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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...

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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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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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2nd international workshop on Applied Parallel Computing Computations in Physics, Chemistry and Engineering Science, PARA 1995

2nd International Workshop on Applied Parallel Computing Com...

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2nd international workshop on Applied Parallel Computing in Computations in Physics, Chemistry and Engineering Science, PARA 1995

ISBN: (纸本)3540609024

The proceedings contain 58 papers. The special focus in this conference is on Applied Parallel Computing Computations in Physics, Chemistry and Engineering Science. The topics include: A high performance matrix multiplication algorithm for MPPs;iterative moment method for electromagnetic transients in grounding systems on CRAY T3D;analysis of crystalline solids by means of a parallel FEM method;parallelization strategies for tree N-body codes;numerical solution of stochastic differential equations on transputer network;development of a stencil compiler for one-dimensional convolution operators on the CM-5;automatic parallelization of the AVL FIRE benchmark for a distributed-memory system;2-D cellular automata and short range molecular dynamics programs for simulations on networked workstations and parallel computers;pablo-based performance monitoring tool for PVM applications;linear algebra computation on parallel machines;a neural classifier for radar images;scaLAPACK;a proposal for a set of parallel basic linear algebra subprograms;parallel implementation of a lagrangian stochastic particle model for turbulent dispersion in fluids;reduction of a regular matrix pair (a, b) to block hessenberg triangular form;parallelization of algorithms for neural networks;paradigms for the parallelization of branch and bound algorithms;three-dimensional version of the danish eulerian model;a proposal for a fortran 90 interface for LAPACK;scaLAPACK tutorial;highly parallel concentrated heterogeneous computing;adaptive polynomial preconditioners for the conjugate gradient algorithm;the IBM parallel engineering and scientific subroutine library;some preliminary experiences with sparse BLAS in parallel iterative solvers and load balancing in a network flow optimization code.

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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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Interpretation of Binary Strings as Security Protocols for their Evolution by means of Genetic algorithms

Interpretation of Binary Strings as Security Protocols for t...

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international workshop on Database and Expert Systems applications

作者： Luis Zarza Josep Pegueroles Miguel Soriano Technical University of Mixteca Mexico Technical University of Catalonia Spain

The design of cryptographic and security protocols for new scenarios and applications can be computationally expensive. Examples of these can be sensor or mobile ad-hoc networks and electronic voting or auctions applications. In such cases, the aid of an automated tool generating protocols for a predefined problem can be of great utility. This work uses the Genetic algorithms (GA) techniques for the automatic design of security networked protocols. When using GA for optimizing protocols the genome definition is critical. We discuss how security protocols can be represented as binary strings. Arbitrary criteria can lead to improper strings for our GA tools. We explain and justify the steps to define genome interpretation in our optimization method. Analysis of the proposal attending is also presented as part of our contribution.

关键词： Security Genetic algorithms Cryptographic protocols Genomics Bioinformatics Cryptography Computer applications Ad hoc networks Electronic voting Algorithm design and analysis

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New Differential Evolution Algorithm with a Second Enhanced Mutation Operator

New Differential Evolution Algorithm with a Second Enhanced ...

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international workshop on Intelligent Systems and applications, ISA

作者： Changshou Deng Bingyan Zhao Anyuan Deng Rixin Hu School of Information Science and Technology Jiujiang University China

To improve the efficiency of the original differential evolution algorithm, a new differential evolution algorithm was proposed. A new framework with a single population was used to improve its' exploration ability. And a second enhanced mutation operator was used to ensure the exploitation of previous knowledge about the fitness landscape. Numerical experiments with typical benchmark functions show the proposed new version of differential evolution performs better than original differential evolution algorithm. Performances compared with dynamic differential evolution and particle swarm optimization algorithm show its superiority.

关键词： Genetic mutations Signal processing algorithms Convergence Particle swarm optimization Machine intelligence Fuzzy logic Information science Algorithm design and analysis Power engineering computing Competitive intelligence

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A Scalability Test for Accelerated DE Using Generalized Opposition-Based Learning

A Scalability Test for Accelerated DE Using Generalized Oppo...

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international Conference on Intelligent Systems Design and applications (ISDA)

作者： Hui Wang Zhijian Wu Shahryar Rahnamayan Lishan Kang State Key Laboratory of Software Engineering Wuhan University of China Wuhan China Faculty of Engineering and Applied Science Institute of Technology University of Ontario Oshawa ONT Canada

In this paper a scalability test over eleven scalable benchmark functions, provided by the current workshop (Evolutionary algorithms and other Metaheuristics for Continuous optimization Problems-A Scalability Test), are conducted for accelerated DE using generalized opposition-based learning (GODE). The average error of the best individual in the population has been reported for dimensions 50, 100, 200, and 500 in order to compare with the results of other algorithms which are participating in this workshop. Current work is based on opposition-based differential evolution (ODE) and our previous work, accelerated PSO by generalized OBL.

关键词： Scalability Life estimation System testing Acceleration Benchmark testing Evolutionary computation Robustness Chromium Intelligent systems Design optimization

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An Autogenerating Test Paper Method Based on Latent Semantic Analysis and Genetic Algorithm

An Autogenerating Test Paper Method Based on Latent Semantic...

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international workshop on Intelligent Systems and applications, ISA

作者： Huming Gao Yanjie Li Inf. Manage. Dept Tianjin Univ. of Econ. & Finance Tianjin

It is a multi-objective optimization problem to autogenerate a test paper from test bank. In this paper an autogenerating test paper method based on latent semantic analysis and genetic algorithm is proposed. Firstly the relationships of keywords among test items in a test bank are analyzed with LSA, and the weights of the test items are calculated. Then using the Genetic Algorithm to compose the test paper accorded to the weights. The proposed method can effectively select test items from Chinese test bank to compose a test paper.

关键词： Testing Algorithm design and analysis Genetic algorithms optimization methods Matrix decomposition Information management Finance Singular value decomposition Information analysis Education

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Full-Wave optimization of Nanoparticle Arrays for Beam-Steering applications

Full-Wave Optimization of Nanoparticle Arrays for Beam-Steer...

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international Electromagnetic Compatibility Conference (EMC Turkiye)

作者： Aşkın Altınoklu Özgür Ergül Middle East Technical University Ankara Turkey

We present design and optimization of nanoarrays, which consist of metallic nanoparticles that possess plasmonic properties. Optimal two-dimensional arrangements of nanoparticles are found by using an optimization environment involving genetic algorithms and a three-dimensional full-wave solver based on the multilevel fast multipole algorithm. The nanoarrays are designed to provide maximum radiation at desired directions when they are excited via isotopic sources. The designed structures and their radiation characteristics are extensively investigated by considering various parameters, such as grid size, nanoparticle shape, distance between nanoparticles, and material. The results demonstrate the favorable radiation characteristics of the designs, as well as the capabilities of the optimization environment to design compact nanoarrays for beam-steering applications.

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Island-based differential evolution with varying subpopulation size

Island-based differential evolution with varying subpopulati...

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IEEE international workshop on Computational Intelligence & applications (IWCIA)

作者： Jun-ichi Kushida Akira Hara Tetsuyuki Takahama Ayumi Kido Graduate School of Information Sciences Hiroshima City University Hiroshima Japan Faculty of Information Sciences Hiroshima City University Hiroshima Japan

Differential evolution (DE) is one of the evolutionally algorithms for solving optimization problems in a continuous space. DE has been widely applied to solve various optimization problems. Additionally, many modified DE algorithms have been developed in an attempt to improve search performance. In this paper, we propose island-based DE with varying subpopulation size. Island model is one of the effective parallel distributed model in evolutionary algorithms. In the proposed method, total population is divided into independent sub-populations called islands. The basic island model uses same control parameters for each subpopulation. In contrast, we allocate different control parameters to each island. Therefore, each island has a different convergence characteristic by using own control parameters. At fixed generation intervals, migration among islands is performed in order to preserve diversity of subpopulation. Additionally, by incorporating the operation of individual transfer, proposed method can vary subpopulation dynamically according to the function landscape. Numerical experiments are performed to illustrate the performance of the proposed method compared with basic DE. The results show that the proposed method outperforms basic DE on standard test functions including various landscape features.

关键词： Vectors Sociology Statistics Convergence Standards Educational institutions optimization

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