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检索条件"主题词=optimization algorithm"

共 3021 条记录，以下是201-210 订阅

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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 on Straight Line Stability Control Strategy of Four Wheel Drive Vehicle Based on the Sliding Mode Variable Structure Control and optimization algorithm

Research on Straight Line Stability Control Strategy of Four...

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Applied Energy Symposium and Summit - Low-Carbon Cities and Urban Energy Systems (CUE)

作者： Wang Zhifu Zhou Yang Li Chaopeng Fang Jun Collaborat Innovat Ctr Elect Vehicles Beijing Beijing 100081 Peoples R China United Automot Elect Syst Co Ltd Pudong New Area 555 Rongqiao St Shanghai 201206 Peoples R China

After the reference of straight line stability control strategy of four-wheel drive vehicle, this paper proposes a control algorithm combining the sliding mode variable structure and optimization control method. The control algorithm is mainly divided into the upper generalized moment calculation based on the sliding mode variable structure controller and the lower torque distribution controller based on the optimization algorithm, also including the slip rates controller based on PID algorithm to ensure the straight line stability control. This paper establishes the combined model based on the CarSim and MATLAB, and tests to verify the validation of the control strategy through the four-wheel drive vehicle test-bed based on RT_LAB. The simulation and experimental results show that when the tire-road friction coefficient is low, the control strategy can not only make the vehicle tire slip rates stay near the optimal slip ratio, at the same time through the yawing moment adjustment, ensure the yaw angle of vehicle not beyond 0.5 deg/s, so the method can effectively ensure the straight line stability of four wheel drive vehicle. (C) 2016 Published by Elsevier Ltd.

关键词： Four-Wheel Drive Vehicle Sliding Mode Variable Structure Control optimization algorithm

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Coyote optimization algorithm-Based PV Planning Strategy for Maximizing Hosting Capacity in A Distribution System

Coyote Optimization Algorithm-Based PV Planning Strategy for...

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IEEE Asia Meeting on Environment and Electrical Engineering (IEEE-AM)

作者： Nguyen Cong Chinh Nguyen Nhat Tung Nguyen Quang Thuan Thuyloi Univ Fac Elect & Elect Engn Hanoi Vietnam

ISBN: (纸本)9798350381061

This paper declares a Coyote optimization algorithm (COA)-based method of determining both optimal PV locations and sizes simultaneously in a distribution system with the largest hosting capacity (HC) of solar photovoltaic (PV) generation and minimizing system voltage deviation. The objective function includes PV hosting capacity (PVHC) and voltage deviation amplitude at each bus. The RMS bus voltage, the maximum size of each PV placement at an installed bus, the total active power losses, and reverse power flow at the substation are constraints to be met. The problem is solved using the Coyote optimization algorithm (COA). The IEEE 123-bus system is applied to test the proposed method. Results are compared with those obtained by other metaheuristic methods, including Genetic algorithm and Particle Swarm optimization. Test results show that the COA method yields exceptional solutions compare to GA and PSO methods in both optimality and convergence.

关键词： PV generation optimization algorithm Hosting capacity Smart inverter Reverse power flow.

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Membrane System-based optimization algorithm for Numeric optimization Problem

Membrane System-based Optimization Algorithm for Numeric Opt...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Liu, Chuang Shen, Wanghui Du, Yingkui Lei, Jiahao Li, Ao Shenyang Univ Sch Informat Engn Shenyang 110044 Liaoning Peoples R China

ISBN: (纸本)9781728124858

In this paper, an optimization algorithm based on membrane system is proposed for numerical optimization problems. In the proposed algorithm, we designed two mechanisms to simulate the movement of molecules in arbitrary direction and a certain direction to balance global exploration and local exploitation. To test the performance of the proposed algorithm, eight benchmark functions were chosen. The simulation results show that the proposed algorithm is more advantageous than other experimental algorithms in solving numerical optimization problems.

关键词： optimization algorithm membrane systems numeric optimization problems

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Stem Cells optimization algorithm

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7th International Conference on Intelligent Computing (ICIC)

作者： Taherdangkoo, Mohammad Yazdi, Mehran Bagheri, Mohammad Hadi Shiraz Univ Fac Elect & Comp Engn Dept Commun & Elect Shiraz Iran Shiraz Univ Med Radiol Med Imaging Res Ctr Shiraz Iran

ISBN: (纸本)9783642245527;9783642245534

optimization algorithms have been proved to be good solutions for many practical applications. They were mainly inspired by natural evolutions. However, they are still faced to some problems such as trapping in local minimums, having low speed of convergence, and also having high order of complexity for implementation. In this paper, we introduce a new optimization algorithm, we called it Stem Cells algorithm (SCA), which is based on behavior of stem cells in reproducing themselves. SCA has high speed of convergence, low level of complexity with easy implementation process. It also avoid the local minimums in an intelligent manner. The comparative results on a series of benchmark functions using the proposed algorithm related to other well-known optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) algorithm, ant colony optimization (ACO) algorithm and artificial bee colony (ABC) algorithm demonstrate the superior performance of the new optimization algorithm.

关键词： optimization algorithm Genetic algorithm (GA) Particle Swarm optimization (PSO) Ant Colony optimization (ACO) Artificial Bee Colony (ABC) algorithm Stem Cells algorithm (SCA)

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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...

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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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An optimization algorithm to Design Compact Plate Heat Exchangers for Waste Heat Recovery Applications in High Power Datacenter Racks 18

An Optimization Algorithm to Design Compact Plate Heat Excha...

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18th IEEE InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm)

作者： Amalfi, Raffaele L. Cataldo, Filippo Thome, John R. Nokia Bell Labs Emerging Mat Components & Devices Lab 600 Mt Ave Murray Hill NJ 07974 USA Provides Metalmeccan Srl Via Piave 82 I-04100 Latina Italy JJ Cooling Innovat Sari Lausanne Switzerland LTCM EPFL Lausanne Switzerland

ISBN: (纸本)9781728124612

Heat dissipations of servers in datacenter racks are following an ever-increasing trend, breaking the economical heat removal limits of traditional air-based cooling technologies. Currently, an average of 40-45% of the total datacenter energy consumption is needed to cool servers, presenting significant challenges to maintain energy efficiencies and also noise levels within US OSHA standards The present paper focuses on the determination of the optimal design of a compact plate heat exchanger (PHE), acting as an overhead refrigerant-to-water condenser of a macro-scale thermosyphon, which dissipates the total heat from a datacenter rack into a cooling loop for waste heat recovery applications (e.g. district heating network). PHEs are already the preferred solution for many industrial and domestic applications (especially small to medium size refrigeration and heat pump systems), since they provide higher heat transfer performance, higher flexibility toward the targeted application and lower pressure drops compared to the conventional tube-in-tube and shell-and-tube heat exchangers. Furthermore, due to the numerous variables involved in the design of PHEs, such as plate number, plate footprint size, geometry of the corrugation pattern (i.e. chevron angle, pressing depth, etc.), an optimization analysis and corresponding simulation tool is auspicious to finding the optimal design of these units to accommodate the targeted heat rates of datacenter racks. Hence, this study proposes a novel optimization process which incorporates a local simulator (an improved version compared to the one presented at ITHERM 2018) for accurately rating and designing PHEs over a wide range of operating conditions, plate geometries and working fluids. The improved simulator uses a local one-dimensional effectiveness-NTU approach, with a local implementation of mass, momentum and energy equations, coupled with newly upgraded methods for condensation heat transfer coefficients and frictional p

关键词： Condenser datacenter rack optimization algorithm performance analysis plate heat exchanger two-phase flow

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Development of a Reinforcement Learning Inspired Monte Carlo Tree Search Design optimization algorithm for Fixed-Wing VTOL UAV Propellers

Development of a Reinforcement Learning Inspired Monte Carlo...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Thiele, Moritz Staudenmaiert, Adrian Venkata, Swapan Madabhushi Hornung, Mirko Tech Univ Munich D-80333 Munich Germany Inst Aircraft Design Boltzmannstr 15 D-85748 Garching Germany

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

A novel Monte Carlo Tree Search optimization algorithm that is trained using a Reinforcement Learning approach is developed for the application to geometric design tasks. It is capable of evaluating design parameters and demonstrates the successful application of reinforcement learning strategies on a physics informed design optimization task. The algorithm is intended to be used for the parametric design of the optimal geometry of a propeller for Fixed-Wing VTOL UAV but is also applied to an aircraft design problem with ease.

关键词： optimization algorithm Reinforcement Learning Fixed Pitch Propellers Aircraft Design Value Function Particle Swarm optimization Genetic algorithm Robots Maximum Takeoff Weight Propulsive Efficiency

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Optimal Placement and Sizing of DER's with Load Models using a Modified Teaching Learning based optimization algorithm

Optimal Placement and Sizing of DER's with Load Models using...

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International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE)

作者： Yammani, Chandrasekhar Sowjanya, G. Maheswarapu, Sydulu Matam, Sailaja Kumari

ISBN: (纸本)9781479949816

In this paper, a method which employs Modified Teaching-Learning Based optimization (MTLBO) algorithm is proposed to determine the optimal placement and size of Distributed Energy Resources (DERs) units in distribution systems. DERs are commonly connected near the load in electric power distribution systems and include renewable energy sources such as wind and solar, fossil-fuel-based generation such as micro turbines, and other distributed energy storage elements. Loss minimization and voltage profile improvement as objective function and for every combination of DERs, impact indices, active and reactive losses and voltage profiles is studied on different load models. For all cases current injection distribution load flow method is used and tested on 84-bus Taiwan Power Company distribution system using MTLBO algorithm.

关键词： Distributed Energy Resource (DER) Load models Loss minimization optimization algorithm MTLBO algorithm

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AOAB - Automated optimization algorithm Benchmarking 10

AOAB - Automated Optimization Algorithm Benchmarking

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12th Annual Genetic and Evolutionary Computation Conference (GECCO)

作者： Weise, Thomas Niu, Li Tang, Ke Univ Sci & Technol China Nat Inspired Computat & Applicat Lab Hefei 230027 Anhui Peoples R China

ISBN: (纸本)9781450300735

In this paper we present AOAB, the Automated optimization algorithm Benchmarking system. AOAB can be used to automatically conduct experiments with numerical optimization algorithms by applying them to different benchmarks with different parameter settings. Based on the results, AOAB can automatically perform comparisons between different algorithms and settings. It can aid the researcher to identify trends for good parameter settings and to find which algorithms are suitable for which type of problem. We introduce the system structure of AOAB (the server and the graphical client interface), define the way in which optimizers and benchmark functions can be implemented for the use in AOAB, and conduct an illustrative example experiment with our system: a comparison between Random Search and two Hill Climbers.

关键词： AOAB Automated Benchmarking optimization algorithm Distribution Single-Objective optimization Numerical optimization

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