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

<p>With the rise of artificial intelligence technology in the context of digital development of big data and information, the biosafety management method under the traditional model can hardly fit the development requirements of the times, and the biosafety management under the traditional model has various problems such as slow manual efficiency, tedious management work, and humanization of work. This paper focuses on studying a biosafety management strategy based on a multiple regression model, then analyzes and compares the two methods of the one-dimensional linear regression model and the multiple linear regression model. The study is conducted under the three indicators of biosafety management weight score. Arithmetic means to score and significance of 100 enterprises (schools, pharmaceutical companies, hospitals, and other types of these four major types) under the multiple linear regression model. The results show schools topped the list with a biosafety management weight score of 0.793. The arithmetic mean scores of the four categories of enterprises were ranked in descending order: schools, hospitals, pharmaceutical plants, and other categories. The size of the enterprise has a significant and positive effect on biosafety management, which means that the larger the size of the enterprise, the more resources the enterprise has under its control, and then the implementation of biosafety management and the improvement of its performance will be guaranteed. Analyzing the efficiency of biosafety management in hospitals based on three different methods over the past 20 years, it was found that the efficiency of biosafety management based on multiple linear regression models fluctuated from 60% to 95% compared to the other two methods. This study promotes university laboratories as important and safe bases for society to cultivate highly qualified and skilled personnel in line with the new era of production, management, and service lines and to contribute to the country’s experimental research work. This study has substantial reference value for biosafety management and promotes bioscience development in China.</p>
</abstract>

With the rise of artificial intelligence technology in the context of digital development of big data and information, the biosafety management method under the traditional model can hardly fit the development requirements of the times, and the biosafety management under the traditional model has various problems such as slow manual efficiency, tedious management work, and humanization of work. This paper focuses on studying a biosafety management strategy based on a multiple regression model, then analyzes and compares the two methods of the one-dimensional linear regression model and the multiple linear regression model. The study is conducted under the three indicators of biosafety management weight score. Arithmetic means to score and significance of 100 enterprises (schools, pharmaceutical companies, hospitals, and other types of these four major types) under the multiple linear regression model. The results show schools topped the list with a biosafety management weight score of 0.793. The arithmetic mean scores of the four categories of enterprises were ranked in descending order: schools, hospitals, pharmaceutical plants, and other categories. The size of the enterprise has a significant and positive effect on biosafety management, which means that the larger the size of the enterprise, the more resources the enterprise has under its control, and then the implementation of biosafety management and the improvement of its performance will be guaranteed. Analyzing the efficiency of biosafety management in hospitals based on three different methods over the past 20 years, it was found that the efficiency of biosafety management based on multiple linear regression models fluctuated from 60% to 95% compared to the other two methods. This study promotes university laboratories as important and safe bases for society to cultivate highly qualified and skilled personnel in line with the new era of production, management, and service lines and to contribute to the country’s experimental research work. This study has substantial reference value for biosafety management and promotes bioscience development in China.

Biosafety management strategy based on multiple linear regression model

Center for Biosafety Research and Strategy, Tianjin University

Applied Mathematics and Nonlinear Sciences

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

{"article-title":"Biosafety management strategy based on multiple linear regression model"}

With the rise of artificial intelligence technology in the context of digital development of big data and information, the biosafety management method under...

Biosafety management strategy based on multiple linear regression model

Online veröffentlicht: 06. Juni 2023

Seitenbereich: -

Eingereicht: 22. Juni 2022

Akzeptiert: 09. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00362

Schlüsselwörter
Big data, Univariate linear regression, Multiple linear regression, Biosecurity, Management Strategy

© 2023 Chao Zhao et al., published by Sciendo

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

Biosafety management strategy based on multiple linear regression model

Online veröffentlicht: 06. Juni 2023

Seitenbereich: -

Eingereicht: 22. Juni 2022

Akzeptiert: 09. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00362

SchlüsselwörterBig data, Univariate linear regression, Multiple linear regression, Biosecurity, Management Strategy

© 2023 Chao Zhao et al., published by Sciendo

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

Schlüsselwörter
Big data, Univariate linear regression, Multiple linear regression, Biosecurity, Management Strategy