检索结果-内蒙古大学图书馆

IEEE international workshop on Intelligent Robots and Systems (IROS)

作者： I. Gravagne I.D. Walker Electrical and Computer Engineering Clemson University Clemson SC USA

There are numerous situations in robotics where it becomes desirable to minimize the maximum magnitude of a solution to an underdetermined set of linear equations. For example, there have been several approaches to finding the joint velocities of kinematically redundant robots using this philosophy. Unfortunately, the solution of this optimization problem, known as the "minimum infinity-norm solution", cannot be expressed in a closed form in general thus requiring the use of an algorithm to iteratively refine an initial guess before reaching the desired solution. In order to increase our understanding and reduce the complexity of infinity-norm algorithms, we first formulate a new "infinity inverse", and then use the new inverse to explore critical issues such as uniqueness and continuity of least infinity-norm solutions. The new inverse is compared with the well-known pseudoinverse, or minimum two-norm solution. We discuss when and why one particular norm might produce a better solution than the other, reinforcing the discussion with an interesting example of a kinematically redundant manipulator.

关键词： H infinity control Robot sensing systems Kinematics Equations Iterative algorithms Energy measurement Motion measurement Legged locomotion Constraint optimization Investments

来源：评论

学校读者我要写书评

暂无评论

Large-Scale Linear Support Vector Ordinal Regression Solver

Large-Scale Linear Support Vector Ordinal Regression Solver

引用

IEEE international Conference on Data Mining workshops (ICDM workshops)

作者： Yong Shi Huadong Wang Lingfeng Niu Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China Research Center on Fictitious Economy & Data Science Chinese Academy of Sciences Beijing China University Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467384940

In multiple classification, there is a type of commonproblems where each instance is associated with an ordinal label, which arises in various settings such as text mining, visual recognition and other information retrieval tasks. The support vectorordinal regression (SVOR) is a good model widely used for ordinalregression. In some applications such as document classification, data usually appears in a high dimensional feature space andlinear SVOR becomes a good choice. In this work, we developan efficient solver for training large-scale linear SVOR basedon alternating direction method of multipliers(ADMM). Whencompared empirically on benchmark data sets, the proposedsolver enjoys advantages in terms of both training speed andgeneralization performance over the method based on SMO, which invalidate the effectiveness and efficiency of our algorithm.

关键词： Support vector machines Training Prediction algorithms Machine learning algorithms Big data Measurement optimization

来源：评论

学校读者我要写书评

暂无评论

RSO based selective harmonic elimination control for nine-level switched capacitor inverter

引用

international JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS 2024年

作者： Sen, Priyanka Sahoo, Ashwin K. Panda, Kaibalya P. Jha, Vandana Pandit Deendayal Energy Univ Gandhinagar Sch Energy Technol Dept Elect Engn Gandhinagar Gujarat India CV Raman Global Univ Dept Elect Engn Bhubaneswar Odisha India RV Coll Engn Dept Elect & Elect Engn Bengaluru India

Renewable energy utilization has gained much attention in the recent time owing to the sharp increase in the power demand. Out of different renewable sources, photovoltaic (PV) energy utilization in different forms is one of key focus. Power converter such as multilevel inverters (MLIs) are proven as key components for PV systems as well as for other applications such as motor drives, electric vehicles, and charging stations. With the advancement of the design of MLIs, the switched-capacitor (SC) based MLIs have been widely deployed for their boosting capability which is a major requirement for PV systems. In this paper, a reduced switch single input step-up 9-level SC MLI is first proposed. Followed by this, a new Rat Swarm optimization (RSO) based Selective Harmonic Elimination (SHE) control method is incorporated for switching operation. RSO has the ability to provide the solution with higher competency within less time and a less computationally complex approach. The operation of proposed structure is analyzed and its advantages are justified by comparison with exiting topologies. The effectiveness of RSO based SHE scheme is also verified by comparing it with other nature-inspired algorithms. The effectiveness and workability of the proposed system are examined using simulation and experimental tests.

关键词： multilevel inverter (MLI) photovoltaic system rat swarm optimization (RSO) switched capacitor total harmonic distortion (THD)

来源：评论

学校读者我要写书评

暂无评论

A peer to peer traffic identification method based on support vector machine and artificial bee colony algorithm

A peer to peer traffic identification method based on suppor...

引用

IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Chunzhi Wang Huili Zhang Zhiwei Ye Yuanli Du Hubei University of Technology School of Computer Science Wuhan China

ISBN: (纸本)9781467383622

Today, Peer-to-peer (P2P) traffic is the most important network flow on the Internet; meanwhile it gives rise to many security problems for the network management. Therefore P2P traffic identification is the hottest topic of P2P traffic management. Support vector machine (SVM) has advantages with resolving small samples for P2P classification problems. However, the performance of SVM is primarily dependent on its parameters. At present, genetic algorithm and particle swarm optimization algorithm are commonly used to learn best parameters for SVM. However, these methods are easy to run into local optimal solution. Thus, artificial bee colony algorithm is proposed to optimize the parameters of SVM and has been applied to P2P traffic identification. And the real campus traffic data is used as the research object to do simulating experiments. The experimental results show that the parameters of support vector machine optimized by artificial bee colony have high P2P classification accuracy.

关键词： Support vector machines Classification algorithms optimization Kernel Algorithm design and analysis Training Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

QPSO-ELM: An evolutionary extreme learning machine based on quantum-behaved particle swarm optimization

QPSO-ELM: An evolutionary extreme learning machine based on ...

引用

international workshop on Advanced Computational Intelligence (IWACI)

作者： Zeping Yang Xinxiu Wen Zhanquan Wang School of Information Science and Engineering East China University of science and Technology Shanghai China Department of Computer Science and Engineering University of Minnestoa USA

Extreme learning machine (ELM), as an emergent technology, has attracted tremendous attention from various fields for its fast learning speed. Different from traditional gradient-based learning algorithms for feed-forward neural networks, ELM need not be neuron alike and learns with good generalization performance. However, ELM may require more hidden neurons than traditional tuning-based learning algorithms in some applications due to the random assignment of the input weights and hidden biases. In this paper, a novel evolutionary ELM is proposed named QPSO-ELM which uses the quantum-behaved particle swarm optimization (QPSO) to select the input weights and hidden layer biases and reduces both the structural and empirical risks. The experimental results demonstrate the effectiveness of the proposed method with more compact networks.

关键词： Training Testing Neural networks Nickel Accuracy Glass Liver

来源：评论

学校读者我要写书评

暂无评论

Material Flow Analysis and Plant Lay-Out optimization of a Manufacturing System

Material Flow Analysis and Plant Lay-Out Optimization of a M...

引用

IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Francesco Longo Giovanni Mirabelli Enrico Papoff Mechanical Department University of Calabria Italy

The paper proposes the results of a project developed by the authors in collaboration with a production system working in the field of manufacturing wood products. The first step of the project was an accurate analysis of the system together with the design of new production documents in order to collect data about the system itself. The collected data has been used to propose an initial solution of plant lay-out. The second step of the project was the realization of a simulation model. The model has been used to find an optimal plant layout configuration by means of genetic algorithms with the goal of material handling cost minimization.

关键词： Manufacturing systems Production systems Flow production systems Genetic algorithms Materials handling Performance analysis Algorithm design and analysis Raw materials Flowcharts Collaborative work

来源：评论

学校读者我要写书评

暂无评论

Multi-classifier System Configuration Using Genetic algorithms

Multi-classifier System Configuration Using Genetic Algorith...

引用

international workshop on Frontiers in Handwriting Recognition

作者： D. Impedovo G. Pirlo D. Barbuzzi Dipartimento di Informatica Università degli Studi di Bari Bari Italy

Classifier combination is a powerful paradigm to deal with difficult pattern classification problems. As matter of this fact, multi-classifier systems have been widely adopted in many applications for which very high classification performance is necessary. Notwithstanding, multi-classifier system design is still an open problem. In fact, complexity of multi-classifiers systems make the theoretical evaluation of system performance very difficult and, consequently, also the design of a multi-classifier system. This paper presents a new approach for the design of a multi-classifier system. In particular, the problem of feature selection for a multi-classifier system is addressed and a genetic algorithm is proposed for automatic selecting the optimal set of features for each individual classifier of the multi-classifier system. The experimental results, carried out in the field of handwritten digit recognition, demonstrate the effectiveness of the proposed approach.

关键词： Genetic algorithms optimization Sociology Statistics Handwriting recognition Classification algorithms Machine learning

来源：评论

学校读者我要写书评

暂无评论

Euclidean Particle Swarm optimization

Euclidean Particle Swarm Optimization

引用

international workshop on Intelligent Networks and Intelligent Systems (ICINIS)

作者： Hongbing Zhu Chengdong Pu Kei Eguchi Jinguang Gu College of Computer Science and Technology Wuhan University of Science and Engineering Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Department of Technology Education Shizuoka University Shizuoka Japan

Particle swarm optimization (PSO) is a swarm intelligence algorithm, has been successfully applied to many engineering optimization problems and shown its high search speed in these applications. However, as the dimension and the number of local optima of optimization problems increase, PSO and most existing improved PSO algorithms such as, the standard particle swarm optimization (SPSO) and the Gaussian particle swarm optimization (GPSO), are easily trapped in local optima. In this paper we proposed a novel algorithm based on SPSO called Euclidean particle swarm optimization (EPSO) which has greatly improved the ability of escaping from local optima. To confirm the effectiveness of EPSO, we have employed five benchmark functions to examine it, and compared it with SPSO and GPSO. The experiments results showed that EPSO is significantly better than SPSO and GPSO, especially obvious in higher-dimension problems.

关键词： Particle swarm optimization Educational technology Educational institutions Computer science Intelligent networks Euclidean distance Interference Probability distribution Intelligent systems Computer science education

来源：评论

学校读者我要写书评

暂无评论

Key Message Algorithm: a communication optimization algorithm in cluster-based parallel computing

Key Message Algorithm: a communication optimization algorith...

引用

IEEE international Conference on Cluster Computing

作者： Ming Zhu Wentong Cai Bu-Sung Lee School of Applied Science Nanyang Technological University Singapore

ISBN: (纸本)0769503438

Parallel computing using Network of Workstations (NOWs) has become very popular recently. However, the execution of parallel applications on such systems has been hampered by the high communication overhead. To reduce the communication overhead and to speedup the execution of parallel applications on NOWs, the paper proposes a Key Message approach that minimizes the cost of message passing in a parallel application by prioritizing communications in the underlying shared communication network. We first describe the queueing network model on which our approach is based, then introduce the algorithm that identifies the messages to be prioritized in a parallel application, and finally discuss the results obtained. Our preliminary analysis of the algorithm on randomly generated task graphs shows improvement over the system without using the prioritization scheme.

关键词： Clustering algorithms Parallel processing Parallel programming Protocols Workstations Costs Algorithm design and analysis Distributed computing Communication system control Control systems

来源：评论

学校读者我要写书评

暂无评论

Interactive system design and end-to-end optimization in sensor networks

Interactive system design and end-to-end optimization in sen...

引用

international workshop on Wearable Micro and Nano Technologies for Personalized Health (pHealth)

作者： Knut Grythe Arne Lie Ilangko Balasingham Department of Communication Systems SINTEF ICT Norway Interventional Centre Rikshospitalet University Hospital Norway Department of Electronics and Telecommunications Norwegian University of Science and Technology Norway

This paper proposes an application oriented four layered quality of service (QoS) stack for wireless sensor networks (WSN), including a supporting system architecture for interacting with WSNs using the MPEG-21 multimedia framework in an medical application setting. The application of the WSNs is signal processing algorithms reporting elaborated observed sensor data to external users. The QoS model supports the tradeoff between end-users expected QoS combined with optimized energy consumption. The MPEG-21 standard is chosen as the media resource framework due to the fact that future hospitals will have networks comprising WSNs supporting an always increasing amount of both low rate medical sensor data as well as high rate audiovisual content. Furthermore due to the heterogeneous set of user terminals and network resources, media adaptation will become important to provide reliable and robust quality of service. In this paper, we argue for an extension of the MPEG-21 terminology for use in biomedical wireless sensor networks and incorporate the requirements needed for medical applications.

关键词： Quality of service Wireless sensor networks Transform coding Media Signal processing algorithms Degradation Wireless communication

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：