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Enhancement of Radiograph Images Based on Chaos optimization

Enhancement of Radiograph Images Based on Chaos Optimization

引用

international workshop on Intelligent Systems and applications, ISA

作者： Yinjie Sun College of computer and information technology Henan normal university Xinxiang China

How to select the parameters of high-frequency emphasis filtering (HFEF) in order to enhance radiograph images, this paper presents an enhancing method based on chaos optimization algorithms (COA). Based on the properties of ergodicity, stochastic property and regularity of chaos, the chaos optimization method can get global solution with low computational load. Firstly, an X-ray image is sharpened with HFEF, at the same time, the controllable and improved COA can optimize the parameters so that the optimal clarity of the image may be got, then the contrast of it is enhanced with histogram equalization to visually enhance the medical radiograph images to solve the questions: blurring and dark nature, which radiograph images generally tend to have. Experimental results show the proposed approach is effective and gets competitive visual effects.

关键词： Radiography Chaos optimization methods Filtering algorithms Stochastic processes X-ray imaging Optimal control Radio control Histograms Biomedical imaging

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A Simple and Fast Particle Swarm optimization and Its Application on Portfolio Selection

A Simple and Fast Particle Swarm Optimization and Its Applic...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Wenjun Wang Hui Wang Zhijian Wu Hubei Dai Department of Management Engineering Nanchang Institute of Technology Nanchang China State Key Laboratory of Software Engineering Wuhan University of China Wuhan China

Particle Swarm optimization (PSO) has shown its good performance on well-known numerical function problems. However, on some multimodal functions the PSO easily suffers from premature convergence because of the rapid decline in diversity. Some diversity-guided PSO algorithms have proposed to maintain diversity, while these techniques cost much computation time on the calculation of diversity. In this paper, a simple and fast PSO (hybrid PSO, HPSO) is proposed, which indirectly maintains the diversity of swarm but not compute it. Experimental studies on 8 well-known benchmark functions and a portfolio selection optimization problem show that the HPSO does not only obtain better performance than the standard PSO and other two diversity-guided PSO algorithms, but almost cost the same computation time with the standard PSO.

关键词： Particle swarm optimization Portfolios Convergence Evolutionary computation Computational efficiency Switches Cost function Genetic algorithms Simulated annealing

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Design for Multi-Machine Power System Damping Controller Based on Particle Swarm optimization

Design for Multi-Machine Power System Damping Controller Bas...

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international workshop on Intelligent Systems and applications, ISA

作者： Zhiyuan Duan Chengxue Zhang Zhijian Hu Fangjie Wu School of Electrical Engineering Wuhan University of China Wuhan Hubei China

This paper provides an algorithm based on the microhabitat theory and particle swarm for the problem of wide area controller parameters optimization. The method cans optimal parameters. According to multi-objects model of the problem, and reduce the difficulties and works in design for multi-machine power system damping controller. In the end of paper, a typical four-generator two-area testing system indicates that wide-area damping controller has a strong capability of damping area oscillation. The result showed that the algorithm validity and feasibility.

关键词： Power systems Damping Power system control Control systems Particle swarm optimization Power system dynamics Clustering algorithms Wide area measurements Power system measurements Iterative algorithms

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Research on an Improved Evolution Algorithm and its Application in Function optimization Problem

Research on an Improved Evolution Algorithm and its Applicat...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Juan Li Jingfeng Yan Guanghui Zhai Coll. of Comput. Sci. & Technol. Xuchang Univ. Xuchang

An improved evolution algorithm (IEA) is proposed in this paper. It has some new features: 1) using multi-parent search strategy and stochastic ranking strategy and a simple diversity rules to maintain the diversity of the population; 2) using a hybrid self-adaptive crossover-mutation operator, which can enhance the search ability and exploit the optimum offspring; The algorithm of this paper is tested on 13 benchmark optimization problems with linear or/and nonlinear constraints and compared with other evolutionary algorithms. The experimental results demonstrate that the performance of IEA outperforms other evolutionary algorithms in terms of the quality of the final solution and the stability; and its computational cost is lower than the cost required by the other techniques compared.

关键词： Constraint optimization Evolutionary computation Evolution (biology) Stochastic processes Benchmark testing Genetic programming Educational institutions Computer science Application software Automatic testing

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An SFL-Based Multicast Routing optimization Algorithm

An SFL-Based Multicast Routing Optimization Algorithm

引用

international workshop on Intelligent Systems and applications, ISA

作者： Xia Sun Ziqiang Wang School of Information Science and Engineering Henan University of Technology Zhengzhou China

The problem of computing the bandwidth-delay-constrained least-cost QoS multicast routing is a NP-complete problem. A novel shuffled frog leaping (SFL) algorithm is proposed to deal with the Qos multicast routing problem effectively and efficiently in this paper. The experimental results show that the proposed algorithm can find optimal solution quickly and has a good scalability.

关键词： Routing Multicast algorithms Quality of service Streaming media Application software Costs Delay Information science Scalability Particle swarm optimization

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The optimization Estimation of the Yield Per Area Based on Intelligent Computing

The Optimization Estimation of the Yield Per Area Based on I...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Chang-Jian Deng Department of Control Engineering Chengdu University of Information and Technology Chengdu Sichuan China

Estimation of the yield per area is useful to increase farmer's *** the paper, models of the yield per area based on special 0-1 knapsack problem and multidimensional knapsack problem are *** order to slove the problem based on these models, genetic algorithm and ant colony algorithm are designed in the paper. And a special coding graph is designed to slove the knapsack *** results of simulation are presented in the *** proves that the model of special 0-1 knapsack problem can slove the problem of optimization estimation of the yield per area based on intelligent computing.

关键词： Yield estimation Multidimensional systems Genetic algorithms Numerical models Production Design optimization Algorithm design and analysis Computational modeling optimization methods Control engineering

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Parachute Decelerate Trajectory optimization Design Based on Genetic Algorithm

Parachute Decelerate Trajectory Optimization Design Based on...

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international workshop on Intelligent Systems and applications, ISA

作者： Zhu Yong Liu Li School of Aerospace Science and Engineering Beijing Institute of Technology Beijing China

In this paper, the optimal parachute decelerating trajectory of mini-UAVs is studied. The mini-UAV trajectory model of parachute decelerating segment is established. The influences to parachute drag are analyzed and the parachute canopy limit area formula is derived. In order to ensure the time effectiveness of mini-UAVs entering working destination, taking flight time and range as the performance function, considering end velocity and end height as optimization constraints, and choosing parachute parameters-canopy area and parachute opening time as design variables, the optimal decelerating trajectory is solved by sequential quadratic programming method and genetic algorithm. Compared the results of these two kinds of optimized algorithms, their applicability to this decelerating trajectory is analyzed. The mechanism of timeliness during parachute decelerating trajectory is analyzed briefly. A numerical example results indicates the validity of the parachute decelerating trajectory design in this paper, which possesses practical value to guide research of parachute design.

关键词： Design optimization Algorithm design and analysis Genetic algorithms Drag Unmanned aerial vehicles optimization methods Quadratic programming Aircraft Shape Aerodynamics

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An Adaptive Clonal Selection Algorithm and Its applications

An Adaptive Clonal Selection Algorithm and Its Applications

引用

international workshop on Intelligent Systems and applications, ISA

作者： Guangzhou Chen Jiaquan Wang Shuheng Hu Department of Environmental Engineering Anhui University of Architecture Hefei China School of Resources and Environmental Engineering Hefei University of Technology Hefei China

Based on the principle of clonal selection, an improved adaptive immune clonal selection algorithm is put forwarded by using real-coded method, where adaptive mutation operator is used according to the changes of function value and mutation coefficient decays with the iteration. In addition, the strategy of mutation by section is used according to the iteration. To test its efficiency, optimization computing is conducted for five typical test functions. Subsequently, a complex nonlinear optimization model is solved based on the algorithm. The results show the validity of this algorithm to solve the above problems.

关键词： Genetic mutations Immune system Testing Cloning Biological system modeling Pursuit algorithms Encoding Maintenance engineering Biology computing optimization methods

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An Improved Multi-Objective Genetic Algorithm Based On Pareto Front and Fixed Point Theory

An Improved Multi-Objective Genetic Algorithm Based On Paret...

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international workshop on Intelligent Systems and applications, ISA

作者： Jingjun Zhang Yanmin Shang Ruizhen Gao Yuzhen Dong Department of Science Research Hebei University of Engineering Handan China

For multi-objective optimization problems, an improved multi-objective genetic algorithm based on Pareto Front and Fixed Point Theory is proposed in this paper. In this Algorithm, the fixed point theory is introduced to multi-objective optimization questions and K 1 triangulation is carried on to solutions for the weighting function constructed by all sub- functions, so the optimal problems are transferred to fixed point problems. The non-dominated-set is constructed by the method of exclusion. The experimental results show that this improved genetic algorithm convergent faster and is able to achieve a broader distribution of the Pareto optimal solution.

关键词： Genetic algorithms Pareto optimization Genetic engineering optimization methods Genetic mutations Constraint optimization Constraint theory Concurrent computing Robustness Parallel processing

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Performance analysis and cross layer optimization for multimedia streaming over wireless networks

Performance analysis and cross layer optimization for multim...

引用

6th international ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2009 and 3rd international workshop on Advanced Architectures and algorithms for Internet Delivery and applications, AAA-IDEA 2009

作者： Ao, Antonio Wu, Zhung-Han Yeh, Ping-Cheng Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)3642106242

Multimedia data are sensitive to delay which deteriorates the video quality and the perception of the viewer. Due to the sensitivity to the delay, transmitting multimedia data over inherently variant wireless channels is a big challenge. Although wireless systems have employed adaptive modulation and coding (AMC) to combat the variation of the environment, the possible delay in the buffers still has impacts on the video quality. In this paper, the focus is on the performance of wireless multimedia streaming using AMC. In particular, the video frame error rate and the resulting GOP distortion for video streaming is analyzed. It is observed that the video quality depends on the target packet error rate of the AMC, which also determines the SNR thresholds of AMC. Through our analysis, the optimal target PER of AMC and the resulting SNR thresholds can be obtained to achieve the optimal video quality that minimizes the GOP distortion. © Institute for Computer Science, Social-Informatics and Telecommunications Engineering 2009.

关键词： Quality control

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