检索结果-内蒙古大学图书馆

Lower bound estimation of the maximum allowable initial error and its numerical calculation

Atmospheric and Oceanic Science Letters 2018年第5期11卷 438-443页

作者： CAO Yi-Xing ZHENG Qin YAN Jun Graduate School PLA Army Engineering University Department of Basic PLA Army Engineering University

In the numerical prediction of weather or climate events,the uncertainty of the initial values and/or prediction models can bring the forecast result’s *** to the absence of true states,studies on this problem mainly focus on the three subproblems of predictability,i.e.,the lower bound of the maximum predictable time,the upper bound of the prediction error,and the lower bound of the maximum allowable initial *** at the problem of the lower bound estimation of the maximum allowable initial error,this study first illustrates the shortcoming of the existing estimation,and then presents a new estimation based on the initial observation precision and proves it ***,the new lower bound estimations of both the two-dimensional ikeda model and lorenz96 model are obtained by using the cnop(conditional nonlinear optimal perturbation)method and a pso(particle swarm optimization)algorithm,and the estimated precisions are also ***,the estimations yielded by the existing and new formulas are compared;the results show that the estimations produced by the existing formula are often incorrect.

关键词： Predictability problem maximum allowable initial error particle swarm optimization algorithm Conditional Nonlinear Optimal Perturbation(CNOP)

来源：评论

学校读者我要写书评

暂无评论

Research on gateway deployment of WMN based on maximum coupling subgraph and PSO algorithm

引用

SOFT COMPUTING 2017年第4期21卷 923-933页

作者： Li, Yang Huang, Shuqiang Fan, Rensheng Zhang, Zhen Zhou, Yuyu Jinan Univ Coll Informat Sci & Technol Guangzhou Guangdong Peoples R China Jinan Univ Network & Educ Technol Ctr Guangzhou Guangdong Peoples R China

The maximum distance from the access points to the nearest gateways determines the network time delay, and has an important effect on network performance in wireless mesh networks. Motivated by the gateway deployment problem, this study is focused on optimizing the gateway deployment by minimizing the maximum distance. This is done by first improving upon theorems so that the plane can be divided into several intersecting regions;vertices locate in the same region are equivalent and can connect the same access points;the coordinates of the regions can also be determined. Then, maximum coupling subgraph is used in order to recognize the maximum intersecting regions;meanwhile, the coordinates are calculated by representative points. Lastly, an RPSO algorithm is designed in which representative points are taken as the initial particles to search the optimal gateway deployment. The simulation results demonstrate that the optimal gateway deployment, as determined by the RPSO algorithm process, has a smaller coverage radius, a more stable result and a faster convergence rate as compared to other algorithms.

关键词： Wireless mesh network Gateway deployment Geometric K-center problem particle swarm optimization algorithm Maximum coupling subgraph Representative point

来源：评论

学校读者我要写书评

暂无评论

Super-Resolution Reconstruction From Multiple Defocused Infrared Images of Stationary Scene

IEEE PHOTONICS JOURNAL

引用

IEEE PHOTONICS JOURNAL 2017年第5期9卷 1-16页

作者： Mao, Yuxing Zhao, Benjiang Yan, Dongmei Jia, Haiwei Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing 400044 Peoples R China Hangzhou Yuanzhou Med Technol Co Ltd Hangzhou 310052 Zhejiang Peoples R China

Infrared image has poor visual effect for its low resolution. Super-resolution reconstruction (SRR) is an effective means to address this problem. Existing SRR algorithms use well-focused images and ignore the value of defocused images generated by the infrared imaging system during focusing. The basic idea of the present study is to treat a defocused infrared image as distribution and accumulation of scene information among different pixels of the infrared detector, as well as a valid observation of the imaged subject;defocused images are the result of blurring a corresponding high resolution (HR) image using a point spread function (PSF) followed by downsampling. From this idea, we used multiple defocused images to build an observation model for HR images and propose an SRR algorithm to approach the HR images. We have developed an image degradation model by analyzing optical lens imaging, using the particle swarm optimization algorithm to estimate the PSF of the HR image, and using compressed sensing theory to implement SRR based on the noncoherent characteristics of the defocused infrared images. Experiments demonstrate that our method can be used to obtain more information about details of a scene and improve the visual effect without adding any hardware facilities, improving the recognition and interpretation of the image subject.

关键词： Defocused infrared image super-resolution reconstruction point spread function compressed sensing particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Simultaneous allocation of electric vehicles' parking lots and distributed renewable resources in smart power distribution networks

引用

SUSTAINABLE CITIES AND SOCIETY 2017年 28卷 332-342页

作者： Amini, M. Hadi Moghaddam, Mohsen Parsa Karabasoglu, Orkun Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA Sun Yat Sen Univ Carnegie Mellon Univ Joint Inst Guangzhou 510006 Guangdong Peoples R China SYSU Sch Elect & Informat Technol Guangzhou Guangdong Peoples R China Tarbiat Modares Univ Fac Elect & Comp Engn Tehran Iran

Electric vehicles (EVs) and distributed renewable resources (DRRs) are introduced to achieve three of the most pivotal objectives of this century: using environmentally-friendly energy resources, reliable supply of the load demand, and sustainable development of power systems. To achieve the aforementioned goals, simultaneous utilization of DRRs and EVs should be implemented in a scheduled manner. In this paper, we propose a two-stage approach for allocation of EV parking lots and DRRs in power distribution network. Our method considers both the economical benefits of parking lot investor and the technical constraints of distribution network operator. First, the parking lot investor offers the candidate buses for installing the parking lot to the distribution network operator based on economic objectives. Then, the distribution network decision-making is obtained to reduce loss of system. The proposed framework not only improves the distribution network loss, but also ameliorates the availability of the parking lot from the economical point of view. In order to solve the formulated optimization problem, we utilize two optimization techniques. Genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are used for the distribution network loss minimization purpose. Besides, we model the EV parking lot by expanding single EV probabilistic model. The performance of the proposed method is evaluated by allocating DRRs and EV parking lots simultaneously on the IEEE standard distribution test system. This system is bus 2 of Roy Billinton Test System (RBTS). (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Distributed renewable resource Electric vehicle Power distribution network Parking lot investor Genetic algorithm particle swarm optimization algorithm Multi-objective optimization mart distribution network

来源：评论

学校读者我要写书评

暂无评论

Implementation of Uniform Deformation Theory in semi-active control of structures using fuzzy controller

引用

SMART STRUCTURES AND SYSTEMS 2017年第4期19卷 351-360页

作者： Mohammadi, Reza Karami Haghighipour, Fariba KN Toosi Univ Technol Dept Civil Engn 1346 Vali Asr Str Tehran Iran

Protection of structures against natural hazards such as earthquakes has always been a major concern. Semi-active control combines the reliability of passive control and versatility and adaptability of active control. So it has recently become a preferred control method. This paper proposes an algorithm based on Uniform Deformation Theory to mitigate vulnerable buildings using magneto-rheological (MR) damper. Due to the successful performance of fuzzy logic in control of systems and its simplicity and intrinsically robustness, it is used here to regulate MR dampers. The particle swarm optimization (PSO) algorithm is also used as an adaptive method to develop a fuzzy control algorithm that is able to create uniform inter-story drifts. Results show that the proposed algorithm exhibited a desirable performance in reducing both linear and nonlinear seismic responses of structures. Performance of the presented method is indicated in compare with passive-on and passive-off control algorithms.

关键词： semi-active control fuzzy system MR damper Uniform Deformation Theory particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A Day-Ahead Energy Optimal Configuration of Islanded Microgrid

引用

电脑学刊 2018年第2期29卷 75-85页

作者： Xiaoxuan Ma Yiping Huang Xiaohui Wang

Microgrid can effectively utilize renewable resources and reduce fossil fuel exploitation and environmental pollution. By setting the microgrid of renewable energy sources as the research object, this paper proposes a day-ahead energy optimization method under island mode. Overall management is realized for electric energy generated by multiple renewable energy sources. Moreover, by combining with energy storage devices and power generation equipment, economic configuration of operation optimization is completed for microgrid system on the basis of particle swarm optimization algorithm under MATLAB environment.

关键词： distributed power economic optimization energy management microgrid particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food E-commerce enterprises

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2017年 106卷 351-360页

作者： Guo, Jianquan Wang, Xinyue Fan, Siyuan Gen, Mitsuo Univ Shanghai Sci & Technol Shanghai Peoples R China Univ Shanghai Sci & Technol Sch Business Shanghai Peoples R China Tokyo Univ Sci Japan Fuzzy Log Syst Inst Tokyo Japan

In view of the rapid development of low-carbon economy, the increasing distribution demand and returned demand which caused by the short shelf life and spoilage of fresh food, network and route planning model of a two-stage forward/reverse logistics is firstly proposed for fresh food e-commerce enterprises under the environment of low-carbon emissions (The objective in the first stage is to minimize the overall cost of the system, and the minimum overall cost of the circulation-type distribution vehicles routing is considered in the second stage). And the validity of the model is verified by adopting genetic algorithm (GA) and particle swarm optimization (PSO) algorithm with the study of the fresh food e-commerce enterprises of Shanghai. Furthermore, a good reference can be provided to build the forward and reverse logistics network and optimal route planning model of fresh food e-commerce enterprises and reduce the carbon emissions during its operation process. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Location and route planning Fresh food e-commerce enterprises Low-carbon Logistics network Genetic algorithm particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Strategic behavior and social optimization in a constant retrial queue with the N-policy

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第3期256卷 841-849页

作者： Wang, Jinting Zhang, Xuelu Huang, Ping Beijing Jiaotong Univ Dept Math Beijing 100044 Peoples R China

We consider customers' strategic behavior and the corresponding social maximization problem in an M/M/1 constant retrial queue with the N-policy. There is no waiting space in front of the server and customers who find the server busy have to abandon the system, but they can leave their contact details to stay on a waiting list. Consequently, after a service completion, the server will seek a customer from the waiting list at a constant retrial rate on an FCFS basis. The server is switched off whenever the system becomes empty, and is resumed only when the number of waitlisted customers reaches a given threshold. We assume that the arriving customers who find the server busy or down decide whether to leave their contact details or to balk based on a linear reward-cost structure. We examine customers' strategic response to this mechanism and compare it to the social optimal behavior with delay information. It is shown that both Follow-the-Crowd (FTC) and Avoid-the-Crowd (ATC) behaviors exist in our system, and therefore, both multiple and unique equilibrium arrival rates could exist. Through the particle swarm optimization (PSO) algorithm, we numerically obtain the optimal solution of the social welfare maximization problem. The individual equilibrium strategies are compared with the social optimum and the Price of Anarchy (PoA) is studied as a measure to quantify the inefficiency of the equilibrium strategies. Finally, numerical examples are presented to illustrate the sensitivity of some key system performance measures. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Queueing Equilibrium strategies N-policy particle swarm optimization algorithm Social optimization

来源：评论

学校读者我要写书评

暂无评论

Evaluating the performance of genetic and particle swarm optimization algorithms to select an appropriate scenario for forecasting energy demand using economic indicators: residential and commercial sectors of Iran

引用

INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING 2015年第4期6卷 345-355页

作者： Nazari, Hesam Kazemi, Aliyeh Hashemi, Mohammad-Hosein Sadat, Mir Mahmoud Nazari, Mahboobeh Univ Tehran Fac Management Chamran HighwayPOB 14155-6311 Tehran Iran Shahid Beheshti Univ Fac Power & Water Shahid Abbaspour Tehran Iran Avicenna Res Inst ACECR Nanobiotechnol Res Ctr Tehran Iran

Energy supply security is one of the strategic issues of all states. In Iran, about 35 % of the total energy is consumed by the residential and commercial sectors. According to the importance of residential and commercial sectors in energy consumption, this paper develops different models to analyze energy demand of residential and commercial sectors. The GA and PSO energy demand estimation models (GA-DEM, PSO-GEM), a suitable model for this study, is used to estimate future energy demand of the sectors. Energy demand of these sectors has been estimated in two various forms, exponential and linear models. These sectors consumption in Iran from 1967 to 2010 is considered as the case of this study. The available data are partly used for finding the optimal, or near-optimal values of the coefficient parameters (1967-2006) and partly for testing the models (2007-2010). Our results show that PSO-DEM exponential model with inputs including, value added of all economic sectors, value of made buildings, the population and the electrical and fuel appliance price index using the mean absolute percentage error on test data is the most suitable model. Finally, based on the best scenario, the energy demand of residential and commercial sectors is estimated 1718 mega barrel of crude oil equivalent (MBOE) (1 barrel = 0.159 m(3)) up to the year 2032.

关键词： Forecasting Residential and commercial sectors Energy demand Genetic algorithm particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Iterative response surface joint algorithm analysis of optimization arrangement on mistuned blades

引用

JOURNAL OF VIBROENGINEERING 2017年第6期19卷 4210-4220页

作者： Pan, Honggang Zhao, Tianyu Yuan, Huiqun Li, Bobo Northeastern Univ Sch Mech Engn & Automat Shenyang Liaoning Peoples R China Northeastern Univ Sch Sci Shenyang Liaoning Peoples R China Shenyang Inst Engn Shenyang Liaoning Peoples R China

This paper presents a test method to measure vibration characteristics of mistuned bladed disk system. Modal analysis for the disk is to verify the precision of test bench. Further mistuned parameter identification method is proposed to introduce stiffness detuning. From this the samples can be obtained. On the other hand, the joint optimization analysis system is applied which consists of iterative response surface method and particle swarm optimization algorithm. At the same time, it is proved to have higher accuracy and better generalization ability than standard polynomial response surface method for the problem in this paper. The research results indicate that the amplitudes of optimal solution are smaller than that with random arrangement. The vibration response can be improved obviously, especially for resonance region. So, this paper has a certain universality and application value for blade arrangement based on iterative response surface joint algorithm.

关键词： blade arrangement mistuned parameter identification response measurement particle swarm optimization algorithm iterative response surface

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：