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检索条件"主题词=Optimization Algorithm"

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A distributed entropy-based QoS multicast routing optimization algorithm for MANET

A distributed entropy-based QoS multicast routing optimizati...

引用

6th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2005)

作者： Gui, C Sun, BL Hubei Univ Econ Dept Comp & Elect Sci Wuhan 430205 Peoples R China

ISBN: (纸本)0769524052

A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task In this paper, we present an entropy-based model to support QoS multicast routing optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations or the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.

关键词： Ad Hoc network QoS multicast routing entropy optimization algorithm

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Mass Ionized Particle optimization algorithm Applied to Optimal FEA-Based Design of Electric Machine

Mass Ionized Particle Optimization Algorithm Applied to Opti...

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20th International Conference on the Computation of Electromagnetic Fields (Compumag)

作者： Han, Wonseok Tran, Trung Tin Kim, Jong-Wook Kim, Yong-Jae Jung, Sang-Yong Sungkyunkwan Univ Sch Elect & Engn Suwon 440746 South Korea Dong A Univ Dept Elect Engn Busan 604714 South Korea Chosun Univ Dept Elect Engn Kwangju 501759 South Korea

A finite-element analysis-based optimal design of an electric machine takes considerable time for its objective evaluation and has many local minima. Thus, selecting an appropriate global convergence optimization with fast convergence speed is necessary in the optimal design of an electric machine. In this paper, a novel global search optimization algorithm, mass ionized particle optimization (MIPO), is newly proposed. The MIPO is the population-based algorithm, which reflects the interactive force between the ionized particles. The global convergence and the convergence speed are validated by comparison with the particle swarm optimization, which have already been proved for its global convergence when applied to a well-known Goldstein-Price function as a benchmark function. In addition, the algorithm has been applied to the optimal design of an interior permanent magnet synchronous machine aiming for its torque ripple reduction.

关键词： Electric machine finite-element analysis (FEA) optimization algorithm population-based algorithm

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An optimization algorithm for Improving Combined Multi-Stage Deep Drawing and Ironing Processes of Axisymmetric Components. Analysis and Experimentation 36

An Optimization Algorithm for Improving Combined Multi-Stage...

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36th International MATADOR Conference

作者： Ramirez, Francisco Javier Domingo, Rosario Sebastian, Miguel Angel Univ Castilla La Mancha Sch Adv Comp Engn Albacete Spain Natl Distance Univ UNED Dept Mfg Engn Madrid Spain

ISBN: (纸本)9781849964319

A new optimization algorithm for combined processes of deep-drawing and ironing has been created in order to improve these types of axisymmetric components manufacturing procedures. The model provides a comprehensive analysis of those phenomena occurring in multi-stage processes of axisymmetric geometry work pieces. The scientific development starts out from works that provide LDR (limiting drawing ratio) solutions based on normal anisotropy value, strain hardering exponent and others parameters which have just been applied to the drawing and redrawing stages so far. The authors extend this work to the ironing stages, and also provide a global and integral scientific solution for the whole process. At the beginning the algorithm provides an initial solution which is afterwards optimized by means of objective functions and constraints. The resolution of the optimization process is carried out by a recursive function that minimizes the total time of the global process. The enhanced solution performs a significant reduction in time and costs of the process. The model allows the modification and correction of certain process variables in order to predict the impact of those that are not fully controllable. The final results are compared using experimental results obtained by the authors, so as to show the reliability of the complete solution.

关键词： optimization algorithm Deep drawing Ironing Limiting drawing ratio Aided system Intelligent manufacturing

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An Improved Snake optimization algorithm and Its Application in Manipulator Trajectory Planning 35

An Improved Snake Optimization Algorithm and Its Application...

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35th Chinese Control and Decision Conference (CCDC)

作者： Li, Wei Zhao, Jiangbo Wang, JunZhen Beijing Inst Technol Sch Automat Beijing Peoples R China

ISBN: (纸本)9798350334722

Manipulator is a kind of widely used mechanical equipment, which has important applications in industry, agriculture, medical and other fields. Manipulator trajectory planning has always been a hot topic in manipulator research. In this paper, an improved snake optimization algorithm is proposed for robot manipulator trajectory planning in complex scenes. Firstly, the mathematical model of trajectory planning problem is constructed and a new cost function with constraint penalty term is proposed. Secondly, the updating mechanism of SO algorithm is improved and a new chaotic local search method is proposed to enhance the search ability and convergence speed of the algorithm. Finally, simulation experiments are carried out in multiple complex environments and compared with traditional algorithms. Experimental results show that ISO algorithm has better performance and stability in trajectory planning.

关键词： snake optimization robot manipulator trajectory planning obstacle avoidance optimization algorithm

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Optimizing Wireless Access Networks towards Power Consumption: Influence of the optimization algorithm 14

Optimizing Wireless Access Networks towards Power Consumptio...

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International Workshop on Parallel optimization using/for Multi and Many-Core High Performance Computing (POMCO) in conjunction with 14th International Conference on High Performance Computing and Simulation (HPCS)

作者： Deruyck, Margot Plets, David Martens, Luc Joseph, Wout Goudos, Sotirios K. Univ Ghent iMinds WAVES Dept Informat Technol Ghent Belgium Aristotle Univ Thessaloniki Dept Phys Thessaloniki Greece

ISBN: (纸本)9781509020881

Nowadays, wireless access networks are already amongst the top power consumers in the ICT (Information and Communication Technology) sector. As it expected that these networks will further expand in the future due to the extreme growth in mobile devices and the high bit rate demand of the applications running on these devices, it is important to consider power consumption as a key parameter in the network design phase. In this paper, two optimization algorithms are proposed: a capacity-based heuristic which aims to reduce power consumption by responding to the instantaneous bit rate demand by the user and an evolutionary opposition-based learning algorithm focusing on the joint-optimization of power consumption and geometrical coverage. Applying both algorithms on a realistic suburban case in Ghent, Belgium, show that both algorithms are able to design an LTE-A network consuming only 24% and 29%, respectively, of the power consumed by the reference scenario which is representative for today's networks. The evolutionary algorithm outperforms the capacity-based algorithm by obtaining a 5% lower power consumption, while the capacity-based heuristic has a 2 to 3% higher coverage. Future research in joint-optimization algorithms of energy and network performance is definitely needed.

关键词： energy efficiency LTE-A network design optimization algorithm power consumption wireless access networks

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Glowworm Swarm optimization algorithm for Solving Numerical Integral

Glowworm Swarm Optimization Algorithm for Solving Numerical ...

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International Conference on Intelligent Computing and Information Science

作者： Yang, Yan Zhou, Yongquan Guangxi Univ Nationalities Coll Math & Comp Sci Nanning 530006 Guangxi Peoples R China

ISBN: (纸本)9783642181283

A new method for solving numerical integration based on artificial glowworm swarm optimization algorithm is presented. The method can not only compute usual definite integral for any functions, but also compute singular integral and oscillatory integral. The simulation results show that the proposed algorithm for solving numerical integration has higher precision.

关键词： glowworm swarm optimization algorithm fitness numerical integration

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ASSIMILATION OF FIELD MEASURED LAI INTO CROP GROWTH MODEL BASED ON SCE-UA optimization algorithm

ASSIMILATION OF FIELD MEASURED LAI INTO CROP GROWTH MODEL BA...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Ren, Jianqiang Yu, Fushui Du, Yunyan Qin, Jun Chen, Zhongxin Minist Agr Key Lab Resources Remote Sensing & Digital Agr Beijing 100081 Peoples R China Chinese Acad Agr Sci Inst Agr Resources & Reg Planning Beijing 100081 Peoples R China Chinese Acad Sci Inst Geog Sci & Natural Resources Res State Key Lab Resources & Environm Informat Syst Beijing 100101 Peoples R China Chinese Acad Sci Inst Tibetan Plateau Res Beijing 100085 Peoples R China

ISBN: (纸本)9781424433940

Assimilating external data into crop growth model to Improve accuracy of crop growth monitoring and yield estimation has been being a research focus in recent years In this paper, the shuffled complex evolution (SCE-UA) global optimization algorithm was used to assimilate field measured LAI into EPIC model to simulate yield, sowing date and nitrogen fertilizer application amount of summer maize in Huanghuaihai Plain in China. The results showed that RMSE between simulated yield and field measured yield of summer maize was 0.84 t ha(-1) and the R-2 was only 0 033 without external data assimilation. While the performances of EPIC model of simulating yield, sowing date and nitrogen fertilizer application amount of summer maize was better through assimilating field measured LAI into the EPIC model. The RMSE of between simulated yield and field measured yield of summer maize was 0.60 t ha(-1) and the R-2 was 0.5301. The relative error between simulated sowing date and real sowing date of summer maize was 2 28% On the simulation of nitrogen fertilizer application rate, the relative error was -6 00% compared with local statistical data These above accuracy could meet the need of crop growth monitoring and yield estimation at regional scale. It proved that assimilating field measured LAI Into crop growth model based on SCE-UA optimization algorithm to monitor crop growth and estimate crop yield was feasible

关键词： Crop growth model EPIC Data assimilation optimization algorithm LAI Yield estimation

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Analysis Of Chaos optimization algorithm Based On Homogenizing Regulator With Chebyshev Mapping 11

Analysis Of Chaos Optimization Algorithm Based On Homogenizi...

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11th International Conference on Intelligent Computation Technology and Automation (ICICTA)

作者： Huang Bin Bao Li-yong Ding Hong-wei Zhao Lei Yunnan Univ Sch Informat Sci & Engn Kunming 650500 Yunnan Peoples R China

ISBN: (纸本)9781538683088

Aimed at the problem of the calculation value tends to distribute at both ends in the traditional chaos optimization algorithm, the paper proposes a method to improve the efficiency of the optimization problem by improving the Chebyshev mapping distribution characteristics through a homogenizing regulator. The homogenization regulator based on the probability density function in this method can improve the ergodic properties of Chebyshev mapping. This paper lists two classical examples to test the optimization algorithm based on homogenization regulator, and compares it with the optimization results based on traditional Tent mapping and Logistic mapping. The test results show that the algorithm significantly reduces the solution step length on the basis of maintaining accuracy. Therefore, this algorithm is feasible and effective in solving optimization problems.

关键词： optimization algorithm Chebyshev mapping Homogenizing regulator optimization algorithm Step length

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Resource optimization algorithm Based on Evaluation Decision mModel of Information Entropy

Resource Optimization Algorithm Based on Evaluation Decision...

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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Huang, Limin He, Guosong Chen, Zhi Hubei Univ Sci & Technol Modern City & Dev Res Inst Coll Resources & Environm Sci Xianning 437100 Peoples R China

ISBN: (纸本)9783038351153

Xianning is located in the fourth pole of economic growth core area of The Central Triangle, through the location entropy analysis method we can know that, tourism industry is an advantaged industry in Xianning and the adjacent region of The Central Triangle, and have their own advantages and characteristics of tourism resources. According to the space constraint issues on function realization of advantaged tourism resources in Xianning, space breakthrough strategy based on The Central Triangle pattern has been presented.

关键词： Information entropy optimization algorithm Resource utilization Function division Weighted objective Radiation

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A Hybrid Particle Swarm optimization algorithm 3

A Hybrid Particle Swarm Optimization Algorithm

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3rd IEEE International Conference on Computer and Communications (ICCC)

作者： Qi Changxing Bi Yiming Han Huihua Li Yong Xian Res Inst High Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9781509063529

Aiming at the the poor local search capability of Particle Swarm optimization(PSO) algorithm, a hybrid particle swarm optimization algorithm is proposed. Firstly, the population is initialized by tent chaotic map to improve the diversity of the initial population. In the evolution process, the tabu search strategy is adopted to improve algorithm convergence rate. Combining the chaos optimization strategy, this algorithm could jump out of local optimization and improve the local search ability. The simulation results of constrained optimization problems are reported and compared with the typical PSO algorithm. Simulation results show that this algorithm could effectively avoid local optimization, have good global search ability and local search ability.

关键词： particle swarm(PSO) optimization algorithm tent chaotic map tabu search strategy

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