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2009 Joint International conference on Modelling and Simulation

作者： Zhao, Long Yang Song, Lin Yang Mi, Li Shu, Ling Chen Jiangsu University Zhenjiang Jiangsu China Jiangsu University of Science and Technology Zhenjiang Jiangsu China

ISBN: (纸本)9781846260612

Based on a kind of typical high speed monohull, the paper discusses an integrate optimization's method of navigational performance and structure characteristic with the materials of some ships and some relevant experience expressions. There're 2 parts of synthetical optimization of mechanics properties for ships: navigation performances and structural mechanics properties .The authors use the weighted sum of rapidity, sea-keeping ability and maneuverability as the sub-objective function of navigation performances;use the weighted sum of static and dynamic properties as the sub-objective function of structural mechanics properties;The weighted sum of these 2 sub-objective functions is just the general objective function. Stability, buoyancy and some other characteristics as well as limits of design variables form the constraint conditions. The author constructed an new algorithm that is composed of the delamination-parallel thinking, maximal distance principle , the chaos algorithm and the genetic algorithm. Then the software with friendly interface is programmed by C++ language. A large number of calculation results show that: the algorithm(DP-GA-chaos) not only can conquer the prematurely problem of GA, but also consume little calculation time and has higher efficiency.

关键词： Genetic algorithms

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Hardware-Aware Model of Sigma-Delta Cellular Neural Network

Hardware-Aware Model of Sigma-Delta Cellular Neural Network

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European conference on Circuit Theory Design

作者： Aomori, Hisashi Naito, Yuki Otake, Tsuyoshi Takahashi, Nobuaki Matsuda, Ichiro Itoh, Susumu Tanaka, Mamoru Tokyo Univ Sci Dept Elect Engn 2641 Yamazaki Noda Chiba 2788510 Japan Sophia Univ Dept Informat & Commun Sci Chiyoda Ku Tokyo 1028554 Japan Tamagawa Univ Dept Software Sci Tokyo 1948610 Japan IBM Japan Ltd IBM Syst & Technol Grp Kanagawa 2428502 Japan

ISBN: (纸本)9781424438952

The sigma-delta cellular neural network (SD-CNN) is a complete framework of a spatial domain sigma-delta modulator, and has a very high image reconstruction (AD-to-DA) performance. In this architecture, the A-template, given by a 2D low pass filter (LIT), is used for a digital to analogue converter (DAC), the C-template works as an integrator, and the nonlinear output function is for the bilevel output. By exploiting to the nonlinear optimization ability of CNN spatio-temporal dynamics, optimal binary and reconstruction image can be obtained. However, in the conventional SD-CNN, the Gaussian LIT, whose coefficients are real number, is used as the A-template. This filter coefficients requirement is one of major factors that restricts a hardware implementation. In this paper, a SD-CNN having hardware-friendly filter coefficients is proposed. Moreover its AD and DA performance is confirmed by some experiments.

关键词： Low pass filters

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Immune optimization based Genetic Algorithm for incremental association rules mining

Immune Optimization based Genetic Algorithm for incremental ...

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International conference on Artificial Intelligence and Computational Intelligence

作者： Zhang, Genxiang Chen, Haishan Xiamen Univ Software Sch Xiamen Fujian Peoples R China

ISBN: (纸本)9780769538167

Business activity and engineering practice always produce large data sets carrying important information, but because of the data sets' largeness and frequent updating, if we apply the Apriori based algorithms to them for incremental rules mining, it is not only inefficient, but also either redundant rules would be produced under low threshold of minimal support, which makes users hardly distinguish which rules arc really meaningful, or significant rules with low support in additional data set would possibly lost when the threshold is defined high. Motivated by these, therefore, following genetic principles, and combining with natural immune evolution theory and relevant bionic mechanism, this paper proposes an IOGA (Immune optimization based Genetic Algorithm) approach for incremental association rules mining to large and frequent updating data sets. Experiment demonstrates the method's efficiency and presents its good performance in pruning redundant rules and discovering meaningful rules, perceiving low support rules in additional data set.

关键词： immune optimization genetic algorithm association rules incremental mining

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performance optimization of Yagi-Uda antenna in wireless communication with additional driven elements using genetic algorithms

Performance optimization of Yagi-Uda antenna in wireless com...

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6th IASTED International conference on Antennas, Radar, and Wave Propagation, ARP 2009

作者： Mohammed, Jafar Ramadhan Communication Engineering Department Electronics Engineering College University of Mosul Mosul Iraq

ISBN: (纸本)9780889867956

A new structure of Yagi-Uda antenna is proposed that can improve the forward/backward ratio (f/b) significantly while maintaining a high gain. This structure involves the addition of two driven dipole elements to the main Yagi-Uda array, the resulting antenna is denoted by augmented Yagi-Uda. The design of such antenna is performed using GA in conjunction with the SNEC software. Comparisons are made among the augmented and conventional Yagi-Uda configurations for different design parameters. It is observed that an improvement of at least 66dB in the f/b ratio is obtained. Moreover, the augmented antenna outperforms the conventional Yagi-Uda antenna, because it achieves higher performance standards over an extended bandwidth around 2.4GHz.

关键词： Genetic algorithms

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A multiple constraint quality of service routing algorithm base on dominating tree

A multiple constraint quality of service routing algorithm b...

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2009 International conference on Computational Intelligence and software Engineering, CiSE 2009

作者： Wang, Xueshun Yu, Shao-Hua Dai, JinYou Luo, Ting Huazhong University of Science and Technology Wuhan Hubei 430074 China Wuhan FiberHome Networks Company. Ltd. Wuhan Hubei 430074 China

ISBN: (纸本)9781424445073

Providing quality of service (QoS) guarantees in networks gives rise to several challenging issues. One of them is how to determine a feasible path that satisfies a set of constraints while maintaining high utilization of network resources. Multiconstrained QoS routing algorithm finds a feasible route in network that satisfies multiple independent constraints. In general, multi-constrained path selection is a NP-complete problem that cannot be exactly solved in polynomial time. The NP-complete problem is converted into a multi-objective optimization problem with constraints, and optimizes multiconstraint QoS parameter respectively in this paper. A multiple constrained QoS routing algorithm is then proposed to generate a set of non-dominated optimal route based on the optimization principle of multi-objective evolutionary algorithms (DTRA), which can attain a satisfied multi-constraint QoS parameter nondominates set based on dominating tree. The dominating tree preserves the necessary relationships among QoS routings, and reduces the comparisons among QoS routing distinctly. So the convergence performance is quick. The theoretic analysis and experiment results show that our proposed algorithm (DTRA) is effective for multi-constrained QoS routing, and can improve the performance of networks. ©2009 IEEE.

关键词： Multiobjective optimization

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Proceedings of 19th International conference Radioelektronika 2009, RADIOELEKTRONIKA '09

Proceedings of 19th International Conference Radioelektronik...

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Proceedings of 19th International conference Radioelektronika 2009, RADIOELEKTRONIKA '09

ISBN: (纸本)9781424435388

The proceedings contain 83 papers. The topics discussed include: comparison of some mathematical models for MTL transient and sensitivity analysis;software for automatic head position monitoring;on MC-CDMA transmission system performance at nonlinear high power amplifier of transmitter over frequency selective fading channel;pulse generator controlled by microcontroller;portable AC current source;novel current-mode quadrature oscillators with explicit-current-outputs using CCCDTA;design optimization of the power transformer and inductor in the switch-mode power supplies;steganography systems by using CDMA techniques;modified buffered transconductance amplifier for analog signal processing;PLL phase-noise modeling by PC;radio frequency systems of the CERN synchrotron accelerators;and binary division algorithm and implementation in VHDL.

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SBA: A software Package for Generic Sparse Bundle Adjustment

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ACM TRANSACTIONS ON MATHEMATICAL software 2009年第1期36卷 2:1-2:30页

作者： Lourakis, Manolis I. A. Argyros, Antonis A. FORTH Inst Comp Sci Computat Vis & Robot Lab Iraklion 70013 Greece

Bundle adjustment constitutes a large, nonlinear least-squares problem that is often solved as the last step of feature-based structure and motion estimation computer vision algorithms to obtain optimal estimates. Due to the very large number of parameters involved, a general purpose least-squares algorithm incurs high computational and memory storage costs when applied to bundle adjustment. Fortunately, the lack of interaction among certain subgroups of parameters results in the corresponding Jacobian being sparse, a fact that can be exploited to achieve considerable computational savings. This article presents sba, a publicly available C/C++ software package for realizing generic bundle adjustment with high efficiency and flexibility regarding parameterization.

关键词： algorithms Design Experimentation performance Unconstrained optimization nonlinear least squares Levenberg-Marquardt sparse Jacobian bundle adjustment structure and motion estimation multiple-view geometry engineering applications

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Genetic adaptive scheme design for high initial gain problems in A L 2-gain state feedback controller

Genetic adaptive scheme design for high initial gain problem...

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2009 IEEE International conference on Control Applications, CCA '09

作者： Hsueh, Yao-Chu Su, Shun-Feng Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781424446025

This paper is a study of a genetic adaptive scheme design for L 2-gain state feedback controllers. It is known that the design of the initial gain producer of the L2-gain state feedback controller (LC) is a difficult problem. The derivative-free optimization, the genetic algorithm, is utilized to resolve the high initial gain problem of LC for a class of nonlinear systems. It is a novel approach for robust control and can be considered as a special application of genetic algorithms. A real-value genetic algorithm with on-line characteristics is designed to search a suitable control gain of LC under auxiliary searching conditions and a specific cost function. The specific cost function is designed under Lyapunov stable theory. Since the system has the L2-gain control properties, then the system states are bounded in an assignable region so that the stability of the initial system is guaranteed. Thus, the system stability of any searched results is guaranteed. Besides, due to the assignable L2-gain attenuation level, the search space of the genetic algorithm is definable. The search target of the genetic algorithm is to find a suitable set of the initial gain so that the system can have required initial control performance. The simulation results indeed demonstrate the effectiveness of the proposed approach. © 2009 IEEE.

关键词： Genetic algorithms

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OPS Laser EPI Design for Different Wavelengths

OPS Laser EPI Design for Different Wavelengths

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conference on Solid State Lasers XVIII - Technology and Devices

作者： Moloney, J. V. Hader, J. Li, H. Kaneda, Y. Wang, T. S. Yarborough, M. Koch, S. W. Stolz, W. Kunert, B. Bueckers, C. Chaterjee, S. Hardesty, G. Nonlinear Control Strategies 3542 N Geronimo Ave Tucson AZ 85705 USA Univ Arizona Coll Opt Sci Tucson AZ 85721 USA Univ Marburg Dept Phys D-35032 Marburg Germany NAsP GmbH D-35041 Marburg Germany Univ Philippines Fac Phys Ctr Mat Sci Marburg Germany

ISBN: (纸本)9780819474391

Design of optimized semiconductor optically-pumped semiconductor lasers (OPSLs) depends on many ingredients starting from the quantum wells, barrier and cladding layers all the way through to the resonant-periodic gain (RPG) and high reflectivity Bragg mirror (DBR) making up the OPSL active mirror. Accurate growth of the individual layers making up the RPG region is critical if performance degradation due to cavity misalignment is to be avoided. optimization of the RPG+DBR structure requires knowledge of the heat generation and heating sinking of the active mirror. nonlinear Control Strategies SimuLase (TM) software, based on rigorous many-body calculations of the semiconductor optical response, allows for quantum well and barrier optimization by correlating low intensity photoluminescence spectra computed for the design, with direct experimentally measured wafer-level edge and surface PL spectra. Consequently, an OPSL device optimization procedure ideally requires a direct iterative interaction between designer and grower. In this article, we discuss the application of the many-body microscopic approach to OPSL devices lasing at 850nm, 1040nm and 2 mu m. The latter device involves and application of the many-body approach to mid-IR OPSLs based on antimonide materials. Finally we will present results on based on structural modifications of the epitaxial structure and/or novel material combinations that offer the potential to extend OPSL technology to new wavelength ranges.

关键词： semiconductor gain photoluminescence spectra recombination losses microscopic theory

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Validation of a Morphogenesis Model of Drosophila Early Development by a Multi-objective Evolutionary optimization Algorithm

Validation of a Morphogenesis Model of <i>Drosophila</i> Ear...

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7th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

作者： Dilao, Rui Muraro, Daniele Nicolau, Miguel Schoenauer, Marc IST Nonlinear Dynam Grp Dept Phys Av Rovisco Pais Lisbon Portugal Univ Paris INRIA LRI Paris France

ISBN: (纸本)9783642011832

We apply evolutionary computation to calibrate the parameters of a morphogenesis model of Drosophila early development. The model aims to describe the establishment of the steady gradients of Bicoid and Caudal proteins along the antero-posterior axis of the embryo of Drosophila. The model equations consist of a system of non-linear parabolic partial differential equations with initial and zero flux boundary conditions. We compare the results of single- and multi-objective variants of the CMA-ES algorithm for the model the calibration with the experimental data. Whereas the multi-objective algorithm computes a full approximation of the Pareto front, repeated runs of the single-objective algorithm give solutions that dominate (in the Pareto sense) the results of the multi-objective approach. We retain as best solutions those found by the latter technique. From the biological point of view, all such solutions are all equally acceptable, and for our test cases, the relative error between the experimental data and validated model solutions on the Pareto front are in the range 3% - 6%. This technique is general and can be used as a generic tool for parameter calibration problems.

关键词： Evolutionary algorithms

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