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检索条件"任意字段=International Workshop on Multilevel Optimization - Algorithms and Applications"

共 1022 条记录，以下是751-760 订阅

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The Modeling and Simulation of the Car-following Behavior Based on Fuzzy Inference

The Modeling and Simulation of the Car-following Behavior Ba...

引用

international workshop on Modelling, Simulation and optimization, WMSO

作者： Qiang Gao Shuliang Hu Chao Dong Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems TianJin University of Technology Tianjin China

Car-following is hard to describe drivers' behavior with precise algorithm because of its indetermination and fuzzy characteristic when the drive controls the vehicle. An algorithm of car-following model is founded and simulated based on fuzzy inference on the basis of it. The simulation results show that it is feasible to describe drivers' behavior with fuzzy controller.

关键词： Vehicle driving Fuzzy control Vehicles Fuzzy systems Control systems Inference algorithms Vehicle safety Chaos Laboratories Control theory

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Fuzzy C-Mean Clustering algorithms Based on Picard Iteration and Particle Swarm optimization

Fuzzy C-Mean Clustering Algorithms Based on Picard Iteration...

引用

ETT and GRS international Education Technology and Training, and international workshop on Geoscience and Remote Sensing

作者： Hsiang-Chuan Liu Jeng-Ming Yih Der-Bang Wu Shin-Wu Liu Department of Bioinformatics Asia University Taichung Taiwan Graduate Institute of Educational Measurement Department of Mathematics Education Taichung University Taichung Taiwan Department of Cell and Developmental Biology Rutgers University U.S.A.

The popular fuzzy c-means algorithm (FCM) converges to a local minimum of the objective function. Hence, different initializations may lead to different results. The important issue is how to avoid getting a bad local minimum value to improve the cluster accuracy. The particle swarm optimization (PSO) is a popular and robust strategy for optimization problems. But the main difficulty in applying PSO to real-world applications is that PSO usually need a large number of fitness evaluations before a satisfying result can be obtained. In this paper, the improved new algorithm, ldquoFuzzy C-Mean based on Picard iteration and PSO (PPSO-FCM)rdquo, is proposed. Two real data sets were applied to prove that the performance of the PPSO-FCM algorithm is better than the conventional FCM algorithm and the PSO-FCM algorithm.

关键词： Clustering algorithms Particle swarm optimization Nonlinear equations Cells (biology) Robustness Educational technology Geoscience and remote sensing Bioinformatics Asia Particle measurements

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Evolutionary algorithms for the Component Selection Problem

Evolutionary Algorithms for the Component Selection Problem

引用

international workshop on Database and Expert Systems applications

作者： Andreea Vescan Crina Grosan Horia F. Pop Department of Computer Science Babeş-Bolyai University Cluj-Napoca Romania

Component selection is a crucial problem in component based software engineering. Component based software engineering (CBSE) is concerned with the assembly of pre-existing software components that leads to a software system that responds to client-specific requirements. We are approaching the component selection involving dependencies between components (requirements). We formulate the problem as multiobjective. The approach used is an evolutionary computation technique. Various representations were used with various applied methods to deal with the multiobjectives.

关键词： Software Strontium optimization Computational modeling Evolutionary computation Conferences Software engineering

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Miniaturization of UWB Antennas and its Influence on Antenna-Transceiver Performance

Miniaturization of UWB Antennas and its Influence on Antenna...

引用

international workshop on Antenna Technology: Small Antennas and Novel Metamaterials, iWAT

作者： Soheil Radiom Hadi Aliakbarian Guy Vandenbosch Georges Gielen Katholieke Universiteit Leuven Belgium

A modified small-size tapered monopole antenna is optimized for ultra wideband applications in co-design with the transceiver. Our optimization procedure aims at finding an antenna not only with low VSWR, but also miniaturizing the antenna at the same time. Our proposed optimization algorithm, real-coded compact genetic algorithm, RCCGA, has lowered the antenna area more than 48% compared to previous work for 3.1 to 11.7 GHz bandwidth operation. Design with the need for co-design and co-integration of the whole system the optimized antenna area is even more miniaturized and this paper explains in detail the trade off between antenna size, antenna performance and transceiver performance.

关键词： Ultra wideband antennas Bandwidth Ultra wideband technology Transceivers Student members Circuit simulation Impedance matching Microstrip antennas Genetic algorithms Design optimization

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Dynamic spectrum management: optimization and game theoretic formulations

Dynamic spectrum management: Optimization and game theoretic...

引用

4th international workshop on Internet and Network Economics, WINE 2008

作者： Luo, Zhi-Quan University of Minnesota United States

ISBN: (纸本)3540921842

Achieving efficient spectrum usage is a major challenge in the management of a complex communication system. With multiple users having conflicting objectives who share a common spectrum, some of whom may be hostile, careful resource allocation is essential for the effective utilization of the available frequency. Conventionally, spectrum sharing is achieved via orthogonal transmission schemes whereby the available frequency band is divided into multiple tones (or bands) which are pre-assigned to all the users on a non-overlapping basis. However, such "static orthogonal spectrum sharing" approach can lead to low bandwidth utilization. In fact, various recent spectrum occupancy studies have demonstrated that a typical geographical region has wide swathes of frequencies (up to 2/3 of the allocated radio spectrum) that are not used at any given time. While the utilization of spectrum varies with time, a significant amount of spectrum is available for opportunistic wireless applications among secondary users. Spectrum-sensing cognitive radio technology allows devices to dynamically and automatically seek out and use the optimum frequencies and bandwidth. To take advantage of the unused spectrum capacity, the users dynamically adapt to the spectral environment and change transmission or reception parameters on the fly. This allows for more efficient wireless communication without causing harmful interference with legacy systems or other devices using the same frequency bands. In these systems all users are allowed to use all the tones simultaneously. In comparison with the static spectrum sharing policies, this setup offers significantly greater freedom in utilizing the spectrum. A major challenge in the development of opportunistic spectrum sharing technology is to devise efficient algorithms for the distributed management of frequency slots and transmit power. This tutorial will describe various optimization and game theoretic formulations of the dynamic spectrum manag

关键词： Legacy systems

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Scalable optimization algorithms for discrete event systems with real-time constraints: An overview of recent developments

Scalable optimization algorithms for discrete event systems ...

引用

international workshop on Discrete Event Systems, WODES

作者： Jianfeng Mao Christos G. Cassandras Department of Manufacturing Engineering Boston University Brookline MA USA

Discrete event systems with real-time constraints involve tasks that must be completed within specified hard deadlines. Guaranteeing such constraints requires a control effort measured through a cost function, giving rise to a class of nonlinear optimization problems. We overview recent developments aimed at solving such problems in an efficient scalable fashion suitable for on-line applications with limited computational resources. We describe how structural properties of the optimal state trajectory in such problems can be exploited and present a critical task decomposition algorithm (CTDA) when tasks are processed by a single-stage system. When tasks are processed over multiple stages and are subject to end-to-end real-time constraints, a different set of structural properties is exploited leading to a virtual deadline algorithm (VDA).

关键词： Discrete event systems Conferences

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Scheduling Geo-processing Workflow applications with QoS

Scheduling Geo-processing Workflow Applications with QoS

引用

ETT and GRS international Education Technology and Training, and international workshop on Geoscience and Remote Sensing

作者： Xianfeng Song Junzhi Liu College of Resources and Environment Graduate School of Chinese Academy of Sciences Beijing China

With the development of OGC Web service program (OWS), Web GIS has progressed towards a service-oriented paradigm that enables a new way to distributed geospatial computing. Many applications require geo-processing workflow (GPW) to take advantage of spatial databases or computing resources distributed over Web based their control or task. This paper presents a dual-layer framework to implement geo-processing workflow, in which an abstract workflow is defined in abstract layer to represent a user-specific task flowchart and a concrete workflow is orchestrated in concrete layer to bind geospatial Web services distributed world wide. Within the framework, we present a tree-coded genetic algorithm (GA) approach to address optimization problems in the process of instantiating an abstract workflow as a concrete workflow. The algorithm performance is analyzed through an example and well verified by the result from integer linear programming (ILP).

关键词： Concrete Web services Distributed computing Processor scheduling Geographic Information Systems Distributed databases Spatial databases Flowcharts Genetic algorithms Performance analysis

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A global optimal technique based on Moving Least Square and Improved Differential Evolution

A global optimal technique based on Moving Least Square and ...

引用

international Conference on Electrical Machines and Systems (ICEMS)

作者： Yong Zhang Gang Lei K. R. Shao L. D. Lavers College of Electrical & Electronic Engineering Huazhong University of Science and Technology Wuhan China Department of Electrical & Computer Engineering University of Toronto Toronto Canada

This paper presents a global optimal technique based on moving least square (MLS) fitting technique and improved differential evolution algorithm (IDEA) for inverse problems on optimizing electromagnetic equipments. In the proposed method, MLS are firstly used to simulate complex objective functions as a response surface model (RSM) in multidimensional space, for transforming an implicit function to an explicit one, then differential evolution algorithm (DEA) is improved and used by combining with MLS to get the global optimization with high accuracy and efficiency. TEAM workshop Problem 22, as numerical benchmark, indicates that the proposed method is superior to other random optimal techniques, and it can be comprehensively used for inverse problems in engineering electromagnetic applications.

关键词： Least squares methods multilevel systems Surface fitting Inverse problems optimization methods Response surface methodology Electromagnetic devices Electromagnetic analysis Least squares approximation Multidimensional systems

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Evolving Fuzzy Classifier System Using PSO for RoboCup Vision applications

Evolving Fuzzy Classifier System Using PSO for RoboCup Visio...

引用

3rd international workshop on Genetic and Evolving Fuzzy Systems (GEFS 2008)

作者： Narges Shamshiri Milani Alireza Kashanipour Amir Reza Kashanipour Department Electrical Engineering Sahand University of Technology Tabriz Iran Department of Electrical Engineering Azad University of Qazvin Qazvin Iran Department of Electrical Engineering Azad University Tehran Iran

In this paper we propose a color classification algorithm in which an evolutionary design optimizes a fuzzy system for Color Classification and Image Segmentation. This system works with the least number of rules and has minimum error rate by the mean of Particle Swarm optimization (PSO) method. In this approach each particle of the swarm codes a set of fuzzy rules. During evolution, each member of a population tries to maximize a fitness criterion which has designed to raise classification rate and to reduce the number of rules. Finally, the particle with the highest fitness value is selected as the best set of fuzzy rules for image segmentation. Fuzzy sets are defined on the H, S and L components of the HSL Color Space to provide a fuzzy logic model which aims to follow the human intuition of Color Classification. Color-based vision applications face the challenge of color variations by illumination. The final system designed by this method is adaptive to continuous variable lighting according to its evolving-fuzzy nature. In this method parameters setting is done only once. The experimental results in RoboCup leagues demonstrate that the presented approach can be very robust to noise and light variations.

关键词： Fuzzy systems Fuzzy sets Image segmentation Classification algorithms Algorithm design and analysis Design optimization Error analysis Particle swarm optimization Fuzzy logic Humans

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Ant Colony optimization and Swarm Intelligence 2008

引用

丛书名： Lecture Notes in Computer Science

2008年

作者： Marco Dorigo Mauro Birattari Christian Blum Maurice Clerc Thomas Stützle Alan Winfield

ISBN: (数字)9783540875277

ISBN: (纸本)9783540875260

This book constitutes the refereed proceedings of the 6th international workshop on Ant Colony optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008. The 17 revised full papers, 24 revised short papers, and 10 extended abstracts presented were carefully reviewed and selected from 91 submissions. The papers cover theoretical and foundational aspects of computational intelligence and related disciplines with special focus on swarm intelligence and are devoted to behavioral models of social insects and new algorithmic approaches, empirical and theoretical research in swarm intelligence, applications such as ant colony optimization or particle swarm optimization, and theoretical and experimental research in swarm robotics systems.

关键词： Ant algorithms Congresses. Mathematical optimization Computer programs Congresses.

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