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

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Simulation and optimization of Kanban System for Steel Rolling

Simulation and Optimization of Kanban System for Steel Rolli...

引用

international workshop on Intelligent Systems and applications, ISA

A simulation model of kanban system for steel rolling production line is established based on discrete event simulation theory and ExtendSim simulation software. The optimal kanban quantity is obtained with the genetic algorithm optimizer module of the ExtendSim, which obviously reduced the WIP stocks and the end product stocks in the production line.

关键词： Steel Discrete event simulation Workstations Authorization Optimized production technology Mass production Heat treatment Logistics Genetic algorithms Control systems

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Technology Program Financial Forecast Model Based on CACO-SVM

Technology Program Financial Forecast Model Based on CACO-SV...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Xiu-e Yuan Yu Zou Department of Business Administration North China Electric Power University Baoding China

Accompany by the rapid changes of the world, the funds on technology programs invested by the country are increasing year by year with the growing demand. This paper introduces the theory of continuous ant colony optimization algorithms and support vector machine to analyze, predicts the financial situation of enterprises and sets up the financial forecast model CACO-SVM. Financial datas of some companies are used to train and test this arithmetic, and the results show that this model is feasible and practicable.

关键词： Technology forecasting Predictive models Ant colony optimization Cities and towns Support vector machines Support vector machine classification Algorithm design and analysis Companies Testing Arithmetic

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An Initialization Method for Clustering High-Dimensional Data

An Initialization Method for Clustering High-Dimensional Dat...

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international workshop on Database Technology and applications

作者： Luying Chen Lifei Chen Qingshan Jiang Beizhan Wang Liang Shi Software School Xiamen University Xiamen Fujian China Department of Computer Science Fujian Normal University Fujian China

In iterative refinement clustering algorithms, such as the various types of K-Means algorithms, the clustering results are very sensitive to the initial cluster centers. Conventional initialization methods tend to loss effectiveness due to the so-called "curse of dimensionality" when clustering high-dimensional data. In this paper, a local density based method is proposed to search for initial cluster centers on high-dimensional data. We define the probability density of a point as the amount of its highly similar neighborhoods with weight coefficient. Points with high density neighborhoods and low similarity are chosen as the initial cluster centers. Experimental results on real world datasets show the effectiveness of the proposed method.

关键词： Clustering algorithms Software algorithms Iterative algorithms optimization methods Databases Application software Computer science Iterative methods Data mining Loss measurement

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A Hybrid Approach of Path Planning for Mobile Robots Based on the Combination of ACO and APF algorithms

A Hybrid Approach of Path Planning for Mobile Robots Based o...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Xin Tan Dingfang Chen School of Logistics Engineering Wuhan University of Technology Wuhan Hubei China Jianghan University Wuhan Hubei China

This paper presents an optimal method based on combination of artificial potential field (APF) and ant colony optimization (ACO) algorithms for global path planning of mobile robots working in partially known environments. Two steps constitute this approach. Firstly, free space model of mobile robot is established by using visible graph method and ACO algorithm is utilized in this model to search a global collision-free path which is the shortest routine through known static obstacles. Secondly, when unknown obstacles are encountered, APF algorithm is employed to generate a real-time local path so as to avoid collision. Results of simulation experiments show that the proposed approach has good performance in convergence speed, dynamic behavior and is fit for complex environment.

关键词： Path planning Mobile robots Ant colony optimization Orbital robotics Navigation Logistics Convergence Potential energy Optimal control Production facilities

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An application of a hybrid algorithm to identification of parameters of semi-empirical model describing a real process

An application of a hybrid algorithm to identification of pa...

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

作者： Krzysztof Brzozowski Kornel Warwas University of Bielsko-Biała Poland

In the paper the problem of identification is formulated and solved using a hybrid algorithm. The identification means calculation of parameters of a model describing a real process. The method proposed is applied to a semi-empirical model of the working cycle of an engine which enables calculations of the pressure courses in a cylinder. The identification procedure determines the values of the computational model parameters in order to ensure the minimal difference between the measured and calculated pressure courses in the cylinder. The identification is performed by solving dynamic optimization task using a hybrid approach. In the hybrid algorithm genetic algorithms are connected with the gradientless Nelder-Mead method. Results of the identification for different vectors of input to the model are presented as well.

关键词： Computational modeling Engine cylinders Pressure measurement Genetic algorithms Differential equations Conferences Data acquisition optimization methods Temperature Testing

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Application of Chaos Genetic Algorithm to Transformer Optimal Design

Application of Chaos Genetic Algorithm to Transformer Optima...

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international workshop on Chaos-Fractals Theories and applications (IWCFTA)

作者： Shuang Zhang Qinghe Hu Xingwei Wang Zhiliang Zhu Software College Northeastern University Shenyang China College of Information & Science Engineering Northeastern University Shenyang China

Optimal design of power transformer is discrete, multi-variable, nonlinear, multi-purposed, and mixed programmed. According to the characteristics of transformer optimal design, the paper combines genetic algorithm with chaos to get a new mixed generic algorithm. It is adopted to transformer electromagnetic calculation optimization, proving its good performance. This research is meaningful for the popularization and application of genetic algorithm to transformer optimal design.

关键词： Chaos Genetic algorithms Algorithm design and analysis Power transformers Power transformer insulation Cost function Ant colony optimization Production Application software Educational institutions

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IPSO Algorithm of Texture Segmentation Based on MRF Model

IPSO Algorithm of Texture Segmentation Based on MRF Model

引用

international workshop on Intelligent Systems and applications, ISA

作者： Huazhong Jin Minyi Ke Junwu Bai Zhiwei Ye Sch. of Remote Sensing & Inf. Eng. Wuhan Univ. Wuhan Hubei University of Technology

An improved particle swarm optimization (IPSO) of texture segmentation approach based on Markov random field (MRF) is proposed in this paper. In the new algorithm, a population of points sampled randomly from the feasible space. Then the population is partitioned into several sub-swarms, each of which is made to evolve based on particle swarm optimization (PSO) algorithm. At periodic stages in the evolution, the entire population is shuffled, and then points are reassigned to sub- swarms to ensure information sharing. This method greatly elevates the ability of exploration and exploitation. To evaluate the performance of the proposed IPSO, the standard PSO is used for comparisons. The results show that IPSO is a more effective global optimization than PSO in texture segmentation based on MRF.

关键词： Particle swarm optimization Image segmentation Partitioning algorithms Remote sensing Markov random fields Image texture Computational modeling Simulated annealing Genetic mutations Pixel

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Service Matching Mechanisms in Pervasive Computing Environments

Service Matching Mechanisms in Pervasive Computing Environme...

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international workshop on Intelligent Systems and applications, ISA

作者： Qingcong Lv Jiliang Zhou Qiying Cao College of Information Science and Technology University of Donghua Shanghai China College of Computer Science and Technology University of Donghua Shanghai China

The increasing popularity of personal wireless devices has raised new demands for the efficient discovery of heterogeneous devices and services in pervasive environments. The existing syntactic level service matching mechanisms such as Jini, UPnP, etc., are limited to syntactic comparisons based on attributes or interfaces. In order to overcome the limitations in these approaches, there has been an increased interest in the use of semantic description and matching techniques to support effective service discovery. But semantic reasoning is a costly task; meanwhile service discovery should context aware in ubiquitous computing environments, so it should provide optimization of semantic matching algorithm and context-aware service matching. This paper first compares syntactic service matching and semantic service matching then analyzes how to optimize semantic service matching and how to provide context-aware service matching in order to efficient and effective service discovery in pervasive computing environments. Through analyzing the shortcomings of the algorithms, and giving optimization service matching algorithms in environments may be designed.

关键词： Pervasive computing Context-aware services Educational institutions Information science Algorithm design and analysis optimization methods Computer science Context awareness Ubiquitous computing Matched filters

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7th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems, SEUS 2009

7th IFIP WG 10.2 International Workshop on Software Technolo...

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7th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems, SEUS 2009

ISBN: (纸本)3642102646

The proceedings contain 35 papers. The special focus in this conference is on Software technologies for embedded and ubiquitous systems. The topics include: Design and implementation of an operational flight program for an unmanned helicopter FCC based on the TMO scheme;energy-efficient process allocation algorithms in Peer-to-Peer systems;power modeling of solid state disk for dynamic power management policy design in embedded systems;optimizing mobile application performance with model-driven engineering;a single-path chip multiprocessor system;towards trustworthy self-optimization for distributed systems;an experimental framework for the analysis and validation of software clocks;towards a statistical model of a microprocessor’s throughput by analyzing pipeline stalls;joining a distributed shared memory computation in a dynamic distributed system;BSART (Broadcasting with Selected Acknowledgements and Repeat Transmissions) for reliable and low-cost broadcasting in the mobile Ad-Hoc Network;an algorithm for reliable and smaller congestion in the mobile Ad-Hoc Network;development of field monitoring server system and its application in agriculture;On-Line model checking as operating system service;designing highly available repositories for heterogeneous sensor data in open home automation systems;fine-grained tailoring of component behaviour for embedded systems;MapReduce system over heterogeneous mobile devices;towards time-predictable data caches for chip-multiprocessors;from intrusion detection to intrusion detection and diagnosis;model-based testing of GUI-Driven applications and parallelizing software-implemented error detection.

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A Pseudo-Parallelism Genetic Algorithm Framework to optimization of Neural Networks

A Pseudo-Parallelism Genetic Algorithm Framework to Optimiza...

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international workshop on Intelligent Systems and applications, ISA

作者： Shu-Hai Zhao Li Shao Jin-Zhu Ma School of Management University of Ji''nan Jinan China

This paper present a new approach, combined pseudo- parallelism evolution technique based on sub-population competition with parent mutation mechanism, for automatic topology optimization of multilayer feedforward neural networks. It allows that two networks with different number of individuals can be crossed to a new valid "child" network. The calculation result of an example shows that PPGA is able to get the real-time information of population diversity during the process of evolution and has some improvements in both global converging velocity and searching precision.

关键词： Genetic algorithms Neural networks Evolution (biology) Encoding Network topology Artificial neural networks Algorithm design and analysis Biological information theory Multi-layer neural network Feedforward neural networks

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