检索结果-内蒙古大学图书馆

IEEE Aerospace Conference

作者： Alaa El-Din Sayed Hafez Mohamed Abd El-latif Alexandria University 21D Toson City Alexandria Egpyt Alexandria University 5H Toson City Alexandria Egpyt

ISBN: (纸本)9781457705564

In this paper, new optimized multilevel biphase pulse compression codes (MBPCC) with low peak side lobe (PSL) and mean side lobes (MSL) have been investigated. Amplitude and phase coding have been used during the optimization process. In previous studies, biphase codes were optimized using genetic algorithm (GA). The robustness of genetic algorithm in solving optimization problems degrades simultaneously as the code length increases. particle swarm optimization (PSO) algorithm has been used with MBPCC to solve this problem. PSO algorithm has the merits of rapid convergence to the global optimum. Complete description of PSO implementation process has been clarified. swarm intelligence boasts a number of advantages due to the use of mobile agents. Set of novel codes with optimum PSL ranging between -27.06 dB and -38.26 dB for codes of length 5 up to 45 has been introduced. Optimization results obtained using both PSO and GA has been compared. Comparative study shows both the optimality and superiority of PSO algorithm over GA for different code lengths. MBPCC have a precision of 10~(3) (-30) dB, which can be feasibly implemented using digital attenuators at element level with optimum performance and hardware implementation facility.

关键词： particle swarm algorithm parametric subharmonic oscillator code length Codes Gallium Optimization Procedure particle swarm optimization phase coding Radar pulses Genetic algorithm (GA) Mobile agents optimum performance biphase optimality Amplitude

来源：评论

学校读者我要写书评

暂无评论

Enhanced adaptive particle swarm optimisation algorithm for dynamic economic dispatch of units considering valve-point effects and ramp rates

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2012年第5期6卷 424-435页

作者： Niknam, T. Golestaneh, F. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

In power systems, dynamic economic dispatch (DED) is one of the most significant non-linear problems showing non-convex characteristic because of the valve-point effects. In this study, an enhanced adaptive particle swarm optimisation (EAPSO) algorithm is proposed to solve the DED problem where the valve-point effects, ramp-rate limits and transmission power losses are taken into account. In the proposed optimisation algorithm, a mutation technique is devised to prevent premature phenomena and lead the swarm search space much more effectively;also a novel non-linear approach is designed to adjust the inertia weight factor dynamically according to the optimisation process performance. Social and cognitive factors are self-adaptively tuned, so the swarm can search the space smartly for global optimum solution. The efficiency of the proposed method is validated on three popular test systems in the area including 5, 10 and 30 thermal units. The results are compared with most of the other works in the area. The superiority of the method is shown over earlier methods.

关键词： Test systems HEAT RATE valve effect Work area particle swarm optimization Optimization algorithms Dispatching dike swarms particle swarm algorithm Self tuning

来源：评论

学校读者我要写书评

暂无评论

Research on Grid-connected Strategy of Distributed Generation Dominated by On-grid Electricity Price (July 2018)

Research on Grid-connected Strategy of Distributed Generatio...

引用

China International Conference on Electricity Distribution (CICED)

作者： Lan Chunhu Fan Wei Wang Nan Yang He Gao Yi Ge Leijiao State Grid Tianjin Elect Power Co Econ Res Inst Tianjin 300171 Peoples R China State Grid Tianjin Elect Power Co Elect Power Res Inst Tianjin 300384 Peoples R China Tianjin Univ Sch Elect Informat & Engn Tianjin Peoples R China

ISBN: (纸本)9781538667750

The access of high permeability and large-scale distributed generation makes the operating environment of distribution network extremely badly. To solve the problem of safe and reliable access to distribution networks with large-scale distributed energy sources, based on the on-grid price, this paper deduces the demand information of power distribution network by analyzing and comparing it;establishes the Markov decision process model, defines the reward and punishment mechanism of different behaviors;introduces particle swarm optimization algorithm to optimize the power flow calculation process and improve convergence rate;proposes the control strategy of distributed energy access to the distribution network, and maximizes the economic benefits of distributed energy under the premise of ensuring the highest priority of power quality, and provide more effective means to solve the problem of active distribution network dissipating distributed energy.

关键词： distributed generation on-grid electricity price power quality Markov decision process particle swarm algorithm maximum economic benefit

来源：评论

学校读者我要写书评

暂无评论

An investigation of Advanced Permanent-Magnet Brushless Motor Using FOPID Controller 33

An investigation of Advanced Permanent-Magnet Brushless Moto...

引用

33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Shen, Shuyu Chu, Hongyan Shao, Yingshu Ning, Jieyu Nanjing Normal Univ Sch Elect & Automat Engn Nanjing Jiangsu Peoples R China Nanjing Normal Univ Sch Energy & Mech Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538672556

The permanent-magnet Brushless DC motor(BLDC) is widely used in aerospace, military, automotive and household equipment industries for its advantages of high efficiency, low noise, long lifetime and good torque-speed characteristics. In this paper, fractional order PID(FOPID) controller is applied to control the BLDC for the convenience to implement and high performance compared to traditional PID controllers. Firstly, the precise mathematical model is built and then the stability analysis is made based on the mathematical model. Secondly, we design the FOPID controller and tune its five parameters by adopting particle swarm optimization algorithm. Finally, oustaloup filtering method helps the controller realizing in the single-loop speed control system. Simulation results and comparison with traditional PID controller show the effectiveness and feasibility of our method.

关键词： fractional order particle swarm algorithm oustaloup filtering

来源：评论

学校读者我要写书评

暂无评论

Research on Vulnerability Classification Method Based on DMO-PSO-SVM algorithm 3

Research on Vulnerability Classification Method Based on DMO...

引用

3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Yang, Huiting Guo, Wenbin Zou, Zhenwan Bai, Yunxiao Wang, Xu Li, Yutao State Grid Xinjiang Elect Power Res Inst Urumqi Peoples R China State Grid Altay Elect Power Supply Co Altay Peoples R China

ISBN: (纸本)9781538645093

Network vulnerabilities are very important for network security. How to standardize and reasonably classify vulnerabilities is the basic work of current network security related research. At present, various types of vulnerability classification algorithms often require long training time and test time, and are easy to fall into local optimum. Therefore, this paper proposes a new DMO-PSO-SVM algorithm for the classification of vulnerabilities. This algorithm introduces an improved particle swarm algorithm to optimize its parameters based on Support Vector Machine. The use of dual mutation operators avoids the occurrence of local optimal conditions, including edge mutation operator and global mutation operator. Experiments show that the method proposed in this paper significantly improves the accuracy of classification of vulnerabilities and reduces the classification time.

关键词： network vulnerabilities particle swarm algorithm support vector machine edge mutation operator global mutation operator

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Energy Management for Community Microgrids

Comparative Analysis of Energy Management for Community Micr...

引用

IEEE International Conference on Power and Energy Systems (ICPES)

作者： Md Alamgir Hossain Md Rasel Mahmud Hemanshu Roy Pota School of Engineering & Information Technology The University of New South Wales (UNSW) Canberra ACT Australia

ISBN: (数字)9781728126586

ISBN: (纸本)9781728126593

The energy management of a microgrid becomes complex due to a number of reasons, including intermittent power generation, unpredictable load demand and variable real-time electricity prices. In this paper, different energy management schemes, such as real-time and scheduling, are analysed under uncertain environments to demonstrate their effectiveness in managing a microgrid's energy. Optimisation problems are first formulated, then separate solution methods using particle swarm optimisation algorithms are applied to efficiently manage the microgrid's energy. It is observed that the scheduling program in all the case studies can reduce the operational costs significantly.

关键词： Community microgrids renewable energy optimum battery control energy management particle swarm optimisation Energy management particle swarm optimization Renewable energy scheduler program MICRO-GRID Manufacturing costs particle swarm algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimisation of total traction current based on niche improved particle swarm algorithms

引用

IET ELECTRICAL SYSTEMS IN TRANSPORTATION 2016年第4期6卷 253-260页

作者： Li Guoxin Du Guifu Wang Chonglin China Univ Min & Technol Sch Informat & Elect Engn Xuzhou Peoples R China

Due to the short distance between stations in DC mass transit systems, the trains accelerate and decelerate frequently with high traction current. If numerous trains are accelerating simultaneously, an extremely high traction current peak occurs. This current will have a great impact on the power supply system, and cause elevated rail potential in reflow system. This study presents an optimal model on traction current by adjusting the train's dwell time, reducing the coincidence degree when multi-train accelerate. Niche improved particle swarm algorithms for traction current optimisation is constructed. Optimised calculation results from the simulation of actual line show that the optimisation can significantly reduce the total maximum traction current value.

关键词： Power supply systems TRAIN acceleration current draw short-distance niches particle swarm algorithm

来源：评论

学校读者我要写书评

暂无评论

Hierarchical genetic-particle swarm optimization for bistable permanent magnet actuators

引用

APPLIED SOFT COMPUTING 2017年 61卷 1-7页

作者： Tan, Cao Chang, Siqin Liu, Liang Nanjing Univ Sci & Technol Sch Mech Engn 200 Xiaolingwei St Nanjing 210096 Jiangsu Peoples R China

Bistable permanent magnet actuator (BPMA) has been widely used in industry as a kind of energy converter. However, its power consumption and response performance are in conflict during operating because of the conflict between holding force and initial force (the minimum threshold driving force). An optimization procedure based on a novel hierarchical genetic-particle swarm algorithm (HGP) for a hybrid excited linear actuator (HELA) constrained in a specific volume has been developed. For obtaining the objective function for each parameter combination precisely, three-dimensional finite element analysis (FEA) was employed. Meanwhile, the improvement of optimization efficiency and quality is extremely demanding because the FEA needs much computing time. The proposed hybrid algorithm adopts a hierarchical structure from the concept of "experimental classes" in China. The base level is composed of the majority general individuals of Genetic algorithms ( GA), which provides the global search ability of the entire algorithm. The top level comprises the minority elite consisting of the better individual, which performs the accurate local search by using the particle swarm optimization (PSO) algorithm with variable inertia weight and constriction coefficient. Additionally, the performance of HGP has been evaluated through the Rosenbrock function, and the proposed method is superior to other related methods Finally, the proposed procedure was verified by optimizing HELA's parameters in multidimensional parameters space under the design constraint. The results show that both of the holding force and the initial force are improved more than 25% compared with the initial design, which ensures both low power consumption and fast response. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Bistable permanent magnet actuator Optimization Hybrid algorithm Genetic algorithms particle swarm algorithm Electromagnetic force

来源：评论

学校读者我要写书评

暂无评论

Relaxed Fuzzy c-Means Clustering algorithm and its application

Relaxed Fuzzy c-Means Clustering Algorithm and its applicati...

引用

2019计算智能、工程与信息技术世界大会

作者： Chuan-jun Wen Li-fan Chen Qi Zhang School of Mathematical Sciences Changzhou Institute of Technology School of Arts and Sciences Shanghai University of Medicine and Health Sciences

The FCM algorithm was sensitive to noise data due to the normalized constraint of fuzzy membership.A novel clustering algorithm is proposed and named as relaxed fuzzy C-means clustering（RFCM） in this paper,the objective function of PCM is utilized as the objective function of RFCM,and RFCM loosens the normalized constraint and only requests the whole summation of n samples' fuzzy memberships equal to n and 0≤u≤1,particle swarm optimization algorithms（PSO） are optimally used to select the fuzzy memberships of RFCM,and the value scope of fuzzy index m is extended to m>0,the iterative formula of clustering centers are derived by gradient method for *** anti-noise performance of RFCM is analyzed theoretically,and the rationality of new value scope of m>0 is explained for RFCM,and the convergence of RFCM is discussed *** effectiveness and anti-noise performance of RFCM are proved through simulation experiments on two-dimensional Gaussian data-set for anti-noise and clustering accuracy tests.

关键词： fuzzy clustering normalization constraint fuzzy index particle swarm algorithm noise data

来源：评论

学校读者我要写书评

暂无评论

particle swarm Optimization algorithm for the Shortest Confidence Interval Problem

引用

JOURNAL OF COMPUTERS 2012年第8期7卷 1809-1816页

作者： Gao, Shang Zhang, Zaiyue Cao, Cungen Jiangsu Univ Sci & Technol Sch Comp Sci & Engn Zhenjiang 212003 Peoples R China Chinese Acad Sci Inst Comp Technol Beijing 100080 Peoples R China

Based on the example of constructing a confidence interval for variance, the notion and construction of the shortest confidence interval are put forward. Furthermore, the particle swarm algorithm for this problem is presented to solve this non-linear programming problem. Compared with the confidence interval calculated with traditional method, it has distinct advantage. The optimum results which is used to find the shortest confidence interval of variance and mean variance are given under the confidence level 0.9 and 0.95. The shortest confidence interval about Gamma distribution, Laplace distribution, Weibull distribution and beta distribution are also discussed.

关键词： mathematical statistics confidence interval the shortest interval particle swarm algorithm

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：