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检索条件"主题词=Optimization algorithm"

共 3114 条记录，以下是181-190 订阅

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A Novel Energy-Minimized optimization algorithm for Mobile Image Transmission

A Novel Energy-Minimized Optimization Algorithm for Mobile I...

引用

11th Pacific Rim Conference on Multimedia

作者： Tang, Zhenhua Qin, Tuanfa Liu, Wenyu Guangxi Univ Sch Comp Elect & Informat Nanning 530004 Peoples R China Huazhong Univ Sci & Technol Elect & Informat Engn Dept Wuhan 430074 Peoples R China

ISBN: (纸本)9783642156953

In this paper, we propose a novel energy-minimized optimization algorithm for image coding and transmission over wireless channel. In order to reduce computational complexity of reaching optimal solutions, the presented algorithm makes full use of the intrinsic relations among the system parameters, optimization objective, and system constraints. We present simulation results to demonstrate that the proposed optimization algorithm is effective and it has much lower computational complexity than the conventional sequential quadratic programming (SQP) method. And the proposed algorithm is suitable for mobile image transmission applications.

关键词： Energy consumption image transmission optimization algorithm

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Landing performance optimization algorithm of civil aircrafts

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2nd International Conference on Civil Engineering and Transportation (ICCET 2012)

作者： Chen, Hongying Luo, Wentian Civil Aviat Flight Univ China Flight Technol Coll Guanghan City Si Chuan Peoples R China

ISBN: (纸本)9783037855645

This paper explains and demonstrates how to calculate and optimize landing performance. According regulation requirement, it needs to consider the different requirements [1], including landing field length, missed approach climb gradient, brake energy and tire speed. Weights limited by the different requirements are calculated, the minimum of these weights limited are determined as the actual allowed maximum landing weight.

关键词： Landing performance optimization algorithm Operating landing distance Landing speed Landing weight

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Determination of tracking errors with respect to the geometrical errors based on optimization algorithm

Determination of tracking errors with respect to the geometr...

引用

International Conference of the SolarPACES

作者： Sun, Feihu Wang, Zhifeng Guo, Minghuan Bai, Fengwu Xu, Zijian Chinese Acad Sci Inst Elect Engn Key Lab Solar Thermal Energy & Photovolta Syst Zhongguancun Haidian Dis 100190 Peoples R China

Accurate dual-axis sun tracking is the key feature of a heliostat and is critical for the performance of a solar tower power plant. The primary tracking errors with respect to the geometrical errors could be theoretically determined from the measurements of the BCS based on optimization algorithm. Tests are performed on two heliostats in DAHAN solar tower plant and analyses are performed to evaluate the comprehensive effect of the six angular geometrical errors on the heliostat tracking accuracy. The test results show that the altitude-azimuth tracking angle formulas for several fixed geometrical errors work well and have a effectiveness for a given period of time. (C) 2013 Zhifeng Wang. Published by Elsevier Ltd.

关键词： BCS tracking angle geometrical errors optimization algorithm

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A Novel optimization algorithm: The Forest algorithm 5

A Novel Optimization Algorithm: The Forest Algorithm

引用

5th International Conference on Intelligent Systems Design and Engineering Applications (ISDEA)

作者： Wu, Qi Chengdu Med Coll Chengdu 610500 Sichuan Peoples R China

ISBN: (纸本)9781479942626

A new optimization algorithm, namely the Forest algorithm (FA), is introduced for the first time. This algorithm simulates trees' growth, reproduction and death in a forest to perform optimization. In the algorithm, trees and branches represent a collection of trial solutions and parameters needed to be optimized respectively, and three mechanisms, i.e. growth, proliferation and death, are employed for improving trees' vitality, which is a factor defined to evaluate the fitness of trial solutions. This algorithm in general execute a global optimization by operating on a group of trial solutions in parallel, but its growth mechanism, which adopts a parameter sweeping method, is a local optimization, so it combines the ability to find global optima of the global optimization and the fast convergence of the local optimization. Several numerical experiments are conducted, in which the performance of the FA in terms of the global optimization capability, accuracy and efficiency is evaluated and compared to that of some widely-used global optimization algorithms such as the Genetic algorithm (GA) and the Particle Swarm optimization (PSO). Results shown the FA is able to perform global optimization effectively and with high accuracy.

关键词： optimization algorithm Forest algorithm global optimization

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An Improved Animal Migration optimization algorithm Based on Interactive Learning Behavior for High Dimensional optimization Problem

An Improved Animal Migration Optimization Algorithm Based on...

引用

International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS)

作者： Lai, Zhaolin Feng, Xiang Yu, Huiqun East China Univ Sci & Technol Dept Comp Sci & Engn Shanghai Peoples R China

ISBN: (纸本)9781728104669

Animal migration optimization(AMO) algorithm inspired by the behavior of animal migration is proposed recently. AMO shows good performance on the benchmark functions whose dimensionality is no more than 30. However, the performance of AMO is degraded rapidly when the dimensionality is larger than 30. In order to overcome this shortcoming, an improved animal migration algorithm (IAMO) based on interactive learning behavior is proposed in this paper. First, we introduce an interactive learning behavior that individuals will learn from each other by exchanging information. During the search process, the search step is dynamically adjusted. In this case, the intelligence of IAMO is higher than AMO. Second, a refined search method is used to search around the current solutions, and this method can enhance the search ability of the algorithm. Third, a birth-and-death mechanism is designed to avoid local optimum. The effectiveness of IAMO is verified on 100 dimensional benchmark functions, and the empirical results show that the performance of IAMO is promising.

关键词： optimization algorithm migration interactive learning birth-and-death mechanism high dimension

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Detection and parameter estimation of R peaks in ECG signal using optimization algorithm 6

Detection and parameter estimation of R peaks in ECG signal ...

引用

6th International Symposium on Computing and Networking (CANDAR) - Across Practical Development and Theoretical Research

作者： Hsieh, Sheng-Ta Lin, Chun-Ling Oriental Inst Technol Dept Commun Engn New Taipei Taiwan Ming Chi Univ Technol Dept Elect Engn New Taipei Taiwan

ISBN: (纸本)9781538691847

Accurate R-peak detection is very important for arrhythmia diagnosis. Our previous effective R detection algorithm consisted of three strategies: band-pass filter, adaptive definition of interesting block and dynamic threshold. Then, it adopted the optimization algorithm to replace the knowledge-based theory and found out the suitable parameters (El, F2, N, WI, W2, beta and mu) in R detection algorithm quickly and obtained the high performance of detecting R peaks (99.77%). In order to improve the performance of the previous study, this study proposes to add the median filter in the algorithm to correct baseline wander components of electrocardiography (ECG) signals. It is necessary to defined two parameters (Ti and T2) in median filter. Therefore, this study adopts particle swarm optimization (PSO) to find the suitable parameters (Ti, T2, F1, F2, N, W1, W2, beta and mu) in the proposed method. The proposed method is applied to MIT-BIH arrhythmia database. The results show that PSO can find out the suitable parameters in R detection algorithm and have a higher accuracy (99.95%) than one of the previous study.

关键词： R-peak detection arrhythmia diagnosis optimization algorithm knowledge-based theory electrocardiography (ECG) particle swarm optimization (PSO) MIT-BIH arrhythmia database

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A Metaheuristic optimization algorithm for Flight Assignment to the North Atlantic Organized Track System

A Metaheuristic Optimization Algorithm for Flight Assignment...

引用

AIAA Aviation Forum and Exposition

作者： Izadi, Arman Trani, Antonio A. Virginia Polytech Inst & State Univ Dept Civil & Environm Engn 200 Patton Hall Blacksburg VA 24061 USA Virginia Polytech Inst & State Univ Dept Civil & Environm Engn 200 Patton Hall Blacksburg VA 24061 USA

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

The North Atlantic region is the busiest oceanic airspace controlled by the United States. To better serve the two traffic flows between Europe and North America, two Organized Track Systems (OTS) are created on a daily basis to accommodate oceanic flights. This paper studies the potential benefits of a novel method for assigning flights to the OTS in the North Atlantic airspace. A mathematical model for the group assignment procedure is provided in this study, and a metaheuristic optimization algorithm is proposed for the solution methodology. The proposed algorithm is validated with a small size problem verifying it can find the global optimal in reasonable computational time. The validated optimization algorithm is implemented inside a fast-time flight simulation tool, called Global Oceanic Model. This study used the real-scale flight traffic related to three consecutive days in June 2016. The simulation results show the operational benefits of the proposed assignment procedure in terms of efficiency, level of service, and airline equity.

关键词： optimization algorithm North Atlantic Airspace Mathematical Models Flight Simulation Flight Level Controller Pilot Data Link Communications Mach Numbers Fuel Consumption Annealing Process Air Navigation Service Provider

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A Mixed Integer Efficient Global optimization algorithm with Multiple Infill Strategy - Applied to a Wing Topology optimization Problem

A Mixed Integer Efficient Global Optimization Algorithm with...

引用

AIAA Science and Technology (SciTech) Forum and Exposition

作者： Roy, Satadru Crossley, William A. Stanford, Bret K. Moore, Kenneth T. Gray, Justin S. Purdue Univ Aeronaut & Astronaut 701 W Stadium Ave W Lafayette IN 47907 USA NASA Langley Res Ctr Aeroelastic Branch 218 Dodd Blvd Hampton VA 23681 USA DB Consulting Grp Inc Cleveland OH 44135 USA NASA Glenn Res Ctr Cleveland OH 44135 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

With the advancement in high performance computing and numerical optimization techniques, engineering design optimization problems are becoming more complex, larger scale, higher fidelity, and computationally more demanding, requiring longer run times than ever before. There exists methodologies and techniques that can address some of these challenges but very few can address all, and most are limited in the extent that these concerns can be addressed. With the goal of addressing such challenging engineering problems, we developed a new optimization algorithm, named AMIEGO, that combines concepts from surrogate-based optimization approaches, gradient-based numerical methods, Partial Least Squares, evolutionary algorithms, and Branch-and-Bound, providing newer capabilities that were not previously perceived. The effort here builds upon this previously developed optimization algorithm to include multiple infill sampling capability that combines the concept of generalized expected improvement function, unsupervised learning, and multi-objective evolutionary technique. To demonstrate, AMIEGO with the multiple infill capability (called AMIEGO-MIMOS) solves a series of increasingly difficult engineering design optimization problems. The results reveal the performance of the new approach is problem dependent. When applied to a ten-bar truss problem, the newly proposed multiple infill strategy consistently leads to a better design solutions when compared to the existing CPTV method (implemented with the context of the AMIEGO algorithm). On the other hand, when applied to a mixed-integer high fidelity wing topology optimization problem - MIMOS, despite showing a steeper convergence at the start, eventually leads to an inferior solution as compared to CPTV approach. These results also reveal that a small number of starting points, in general, are sufficient to lead to a good overall solution.

关键词： optimization algorithm Numerical optimization Trusses Multi Objective Evolutionary algorithms High Performance Computing Surrogate Model Wingbox Kernel Functions Parallel Computing Aspect Ratio

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A new swarm intelligent optimization algorithm: Pigeon Colony algorithm (PCA)

A new swarm intelligent optimization algorithm: Pigeon Colon...

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7th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII)

作者： Yi, Ting-Hua Wen, Kai-Fang Li, Hong-Nan Dalian Univ Technol Sch Civil Engn Dalian 116023 Peoples R China Shenyang Jianzhu Univ Sch Civil Engn Shenyang 110168 Peoples R China

In this paper, a new Pigeon Colony algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution;the flying process is designed to search for the local and global optimum and improve the global worst solution;and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.

关键词： optimization algorithm Pigeon Colony algorithm low-dimensional function high-dimensional function nonlinear equation

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Research and Application of optimization algorithm Based on Two-stage in Distribution Routing Planning

Research and Application of Optimization Algorithm Based on ...

引用

IEEE International Conference on Automation and Logistics

作者： He, Minai Zhu, Menggao Univ Shandong Jiaotong Dept Transporationt & Logist Engn Jinan Shandong Peoples R China Wuhan Univ Technol Transportat Sch Wuhan Peoples R China

ISBN: (纸本)9781424425020

In this paper, author comes up with a new optimization algorithm about distribution routing planning. This method is used to make the best distribution route according to vehicle's load capacity, distance from distribution centre and various client demand as well as cargo priority etc. The result could be displayed in electronic map. Proved by instances, this method can help managers to reduce the cost of distribution and make decisions for transportation control.

关键词： Distribution VRP optimization algorithm Logistics Informationization

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