检索结果-内蒙古大学图书馆

ENGINEERING RESEARCH EXPRESS 2025年第1期7卷

作者： Zhang, Jia Tianjin Sino German Univ Appl Sci Fundamental Expt Training Ctr Tianjin 300350 Peoples R China

The structure of automotive electrical equipment is becoming increasingly complex. How to optimize the structure without affecting the performance of the car itself to reduce the weight and manufacturing cost of electrical equipment has become particularly important. Based on this, this study introduces diversity preservation mechanism and adaptive mutation strategy to improve the multi-population genetic algorithm, and proposes the objective function and constraint conditions for the results of automotive electrical equipment, constructing an optimization model for the structure of automotive electrical equipment. The results showed that at 500 iterations, the improved multi-population genetic algorithm had optimal and average fitness values of 0.96 and 0.94, respectively, demonstrating higher accuracy and search capability compared to other algorithms. After using optimization models for different automotive electrical equipment structures, the average energy consumption decreased by 18%, the total cost decreased by 16.55%, and the average total weight of electrical equipment structures decreased by 16.475%. This model is effective in optimizing the structure of electrical equipment. This study contributes to improving the performance and design efficiency of automotive electrical equipment, and has significant implications for promoting the application of intelligent optimization technology in the automotive industry.

关键词： improved multi-population genetic algorithm automotive electrical equipment structural optimization global search capability adaptive mutation strategy

来源：评论

学校读者我要写书评

暂无评论

An improved multi-population genetic algorithm with a greedy job insertion inter-factory neighborhood structure for distributed heterogeneous hybrid flow shop scheduling problem

引用

EXPERT SYSTEMS WITH APPLICATIONS 2023年第1期222卷

作者： Cui, Hanghao Li, Xinyu Gao, Liang Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430070 Peoples R China

Distributed heterogeneous hybrid flow shop scheduling problem (DHHFSP) is an extension of the classical hybrid flow shop scheduling problem (HFSP), which is an NP-hard problem. In the context of economic globalization, DHHFSP considers the collaboration and heterogeneity among multiple factories. The neighborhood structure plays an important role in continuously improving the current individuals for DHHFSP. The existing work has fully studied the inner-factory neighborhood structure, but the research on the inter-factory neighborhood structure is still immature. A greedy job insertion inter-factory neighborhood structure and a new move eval-uation method are designed to ensure the efficiency of neighborhood movement. And an improved multi-population genetic algorithm (IMPGA) is proposed to solve the DHHFSP with makespan. To enhance the convergence speed and robustness of the IMPGA, a guided sub-populations information interaction and a re-initialization procedure with an individual resurrection strategy are designed respectively. In computational experiments, there are 480 instances (including the same proportion of small, medium, and large-scale problems) randomly generated. The proposed IMPGA obtains the best solutions for 457 instances. The analysis of experi-mental results shows that IMPGA significantly outperforms the reported state-of-the-art algorithms for DHHFSP. Finally, the proposed method is used to solve a polyester film manufacturing company case effectively.

关键词： Distributed heterogeneous hybrid flow shop improved multi-population genetic algorithm Inter-factory neighborhood structure Movement evaluation method Guided subpopulations information interaction

来源：评论

学校读者我要写书评

暂无评论

Atmospheric environmental changes and a multi-objective optimization model for energy conservation and environmental protection based on improved multi-population genetic algorithm

引用

ARABIAN JOURNAL OF GEOSCIENCES 2021年第10期14卷 1-17页

作者： Shi, Jianguo China Univ Min & Technol Sch Management Xuzhou 221116 Jiangsu Peoples R China

With the development of computer technology and theory, cloud computing technology suitable for modern computing and large-capacity storage has emerged. Cloud computing technology depends on the Internet. The advancement and development of virtualization technologies such as cloud computing technology is the most cited of current computer technologies. With the development of cloud computing technology, this paper proposes a multi-group genetic algorithm based on interactive multi-functional processing methods, which can achieve the expectation of reducing the energy consumption of the cloud computing center to the greatest extent and at the same time ensure the stability and the running state of the server effectiveness. Through this survey, while reducing the company's operating costs, it will also contribute to energy conservation and environmental protection. multi-group genetic algorithms can effectively overcome the shortcomings of standard genetic algorithms, such as optimization range and efficiency, number of iterations, and premature end of iteration. The optimized result can reflect the subjective will of the decision-maker. Experimental examples show the efficiency of the algorithm, and the results show the applicability and feasibility of the algorithm. Based on the changes in the global atmospheric environment in recent years, this article discusses the reasons for the changes and focuses on the impact of human activities. In addition, the environmental issues that have received much attention today are the clues to discuss the climate issues and the harmful effects brought about by changes in the atmospheric environment, which has aroused people's attention to energy conservation and environmental protection.

关键词： Changes in atmospheric environment improved multi-population genetic algorithm Energy saving and environmental protection multi-objective optimization model

来源：评论

学校读者我要写书评

暂无评论

multi-population genetic algorithm with greedy job insertion inter-factory neighbourhoods for multi-objective distributed hybrid flow-shop scheduling with unrelated-parallel machines considering tardiness

引用

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2024年第12期62卷 4427-4445页

作者： Cui, Hanghao Li, Xinyu Gao, Liang Zhang, Chunjiang Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430070 Peoples R China

Distributed manufacturing is gradually becoming the future trend. The fierce market competition makes manufacturing companies focus on productivity and product delivery. The hybrid flow shop scheduling problem (HFSP) is common in manufacturing. Considering the difference of machines at the same stage, the multi-objective distributed hybrid flow shop scheduling problem with unrelated parallel machines (MODHFSP-UPM) is studied with minimum makespan and total tardiness. An improved multi-population genetic algorithm (IMPGA) is proposed for MODHFSP-UPM. The neighbourhood structure is essential for meta-heuristic-based solving algorithms. The greedy job insertion inter-factory neighbourhoods and corresponding move evaluation method are designed to ensure the efficiency of local search. To enhance the optimisation ability and stability of IMPGA, sub-regional coevolution among multiple populations and re-initialisation procedure based on probability sampling are designed, respectively. In computational experiments, 120 instances (including the same proportion of medium and large-scale problems) are randomly generated. The IMPGA performs best in all indicators (spread, generational distance, and inverted generational distance), significantly outperforming existing efficient algorithms for MODHFSP-UPM. Finally, the proposed method effectively solves a polyester film manufacturing case, reducing the makespan and total tardiness by 40% and 60%, respectively.

关键词： Distributed hybrid flow shop with unrelated parallel machines multi-objective scheduling considering total tardiness improved multi-population genetic algorithm Greedy job insertion inter-factory neighbourhoods Rapid evaluation method for inter-factory neighbourhoods Sub-regional coevolution among multiple populations

来源：评论

学校读者我要写书评

暂无评论

P300-based deception detection of mock network fraud with modified genetic algorithm and combined classification 7

P300-based deception detection of mock network fraud with mo...

引用

7th International Winter Conference on Brain-Computer Interface (BCI)

作者： Liu, Xiaochen Shen, Jizhong Zhao, Wufeng Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781538681169

To detect network fraud, a three-stimulus paradigm was used in a mock crime P300-based concealed information test. A P300-based deception detection method based on a modified genetic algorithm and a confidence-coefficient-based combined classifier was created for mock network fraud detection. After the multi-domain integrated signal preprocessing and feature extraction, a modified logistic equation based multi-population genetic algorithm was adopted for feature selection to obtain an optimal feature subset. Then the confidence coefficient was proposed to determine the classification difficulty levels of samples. A combined classifier based on confidence coefficient was proposed for classification. Compared with the component classifiers and other individual classifiers, the combined classifier requires 34% less computing time and the mean classification accuracy rate is 0.2 to 2.23 percentage points higher for twelve subjects using leave-one-out cross validation. Experiment results confirm that the proposed method is effective to detect deception during network fraud simulation.

关键词： mock crime network fraud P300 improved multi-population genetic algorithm confidence coefficient combined classifier

来源：评论

学校读者我要写书评

暂无评论

Load Transfer Device for Solving a Three-Phase Unbalance Problem Under a Low-Voltage Distribution Network

引用

ENERGIES 2019年第15期12卷 2842页

作者： Bao, Guanghai Ke, Sikai Fuzhou Univ Coll Elect Engn Fuzhou 350001 Fujian Peoples R China Fujian Key Lab New Energy Generat & Power Convers Fuzhou 350108 Fujian Peoples R China

In the low-voltage (LV) distribution network, a three-phase unbalance problem often exists. It does not only increase line loss but also threaten the safety of the distribution network. Therefore, the author designs a residential load transfer device for a LV distribution network that can deal with a three-phase unbalance problem by changing the connecting phase of the load. It consists of three parts: user controller for phase swapping, central controller for signal processing and monitoring platform for strategy calculation. This design was based on message queuing telemetry transport (MQTT) communication protocol, and Long Range and 4th Generation mobile telecommunications (LoRa + 4G) communication mode is used to realize the wireless connection between equipment and monitoring platform, and a control scheme is proposed. The improved multi-population genetic algorithm (IMPGA) with multi-objective is used to find the optimal swapping strategy, which is implemented on the monitoring platform. Then the phase swapping is realized by remote control, and the function of reducing three-phase unbalance is realized. The practical experimental result shows that the method can help to reduce the three-phase unbalance rate by changing the connection phase of the load, and the simulation results verify the effectiveness of the algorithm in the phase-swapping strategy.

关键词： three-phase unbalance residential load transfer device improved multi-population genetic algorithm LoRa+4G MQTT

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：