检索结果-内蒙古大学图书馆

JOURNAL OF APPLIED SCIENCE AND ENGINEERING 2025年第2期28卷 381-390页

作者： Xu, Guimin Yang, Zhengxiang Hubei Univ Educ Sch Phys & Mech & Elect Engn Wuhan 430205 Peoples R China Wuhan Tech Coll Commun Sch Intelligent Mfg Wuhan 430065 Peoples R China

Today's power systems for various reasons, including linearization of equations of state estimation and improved speed control and protection systems, use Wide Area Measurement (WAMS). Due to their high cost, it is essential to optimize the number and placement of this equipment. The costs associated with deploying a Synchro phasor have evolved throughout time. The cost of upgrading a substation, which is far more than the cost of a single device, has emerged as the major expense component. When determining where to put phasor measuring units (PMUs), it's important to consider not only how many will need to be built at each substation but also how many will need to undergo upgrades to accommodate them. In this paper, the multi-functional locating of phasor measurement units has been done with goals such as the cost of investment and risk in power systems (reliability) by indicating the observability. Then the location of the phasor units was solved in the form of an optimization problem, using multi-objective optimization algorithm nsga-ii. In the end, the performance of the proposed method is examined on the 9-bus system.

关键词： Observability of Power Systems Optimal PMU Allocation Power System Reliability Risk Cost nsga-ii algorithm

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Optimization of Construction Project Management Based on nsga-ii algorithm Improvement

引用

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2025年第1期16卷 432-444页

作者： Yang, Yong Men, Jinrui Shandong Huayu Univ Technol Sch Energy & Bldg Engn Dezhou 253000 Peoples R China

the building industry, one of the key components to ensuring a project's successful completion is multi-objective project management. However, due to its own limitations, the traditional multi-objective management approach for projects is no longer able to meet the requirements of building construction and urgently needs to be improved. This is because the construction industry is becoming more competitive and construction standards are improving. Traditional methods for multi-objective optimization typically involve simply summing multiple objectives with weights, overlooking the interdependencies among these objectives. These methods often get trapped in local optimal solutions and rely heavily on predefined models and parameters, limiting their adaptability to sudden changes during the construction process. Therefore, a multi-objective management approach based on multi-objective genetic algorithm for construction projects is proposed. It enables in-depth analysis and comprehensive optimization of the complex relationships between objectives, leading to more informed decisions. By facilitating rapid iteration and adaptation, it enables timely adjustments and optimizations to ensure that project goals remain consistent in complex and dynamic environments. In the experimental validation, the nsga-ii algorithm achieved a significant accuracy of 0.642 and success rate of 0.504 on the VOT dataset, both of which improved by about 1.0% and 0.6% compared to the comparison algorithm. Experimental results on the TrackingNet dataset revealed that the algorithm achieved an accuracy of 0.791 and a success rate of 0.763, while it still maintained an accuracy of 0.542 and a success rate of 0.763 in the face of occlusion. The enhanced multi-objective genetic algorithm had higher accuracy and success rates. This demonstrates the efficiency and excellence of the multi-objective management optimization approach suggested in this study for building projects. The research results hav

关键词： nsga-ii algorithm improvement strategy construction engineering project management multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimization of railway construction under carbon trading mechanism based on improved nsga-ii algorithm

ENGINEERING RESEARCH EXPRESS

引用

ENGINEERING RESEARCH EXPRESS 2025年第2期7卷

作者： Xu, Xizhen Liu, Yuming Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China

Railway engineering projects exhibit complex internal structures and extensive external interconnections, making it difficult to establish definitive control objectives for duration and cost during construction. With the increasing severity of environmental pollution and energy consumption, carbon emissions have gradually become a critical factor that cannot be ignored in the construction process. This study proposes a multi-objective optimization method for construction based on cost-duration-carbon emissions under the carbon trading mechanism, employing an improved nsga-ii algorithm to solve the multi-objective optimization model and deriving the optimal construction solution based on projection characteristic values. An empirical study of a railway engineering project demonstrates the following results: (1) Compared to the baseline solution, the optimized construction solution achieves reductions of 1.87 million yuan in cost, 3 days in duration, and 137 tons in carbon emissions, with all optimization results being statistically significant;(2) Quantitative analysis using spacing metrics and one-sample t-tests confirms that the improved nsga-ii algorithm exhibits high solution stability and solution set uniformity in solving construction multi-objective optimization problems, along with good scalability;(3) The optimal projection vector [Duration, Cost, Carbon Emission] = [0.0120, 0.9821, 0.9958] indicates that carbon emissions are the most critical factor influencing the selection of the optimal construction solution. This study provides theoretical foundations and technical support for multi-objective optimization in railway engineering construction, offering significant value for promoting green and sustainable development in the industry.

关键词： engineering construction multi-objective optimization carbon trading mechanism nsga-ii algorithm

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimal tolerance allocation design of machine tool based on nsga-ii algorithm and thermal characteristic analysis

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2025年

作者： Niu, Peng Cheng, Qiang Liu, Zhifeng Chen, Chuanhai Zhao, Yongsheng Li, Ying Qi, Baobao Beijing Univ Technol Inst Adv Mfg & Intelligent Technol 100 Pingleyuan Beijing 100124 Peoples R China Jilin Univ Jilin Prov Key Lab Adv Mfg & Intelligent Technol H Changchun Jilin Peoples R China

Tolerance allocation optimization (TAO) is a crucial step in the manufacturing process of the portal milling machine (PMM). Traditional design approaches often consider only the machining errors arising from geometric errors. However, the thermal characteristics of the bi-rotary milling head (BRMH), which significantly machine tool accuracy, are frequently overlooked. Hence, a novel TAO model of PMM is proposed, considering the thermal characteristics of BRMH across multiple operating conditions. Firstly, based on the multi-body system (MBS) theory and homogeneous transform matrix (HTM), a mapping function relating geometric errors to tolerance and volume errors is developed. Secondly, the heat generation and dissipation mechanisms of the BRMH are analyzed, and precise boundary conditions for thermal simulations are determined. Notably, the spin friction torque of the rolling body on the bearing, which contributes to heat generation, must be considered. Finally, the established accuracy design optimization model, which balances total cost and machining accuracy, is solved using the nsga-ii algorithm. The Pareto optimal solution set reveals an 11.74% reduction in total cost and improved machining accuracy for the PMM. Besides, the proposed framework for accuracy design optimization with thermal characteristics is applicable to the manufacturing processes of other machine tools.

关键词： Portal milling machine tolerance allocation optimization bi-rotary milling head thermal characteristics analysis nsga-ii algorithm

来源：评论

学校读者我要写书评

暂无评论

nsga-ii algorithm in Path Planning of Multiple Unmanned Aerial Vehicle Collaborative Search Tasks 24

NSGA-II Algorithm in Path Planning of Multiple Unmanned Aeri...

引用

International Conference on Machine Intelligence and Digital Applications (MIDA)

作者： Huang, Xin Tianjin Vocat Inst Sch Elect Mech Engn & Automat Tianjin 300410 Peoples R China

ISBN: (纸本)9798400718144

In response to the problem of single objective optimization in collaborative search path planning for multiple unmanned aerial vehicles, this paper aims to use the nsga-ii (Non-dominated Sorting Genetic algorithm ii) algorithm for optimization. The first step of this article is to conduct multi-objective optimization modeling on the path planning problem, clarifying that the optimization objectives include search area coverage and flight time. To find the best path planning solution, the nsga-ii algorithm is used in the second stage to enhancing the dynamic environment's adaptability and the drone's flexibility and search efficiency in complex surroundings constitute the third step. Finally, by comparing the performance indicators with traditional algorithms, it was found that the algorithm used in this paper performs well in terms of search area coverage, with the highest average coverage, up to 87%. At the same time, it requires the least flight time to perform search tasks. In summary, the multi-objective optimization method based on nsga-ii algorithm proposed in this article has shown significant performance advantages in multi-UAV (Unmanned Aerial Vehicle) collaborative search path planning.

关键词： Multiple Drones in a Coordinated Search Path Planning nsga-ii algorithm Problem Modeling Objective Function

来源：评论

学校读者我要写书评

暂无评论

Reverse reconstruction of motorcycle-car accident based on response surface model and nsga-ii algorithm

引用

INTERNATIONAL JOURNAL OF CRASHWORTHINESS 2022年第1期27卷 107-116页

作者： Wang, Qian Lou, Yunfeng Li, Tong Jin, Xianlong Kong, Lingshuang Hou, Xinyi Shanghai Jiao Tong Univ State Key Lab Mech Syst & Vibrat Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China Aerosp Syst Engn Shanghai Shanghai Peoples R China Shanghai Municipal Bur Publ Secur Shanghai Peoples R China

In order to obtain the initial condition of the traffic accident and reconstruct the collision process of motorcycle and car in reverse, this paper proposes a multi-objective optimisation algorithm based on the combination of nsga-ii and surrogate model. Aiming at a collision accident between a car and motorcycle, a simulation model of the human-vehicle-road coupling system is established. First, select the optimisation variables, optimisation objectives and constraints, define the variable range, and through the Opt-LHD to sample the optimisation variables. Then, obtain and fit the sample data, and take the sample data as the initial conditions into the established motorcycle traffic accident simulation model. Next, obtain the simulation data of the optimisation variables, and establish the response surface model of the optimisation objectives in MATLAB. Finally, using nsga-ii algorithm, the individuals in the population are solved based on the response surface model in turn, the Pareto solution set is obtained, and a group of satisfactory solutions is taken back to the simulation model for verification of the optimisation model, so as to prove the correctness of the satisfactory solution, and then the initial conditions of the collision between the motorcycle and the car are obtained.

关键词： Motorcycle traffic accident reverse reconstruction initial collision conditions response surface model nsga-ii algorithm

来源：评论

学校读者我要写书评

暂无评论

Structural Design and Optimization of the Crossbeam of a Computer Numerical Controlled Milling-Machine Tool Using Sensitivity Theory and nsga-ii algorithm

引用

INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING 2021年第2期22卷 287-300页

作者： Li, Xueguang Li, Chongqing Li, Penghui Hu, Huizhong Sui, Xiansheng Changchun Univ Sci & Technol Sch Mech & Elect Engn 7089 Weixing Rd Changchun 130022 Jilin Peoples R China

The crossbeam plays a vital role in computer numerical controlled milling machines, especially in machines with a gantry structure, as it directly influences the machining precision. In this study, a machine tool crossbeam was designed, and the modal frequency of the crossbeam was analyzed using the finite element model (FEM) analysis. In the improved structure obtained through FEM analysis, the X-type structure of the internal unit of the crossbeam was replaced by an O-type structure. The specific structure dimensions were further optimized using a neural-network algorithm and a nondominated sorting genetic algorithm. Finally, we calculated the effect of each crossbeam dimension on the mass, deformation, and frequency in a sensitivity analysis. After optimizing the crossbeam dimensions with respect to deformation, modal frequency, and mass, the structural characteristics of the original and optimized crossbeams were compared. After optimization, the mass and deformation were reduced by 7.45% and 3.08%, respectively, and the modal frequency was increased by 0.42%. These results confirm that the optimization improved the performance of the crossbeam structure.

关键词： Finite element models Sensitivity theory Neural network Structure optimization nsga-ii algorithm

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimisation of high-speed rail profile with small radius curve based on nsga-ii algorithm

引用

VEHICLE SYSTEM DYNAMICS 2023年第12期61卷 3111-3135页

作者： Li, Guofang Li, Xing Li, Meng Na, Tong Wu, Shaopei Ding, Wangcai Lanzhou Jiaotong Univ Sch Mechatron Engn Lanzhou Peoples R China Southwest Jiaotong Univ State Key Lab Tract Power Chengdu Peoples R China

The multi-objective optimisation of high-speed rail profile with small radius curve is studied in the paper. A multi-objective mathematical model for rail profile optimisation of high-speed railway is established. The CN60 rail profile is parameterised into a series of generalised functions of design variables. In order to guarantee the smoothness of the rail profile and meet the maximum grinding depth of rail in China, the constraints are employed. The wheel-rail vertical clearance and equivalent conicity of wheelset are taken as objective functions, and a rail wear prediction programme is compiled. Contact line method is employed to complete the detection algorithm of wheel-rail contact points. Finally, nsga-ii algorithm is adopted to solve the Pareto-optimal front of the optimisation model. A set of solutions are retrieved from the Pareto optimal front solution as the optimised profile. The optimised rail profile and the original rail profile are matched with the LMA wheel profile (a certain worn type of wheel profiles for EMU in China) respectively. It is testified that the rail profile could effectively reduce the rail wear and improve curving performance. The new method proposed in this paper can provide some reference for the optimisation design of high-speed rail profile with small radius curve.

关键词： Rail wear whee-rail contact geometry wheel-rail vertical clearance optimisation of rail profile with small radius curve nsga-ii algorithm

来源：评论

学校读者我要写书评

暂无评论

An optimal preventive maintenance strategy for the hydraulic system of platform firefighting vehicle based on the improved nsga-ii algorithm

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY 2019年第6期233卷 978-989页

作者： Teng, Rumin Liang, Jifei Wu, Guanglei Wang, Dianlong Wang, Xin Dalian Univ Technol Sch Mech Engn Dalian 116024 Peoples R China

Based on the reliability analysis, this work presents a model of the preventive maintenance for the hydraulic system of platform firefighting vehicle, considering the working age regression factor and the equivalent service life. In this model, both the equipment availability and average maintenance cost are treated as the objective functions and constrained by the equipment reliability as well as the total working time. The non-dominated sorting genetic algorithm ii (nsga-ii) algorithm is adopted to solve the previous optimization problem, wherein the constrained inequality functions in the stages of initialization, mutation, and crossover are introduced to assess the solution to meet the constraints or not, through the improvements in three aspects, namely, the improvement of the algorithm's initialization to ensure the initial variables meet the equality constraint, the utilization of the mean division of the difference values to adjust the variables after the selection, and crossover and mutation of the gene. Numerical analysis is carried out to verify the feasibility of the improved algorithm, wherefrom the Pareto-optimal solutions for the preventive maintenance of the platform firefighting vehicle are obtained to provide the optimum strategy for the service engineers with different weighted factors.

关键词： Platform firefighting vehicle hydraulic system preventive maintenance nsga-ii algorithm reliability analysis

来源：评论

学校读者我要写书评

暂无评论

Multiobjective optimization-based DV-hop localization using nsga-ii algorithm for wireless sensor networks

引用

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2020年第11期33卷 e4431-e4431页

作者： Kanwar, Vivek Kumar, Ashok Natl Inst Technol Dept Elect & Commun Engn Hamirpur Himachal Prades India

Localization is one of the important requirements in wireless sensor networks for tracking and analyzing the sensor nodes. It helps in identifying the geographical area where an event occurred. The event information without its position information has no meaning. In range-free localization techniques, DV-hop is one of the main algorithm which estimates the position of nodes using distance vector algorithm. In this paper, a multiobjective DV-hop localization based Non-Sorting Genetic algorithm-ii (nsga-ii) is proposed in WSNs. Here, we consider six different single-objective functions to make three multiobjective functions as the combination of two each. Localization techniques based on proposed multiobjective functions has been evaluated on the basis of average localization error and localization error variance. Simulation results demonstrate that the localization scheme based on proposed multiobjective functions can achieve good accuracy and efficiency as compared to state-of-the-art single- and multiobjective GA DV-hop localization scheme.

关键词： DV-hop localization multiobjective nsga-ii algorithm range-free wireless sensor network

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：