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<p>The purpose of exploring the new theoretical system of college education development is to improve college students’ quality in all aspects. This paper constructs a new theoretical system of college education development based on the new theory of college education development--”three comprehensive education” theory. The fuzzy credibility measure and credibility distribution are used to explain the fuzzy processing theory, and the uncertainty index of the fuzzy processing model is optimized based on the cross-rhombus search algorithm to improve the search speed of the fuzzy processing model. Data experimental analysis is conducted for the fuzzy ICDS multi-optimization principle. Regarding search speed, the average search speed improvement of the algorithm in this paper relative to the CD algorithm saves about 1.37 to 4.69 points per block. It improves classification accuracy by 12.02% and 7.65% compared to the best fuzzy and GFCM algorithms, respectively. This shows that using the fuzzy ICDS multi-optimization principle can help analyze the effectiveness of the “three holistic education” theory in constructing the education development system and provide a reference for planning and implementing the new education development system.</p>
</abstract>

The purpose of exploring the new theoretical system of college education development is to improve college students’ quality in all aspects. This paper constructs a new theoretical system of college education development based on the new theory of college education development--”three comprehensive education” theory. The fuzzy credibility measure and credibility distribution are used to explain the fuzzy processing theory, and the uncertainty index of the fuzzy processing model is optimized based on the cross-rhombus search algorithm to improve the search speed of the fuzzy processing model. Data experimental analysis is conducted for the fuzzy ICDS multi-optimization principle. Regarding search speed, the average search speed improvement of the algorithm in this paper relative to the CD algorithm saves about 1.37 to 4.69 points per block. It improves classification accuracy by 12.02% and 7.65% compared to the best fuzzy and GFCM algorithms, respectively. This shows that using the fuzzy ICDS multi-optimization principle can help analyze the effectiveness of the “three holistic education” theory in constructing the education development system and provide a reference for planning and implementing the new education development system.

The construction of a new theoretical system of university education development based on the principle of multi-optimization of fuzzy ICDS

Applied Mathematics and Nonlinear Sciences

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

The purpose of exploring the new theoretical system of college education development is to improve college students’ quality in all aspects. This paper...

The construction of a new theoretical system of university education development based on the principle of multi-optimization of fuzzy ICDS

Publicado en línea: 25 sept 2023

Páginas: -

Recibido: 05 dic 2022

Aceptado: 05 abr 2023

DOI: https://doi.org/10.2478/amns.2023.2.00365

Palabras clave
Fuzzy processing model, Trustworthiness distribution, ICDS algorithm, Trustworthiness measure, Uncertainty index

© 2023 Peng Wang et al., published by Sciendo

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

The construction of a new theoretical system of university education development based on the principle of multi-optimization of fuzzy ICDS

Publicado en línea: 25 sept 2023

Páginas: -

Recibido: 05 dic 2022

Aceptado: 05 abr 2023

DOI: https://doi.org/10.2478/amns.2023.2.00365

Palabras claveFuzzy processing model, Trustworthiness distribution, ICDS algorithm, Trustworthiness measure, Uncertainty index

© 2023 Peng Wang et al., published by Sciendo

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

Palabras clave
Fuzzy processing model, Trustworthiness distribution, ICDS algorithm, Trustworthiness measure, Uncertainty index