<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The analysis and structural transformation of power-related picture elements is an essential result of regional power grid research. This paper proposes a new idea for extracting monolithic insulator images based on analysing the characteristics of scanned colour grid power insulators. At the same time, the article extracts the RGB colour matrix of the insulator based on the BP neural network algorithm. Then, it uses it as a characteristic parameter for training and analysis. Combining the characteristics of image data, it is found that the model proposed in this paper enhances the ability to express images, thereby improving the accuracy of image classification. Furthermore, many experiments on the accurate data set of insulator monoliths show the effectiveness of this model.</p>
</abstract>

The analysis and structural transformation of power-related picture elements is an essential result of regional power grid research. This paper proposes a new idea for extracting monolithic insulator images based on analysing the characteristics of scanned colour grid power insulators. At the same time, the article extracts the RGB colour matrix of the insulator based on the BP neural network algorithm. Then, it uses it as a characteristic parameter for training and analysis. Combining the characteristics of image data, it is found that the model proposed in this paper enhances the ability to express images, thereby improving the accuracy of image classification. Furthermore, many experiments on the accurate data set of insulator monoliths show the effectiveness of this model.

Mathematical model of transforming image elements to structured data based on BP neural network

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The analysis and structural transformation of power-related picture elements is an essential result of regional power grid research. This paper proposes a new...

Mathematical model of transforming image elements to structured data based on BP neural network

Online veröffentlicht: 15. Dez. 2021

Seitenbereich: 257 - 266

Eingereicht: 16. Juni 2021

Akzeptiert: 24. Sept. 2021

DOI: https://doi.org/10.2478/amns.2021.1.00084

Schlüsselwörter
BP neural network, image elements, feature extraction, insulator monolithic, structured, data conversion

© 2021 Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mathematical model of transforming image elements to structured data based on BP neural network

Online veröffentlicht: 15. Dez. 2021

Seitenbereich: 257 - 266

Eingereicht: 16. Juni 2021

Akzeptiert: 24. Sept. 2021

DOI: https://doi.org/10.2478/amns.2021.1.00084

SchlüsselwörterBP neural network, image elements, feature extraction, insulator monolithic, structured, data conversion

© 2021 Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
BP neural network, image elements, feature extraction, insulator monolithic, structured, data conversion