An Ensemble of Component-Based and Population-Based Self-Organizing Maps for the Identification of the Degradation State of Insulated-Gate Bipolar Transistors

2018 ◽  
Vol 67 (3) ◽  
pp. 1304-1313 ◽  
Author(s):  
Marco Rigamonti ◽  
Piero Baraldi ◽  
Allegra Alessi ◽  
Enrico Zio ◽  
Daniel Astigarraga ◽  
...  
Keyword(s):  
Population Based ◽  
Bipolar Transistors ◽  
Insulated Gate Bipolar Transistors ◽  
Self Organizing Maps ◽  
Degradation State ◽  
Self Organizing

A Psychographic Segmentation of Kuwaiti Travelers Using Self-Organizing Maps

2019 ◽  
Vol 24 (1) ◽  
pp. 87-92 ◽  
Author(s):  
Yvette Reisinger ◽  
Mohamed M. Mostafa ◽  
John P. Hayes
Keyword(s):  
Self Organizing Maps ◽  
Self Organizing

Self Organizing Maps, Pattern Recognition and Financial Crises

2011 ◽  
Author(s):  
Sylvain Barthelemy ◽  
Pascal Devaux ◽  
Francois Faure ◽  
Matthieu Pautonnier
Keyword(s):  
Pattern Recognition ◽  
Financial Crises ◽  
Self Organizing Maps ◽  
Self Organizing

scholarly journals Research on Small Square PCB Rogowski Coil Measuring Transient Current in the Power Electronics Devices

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4176 ◽  
Author(s):  
Chaoqun Jiao ◽  
Juan Zhang ◽  
Zhibin Zhao ◽  
Zuoming Zhang ◽  
Yuanliang Fan
Keyword(s):  
Power Electronics ◽  
Printed Circuit Board ◽  
Electronic Devices ◽  
Rogowski Coil ◽  
Bipolar Transistors ◽  
Circuit Board ◽  
Power Electronic ◽  
Insulated Gate Bipolar Transistors ◽  
Printed Circuit ◽  
Internal Structures

With the development of China’s electric power, power electronics devices such as insulated-gate bipolar transistors (IGBTs) have been widely used in the field of high voltages and large currents. However, the currents in these power electronic devices are transient. For example, the uneven currents and internal chip currents overshoot, which may occur when turning on and off, and could have a great impact on the device. In order to study the reliability of these power electronics devices, this paper proposes a miniature printed circuit board (PCB) Rogowski coil that measures the current of these power electronics devices without changing their internal structures, which provides a reference for the subsequent reliability of their designs.

Using self organizing maps to analyze larval fish assemblage vertical dynamics through environmental-ontogenetic gradients

2021 ◽  
pp. 107410
Author(s):  
I. Álvarez ◽  
J.S. Font-Muñoz ◽  
I. Hernández-Carrasco ◽  
C. Díaz-Gil ◽  
P.M. Salgado-Hernanz ◽  
...  
Keyword(s):  
Fish Assemblage ◽  
Larval Fish ◽  
Self Organizing Maps ◽  
Self Organizing

scholarly journals The Spread of the COVID-19 Outbreak in Brazil: An Overview by Kohonen Self-Organizing Map Networks

Medicina ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 235
Author(s):  
Diego Galvan ◽  
Luciane Effting ◽  
Hágata Cremasco ◽  
Carlos Adam Conte-Junior
Keyword(s):  
The Self ◽  
Self Organizing Map ◽  
Virus Spread ◽  
Self Organizing Maps ◽  
The North ◽  
Som Clustering ◽  
Unsupervised Neural Networks ◽  
Mining Tools ◽  
Temporal Spread ◽  
Self Organizing

Background and objective: In the current pandemic scenario, data mining tools are fundamental to evaluate the measures adopted to contain the spread of COVID-19. In this study, unsupervised neural networks of the Self-Organizing Maps (SOM) type were used to assess the spatial and temporal spread of COVID-19 in Brazil, according to the number of cases and deaths in regions, states, and cities. Materials and methods: The SOM applied in this context does not evaluate which measures applied have helped contain the spread of the disease, but these datasets represent the repercussions of the country’s measures, which were implemented to contain the virus’ spread. Results: This approach demonstrated that the spread of the disease in Brazil does not have a standard behavior, changing according to the region, state, or city. The analyses showed that cities and states in the north and northeast regions of the country were the most affected by the disease, with the highest number of cases and deaths registered per 100,000 inhabitants. Conclusions: The SOM clustering was able to spatially group cities, states, and regions according to their coronavirus cases, with similar behavior. Thus, it is possible to benefit from the use of similar strategies to deal with the virus’ spread in these cities, states, and regions.

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