Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Transformers01:26

Transformers

1.2K
A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
1.2K
Transformers in Distribution System01:27

Transformers in Distribution System

165
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
165
The Ideal Transformer01:26

The Ideal Transformer

913
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
913
Types Of Transformers01:16

Types Of Transformers

1.1K
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
1.1K
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

213
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
213
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

807
The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
807

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A novel computational framework for tumor-specific T cell antigen identification using a deep neural network.

Journal of computer-aided molecular design·2026
Same author

Focusing on legal cases: Automatic classification of legal documents with sentence embeddings and deep learning models.

PloS one·2026
Same author

Corrigendum to "LLM predicts human behavior: A BERT-based approach for conscientiousness personality trait detection from online content" [Acta Psychologica 266 (2026), 106832].

Acta psychologica·2026
Same author

AIM2 framework for smart marketing innovation using AI driven consumer analytics with SOR neural networks and XGBoost in Saudi retail.

Scientific reports·2026
Same author

LLM predicts human behavior: A BERT-based approach for conscientiousness personality trait detection from online content.

Acta psychologica·2026
Same author

Neuropeptide and cytokines expression in long COVID-19 related neuropsychological sequelae: insights into NK1R-mediated neuroinflammation and <i>in silico</i> therapeutic targeting.

Frontiers in cellular neuroscience·2026

相关实验视频

Updated: Sep 16, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

692

一个基于变压器的架构,用于在个性化推系统中协作过建模.

Hikmat Ullah Khan1, Anam Naz2, Fawaz Khaled Alarfaj3

  • 1Department of Information Technology, University of Sargodha, Punjab, Pakistan. dr.hikmat.niazi@gmail.com.

Scientific reports
|July 8, 2025
PubMed
概括

一个新的AI模型,MetaBERTTransformer4Rec (MBT4R),通过了解用户偏好,显著改善电影推. 它的性能优于现有的方法,通过个性化的电影建议提高用户满意度.

关键词:
人工智能的人工智能是人工智能.协作过是一种合作过.深度学习是一种深度学习.个性化 个性化推系统是一个推系统.

更多相关视频

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

587
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

914

相关实验视频

Last Updated: Sep 16, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

692
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

587
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

914

科学领域:

  • 人工智能的人工智能
  • 推系统是一个推系统.
  • 机器学习 机器学习

背景情况:

  • 推系统对于电子商务,社交媒体和娱乐领域的个性化内容提供至关重要.
  • 准确的用户偏好建模对于电影推系统来说至关重要,以提高用户满意度.
  • 人工智能 (AI) 越来越多地用于提高这些系统的精度和适应性.

研究的目的:

  • 为电影推提出一种新的基于变压器的架构,MetaBERTTransformer4Rec (MBT4R).
  • 为了证明MBT4R在现有最先进的方法上的优势.
  • 提高电影推的准确性和个性化,以提高用户满意度.

主要方法:

  • 开发了一个新的基于变压器的架构,MetaBERTTransformer4Rec (MBT4R).
  • 利用自我注意机制来捕捉顺序依赖和上下文关系.
  • 在两个MovieLens数据集上进行实证分析.

主要成果:

  • MBT4R获得了最低的RMSE (0.62) 和MAE (0.45),以及最高的R2 (0.39).
  • 该模型显著超过了传统的机器学习,矩阵分解和深度学习基准.
  • 与DT,KNN,RF,XGB,SVD和GRU模型相比,表现出优越的性能.

结论:

  • 人工智能技术,特别是MBT4R模型,有效地提高了推系统的准确性和个性化.
  • 拟议的模型为个性化用户体验的未来进步提供了一条途径.
  • 准确预测用户偏好导致量身定制的电影建议和提高用户满意度.