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

<p>In recent years, China has set off a round of “war for talents” all over the world, and college graduates, as a high-quality group of people in the labor market, are the focus of the competition for talent across the globe. How to retain and attract college students is an essential issue in promoting the construction of the Chengdu-Chongqing Twin Cities Economic Circle. An employment prediction algorithm for graduates is proposed in this paper that employs the HMIGW algorithm for feature selection to obtain the optimal feature subset. Then, it uses the XGBoost algorithm to predict the employment situation. In the meantime, a method for selecting fractal dimension attributes based on the binary firefly algorithm is used, and an algorithm for extracting employment willingness influence factor is proposed. In the analysis of the employment intention of college graduates in the Chengdu-Chongqing region, the number of college graduates in 2023 is 366,000; the growth reaches 18.83%, but the number of college graduates who stay in local employment is only 112,000. The mean value of all indicators for college graduates in the Chengdu-Chongqing region is below 4, and their overall satisfaction is low. The group not willing to stay in the area for employment valued the soft environment of the unit (P=0.012) and the economic level of the region (P=0.024) more than the group willing to stay in the area for employment.</p>
</abstract>

In recent years, China has set off a round of “war for talents” all over the world, and college graduates, as a high-quality group of people in the labor market, are the focus of the competition for talent across the globe. How to retain and attract college students is an essential issue in promoting the construction of the Chengdu-Chongqing Twin Cities Economic Circle. An employment prediction algorithm for graduates is proposed in this paper that employs the HMIGW algorithm for feature selection to obtain the optimal feature subset. Then, it uses the XGBoost algorithm to predict the employment situation. In the meantime, a method for selecting fractal dimension attributes based on the binary firefly algorithm is used, and an algorithm for extracting employment willingness influence factor is proposed. In the analysis of the employment intention of college graduates in the Chengdu-Chongqing region, the number of college graduates in 2023 is 366,000; the growth reaches 18.83%, but the number of college graduates who stay in local employment is only 112,000. The mean value of all indicators for college graduates in the Chengdu-Chongqing region is below 4, and their overall satisfaction is low. The group not willing to stay in the area for employment valued the soft environment of the unit (P=0.012) and the economic level of the region (P=0.024) more than the group willing to stay in the area for employment.

Study on the Employment Intention and Influencing Factors of College Graduates in Chengdu-Chongqing Region under the Background of “Talent Competition”

Applied Mathematics and Nonlinear Sciences

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

In recent years, China has set off a round of “war for talents” all over the world, and college graduates, as a high-quality group of people in the labor...

Study on the Employment Intention and Influencing Factors of College Graduates in Chengdu-Chongqing Region under the Background of “Talent Competition”

Online veröffentlicht: 15. Mai 2024

Seitenbereich: -

Eingereicht: 28. Jan. 2024

Akzeptiert: 05. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1088

Schlüsselwörter
Employment willingness, HMIGW algorithm, XGBoost algorithm, Firefly algorithm

© 2024 Fan Zhu, published by Sciendo

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

Study on the Employment Intention and Influencing Factors of College Graduates in Chengdu-Chongqing Region under the Background of “Talent Competition”

Online veröffentlicht: 15. Mai 2024

Seitenbereich: -

Eingereicht: 28. Jan. 2024

Akzeptiert: 05. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1088

SchlüsselwörterEmployment willingness, HMIGW algorithm, XGBoost algorithm, Firefly algorithm

© 2024 Fan Zhu, published by Sciendo

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

Schlüsselwörter
Employment willingness, HMIGW algorithm, XGBoost algorithm, Firefly algorithm