetic field. These distortions lead to inaccurate readings, posing navigation and land surveying challenges.Local...
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Sequence Networks of Rotating Machines01:24

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
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In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
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相关实验视频

Updated: Jun 9, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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在社交网络中最大限度地影响使用结合本地特征和基于深度学习的节点嵌入.

Asgarali Bouyer1,2, Hamid Ahmadi Beni3, Amin Golzari Oskouei2

  • 1Department of Software Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran.

Big data
|October 22, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了影响力最大化嵌入技术 (ETIM),这是一种新的算法,可以显著提高感染率并减少大规模网络中的计算时间. 通过图形嵌入和局部结构特征,ETIM有效地识别了有影响力的节点.

关键词:
图形嵌入 图形嵌入.独立的级联模型.影响力最大化 影响力最大化有影响力的节点.社交网络 社交网络

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科学领域:

  • 网络科学 网络科学
  • 计算机科学 计算机科学
  • 数据挖掘 数据挖掘

背景情况:

  • 影响力最大化对于病毒营销和信息传播至关重要,但在大型网络中面临着低感染率和高时间复杂性等挑战.
  • 现有的方法通常由于计算需求或依赖自由参数而难以扩展,从而限制了它们的实际应用.
  • 解决这些局限性对于在复杂的现实世界网络中开发高效的影响力最大化策略至关重要.

研究的目的:

  • 提出一种新的局部启发式算法,即影响最大化嵌入技术 (ETIM),旨在克服现有的影响最大化方法的局限性.
  • 通过减少搜索空间和计算开销,提高大规模网络影响力最大化的效率和有效性.
  • 与现有的算法相比,提高感染率和解决方案质量.

主要方法:

  • ETIM采用外分解,图形嵌入和缩小,整合了候选节点选择的本地结构特征.
  • 基于深度学习的节点嵌入技术为候选节点生成多维向量,捕捉复杂的网络关系.
  • 节点对扩散的依赖性是使用本地拓特征计算的,其次是根据结合的本地和嵌入式特征识别有影响力的节点.

主要成果:

  • 当使用独立级联模型进行评估时,ETIM表现出竞争力,并在解决方案质量方面取得了卓越的表现.
  • 该算法通过专注于网络外和拓特征,显著降低了计算开销和搜索空间.
  • ETIM在感染率上取得了实质性的改善,平均比集体影响全球算法高出12%,同时速度更快.

结论:

  • 影响力最大化嵌入技术 (ETIM) 为大规模网络中的影响力最大化问题提供了高效和有效的解决方案.
  • 通过将图形嵌入与局部结构分析相结合的混合方法,ETIM成功地解决了时间复杂性和解决方案质量的挑战.
  • 拟议的方法为需要在复杂网络结构中有效识别有影响力的节点的应用提供了有希望的进步.