检索结果-内蒙古大学图书馆

Research and application of optimization of physical education training model based on multi-objective differential evolutionary algorithm

引用

SYSTEMS AND SOFT COMPUTING 2025年 7卷

作者： Wu, Man Wenzhou Polytech Wenzhou 325035 Peoples R China

With the development of computer science, various algorithm models are gradually applied in various fields of life. In order to study the application of the multi-objective differential evolution algorithm in the field of sports transportation. Based on the improvement of multi-objective differential evolution algorithm, this paper proposes the training model of PE education, and compares the prediction results and the actual results. The specific conclusions are as follows: (1) MODE algorithm is better to other algorithms in convergence speed and accuracy;MODE algorithm can not only reach the optimal particle position quickly, but also fluctuate around the best point.(2) AMODE-MPS has great potential for dealing with complex and multiple objectives.(3) There are significant differences between the prediction performance of the proposed algorithm model and the statistical performance, in which the statistical performance is significantly higher than the predicted performance.(4) The proposed model can basically meet the prediction requirements. Although there are some differences between the prediction results and the actual results, this is because the statistical process is affected by the weather, physical condition and other factors. The results show that the PE training model has good results in practice, so this paper can provide reference for the improvement of PE teaching model.

关键词： multi-objective differential evolutionary algorithm Random forest algorithm Mirror point screening method Physical education

来源：评论

学校读者我要写书评

暂无评论

Fitness partition-based multi-objective differential evolutionary algorithm and its application to the sodium gluconate fermentation process

引用

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2018年 177卷 8-16页

作者： Guo, Zhan Yan, Xuefeng East China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai 200237 Peoples R China

The operating conditions of the fermentation process of sodium gluconate play a key role in the quality and quantity of its production. The fermentation process is highly nonlinear and dynamic, and several objects must be considered. To implement a global and efficient optimization for the fermentation process, a fitness partition-based multi-objective differential evolutionary algorithm (FPMDE) is proposed. In the FPMDE algorithm, the information in the target space, which expresses some superiority message, is used to guide the evolutionary process. Namely, according to the fitness values, the target space is divided into some sub-region, and then some optimal directions are extracted for individuals to search for the optimal region and finally approximate the Pareto front. Experimental results on 20 benchmark functions show its advantage in convergence and diversity compared with 5 other state-of-art algorithms. Further, three objective functions for the fermentation process of sodium gluconate are proposed, and the FPMDE algorithm is applied to obtain its Pareto front;the conversion rates and utilization rate of equipment has been improved. It is shown that the FPMDE can optimize the conditions of the production of sodium gluconate effectively and efficiently.

关键词： multi-objective differential evolutionary algorithm Fitness partition Self-adaptive mutation strategy Fermentation process Sodium gluconate

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：