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<p>In this paper, based on digital means and technical philosophy, the histogram algorithm in the Light GBM model is used to calculate the floating point values of the raw data for the analysis of vocational education service for rural revitalization so that each of its features is converted into a histogram. In order to prevent the feature training overfitting problem of the Light GBM model, the LightGBM model is optimized by the iterative tree MPA algorithm, and the prediction model of returning to poverty risk based on IMPA-LightGBM is constructed. Starting from the current situation of vocational education service for rural revitalization, we put forward research hypotheses to realize the research design of vocational education accurate poverty alleviation service for rural revitalization and carry out an example analysis of vocational education service for rural revitalization combined with digital technology. The results show that in terms of model performance, the WAPE values of the return-to-poor risk values obtained from the prediction of the IMPA-LightGBM model are all lower than 5.5%, so the prediction effect is relatively satisfactory, and the return-to-poor risk values of poverty-eradicating households can be effectively predicted. On the practice road analysis, the standard deviation (SD) of the rural revitalization development index in China as a whole decreased from 0.63 to 0.52, which means that the differences in rural revitalization among provinces are decreasing. This study explores the synergistic development of the community of interest between vocational education and rural revitalization through the cultivation of new vocational farmers.</p>
</abstract>

In this paper, based on digital means and technical philosophy, the histogram algorithm in the Light GBM model is used to calculate the floating point values of the raw data for the analysis of vocational education service for rural revitalization so that each of its features is converted into a histogram. In order to prevent the feature training overfitting problem of the Light GBM model, the LightGBM model is optimized by the iterative tree MPA algorithm, and the prediction model of returning to poverty risk based on IMPA-LightGBM is constructed. Starting from the current situation of vocational education service for rural revitalization, we put forward research hypotheses to realize the research design of vocational education accurate poverty alleviation service for rural revitalization and carry out an example analysis of vocational education service for rural revitalization combined with digital technology. The results show that in terms of model performance, the WAPE values of the return-to-poor risk values obtained from the prediction of the IMPA-LightGBM model are all lower than 5.5%, so the prediction effect is relatively satisfactory, and the return-to-poor risk values of poverty-eradicating households can be effectively predicted. On the practice road analysis, the standard deviation (SD) of the rural revitalization development index in China as a whole decreased from 0.63 to 0.52, which means that the differences in rural revitalization among provinces are decreasing. This study explores the synergistic development of the community of interest between vocational education and rural revitalization through the cultivation of new vocational farmers.

Analysis of the Practical Path of Vocational Education Serving Rural Revitalization by Digital Means and Philosophy of Technology

Henan University of Science and Technology

Applied Mathematics and Nonlinear Sciences

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

In this paper, based on digital means and technical philosophy, the histogram algorithm in the Light GBM model is used to calculate the floating point values...

Analysis of the Practical Path of Vocational Education Serving Rural Revitalization by Digital Means and Philosophy of Technology

Online veröffentlicht: 06. Dez. 2023

Seitenbereich: -

Eingereicht: 27. Dez. 2022

Akzeptiert: 16. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01406

Schlüsselwörter
Light GBM model, MPA algorithm, Histogram algorithm, Iterative tree, Rural revitalization

© 2023 Feifei Tian, published by Sciendo

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

Analysis of the Practical Path of Vocational Education Serving Rural Revitalization by Digital Means and Philosophy of Technology

Online veröffentlicht: 06. Dez. 2023

Seitenbereich: -

Eingereicht: 27. Dez. 2022

Akzeptiert: 16. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01406

SchlüsselwörterLight GBM model, MPA algorithm, Histogram algorithm, Iterative tree, Rural revitalization

© 2023 Feifei Tian, published by Sciendo

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

Schlüsselwörter
Light GBM model, MPA algorithm, Histogram algorithm, Iterative tree, Rural revitalization