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Chinese Intelligent Automation Conference (CIAC)

作者： Wu, Xiuyu Xing, Guoping Chen, Yongren Wu, Lijie Aviat Univ Air Force PLA Dept Aviat Lifesaving 7855 Renmin St Changchun 130022 Peoples R China Aviat Univ Air Force PLA Changchun 130022 Peoples R China Chengde Petr Coll Dept Foreign Language & Traveling Chengde 067000 Peoples R China

ISBN: (纸本)9783642385247;9783642385230

Based on the theoretic study of location of general facilities, this paper makes an attempt to optimize the typical discrete element of the location of aviation rescue base through discrete binary particle swarm (PSO) algorithm in order to find out an optimized location method with more simplified calculation and more optimized result, which will finally provide a solid theoretical foundation for the location of aviation rescue base.

关键词： Aviation rescue base Location model particle swarm optimization algorithm

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Hybrid Bat & particle swarm algorithm for optimization of labyrinth spillway based on half & quarter round crest shapes

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FLOW MEASUREMENT AND INSTRUMENTATION 2019年 66卷 209-217页

作者： Ferdowsi, Ahmad Farzin, Saeed Mousavi, Sayed-Farhad Karami, Hojat Semnan Univ Fac Civil Engn Dept Water Engn & Hydraul Struct Semnan Iran

optimization is an interesting method that finds the optimal response (i.e., objective function) by searching the decision variables in the search space. The present study deals with the optimal design of a labyrinth spillway (LS) having half-round or quarter-round crest shape. For optimal the design of the spillway geometry, an evolutionary Hybrid algorithm (HA) of Bat algorithm (BA) and particle swarm optimization (PSO) algorithm was developed. By this procedure, the worst responses of one algorithm are replaced by the best responses of the other algorithm. This HA does not get trapped in local minima and has high convergence rate concerning the optimal absolute response. Results of using HA showed that LS with half-round crest requires less concrete, compared to quarter-round crest. Moreover, the discharge capacity for LS with half-round crest was more than the quarter-round crest. The HA significantly reduced the computational time for the optimal design of LS with half-round or quarter-round crest, as compared to BA or PSO.

关键词： optimization Labyrinth spillway Crest shape Hybrid algorithm Bat algorithm particle swarm optimization algorithm

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An Assimilated Approach of Concept Analysis and particle swarm optimization algorithm for Effective Test Suite Minimization

An Assimilated Approach of Concept Analysis and Particle Swa...

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IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)

作者： Selvakumar, S. Manikumar, T. Kumar, A. John Sanjeev Latha, L. GKM Coll Engn Technol Dept Comp Sci & Engn Madras Tamil Nadu India RVS Coll Engn Technol Dept Comp Applicat Dindigul India Thiagarajar Coll Engn Dept Comp Applicat Madurai 625015 Tamil Nadu India Bharathiar Univ Dept Comp Sci Ctr Res & Dev Coimbatore Tamil Nadu India

ISBN: (纸本)9781479915941;9781479915958

In most of the test suite minimization techniques, either the size minimization is more or the fault detection is more. But a combination of both would yield better qualified reduced test suite. This paper presents a technique where the size minimization is obtained through the optimization algorithm, particle swarm optimization and the Fault Detection Effectiveness is obtained through Concept Analysis. In spite of our algorithm producing results similar to Genetic algorithm, the computation time of our algorithm is simple and improves the fault detection capacity. The experimental results indicate that PSO outperforms GAs for most code elements to be covered in terms of effectiveness and efficiency.

关键词： Test suite minimization concept analysis particle swarm optimization algorithm Empirical analysis

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Dynamic particle swarm optimization algorithm based Maximum Power Point Tracking of Solar Photovoltaic Panels

Dynamic Particle Swarm Optimization Algorithm based Maximum ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Huynh, Duy C. Nguyen, Thoai N. Dunnigan, Matthew W. Mueller, Markus A. Vietnam Natl Univ Univ Technol Power Syst Dept Ho Chi Minh City Vietnam

ISBN: (纸本)9781467351942;9781467351928

This paper proposes a novel application of a dynamic particle swarm optimization (PSO) algorithm for determining a maximum power point (MPP) of a solar photovoltaic (PV) panel. Solar PV cells have a non-linear V-I characteristic with a distinct MPP which depends on environmental factors such as temperature and irradiation. In order to continuously harvest maximum power from the solar PV panel, it always has to be operated at its MPP. The proposed dynamic PSO algorithm is one of the PSO algorithm variants, which modifies the acceleration coefficients of the cognitive and social components in the velocity update equation of the PSO algorithm as linear time-varying parameters to improve the global search capability of particles in the early stage of the optimization process and direct the global optima at the end stage. The obtained simulation results are compared with MPPs achieved using other algorithms such as the standard PSO, and Perturbation and Observation (P&O) algorithms under various atmospheric conditions. The results show that the dynamic PSO algorithm is better than the standard PSO and P&O algorithms for determining and tracking MPPs of solar PV panels.

关键词： solar photovoltaic panel maximum power point tracking particle swarm optimization algorithm

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Multi-objective Optimal Sizing Hybrid Power System in a Solar Electric Vehicle Using particle swarm optimization algorithm

Multi-objective Optimal Sizing Hybrid Power System in a Sola...

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4th International Conference on Manufacturing Science and Engineering (ICMSE 2013)

作者： Zhou Shiqiong Guo Guifang Xiang Yongyang Shenzhen Inst Informat Technol Dept Traff & Environm Shenzhen Peoples R China Tibet Univ Int Informat Engn Dept Tibet Peoples R China

ISBN: (纸本)9783037856932

In a solar electric vehicle, the optimal sizing of hybrid power system can be considered as a multi-objective optimization problem. The two conflicting goals are to maximize the Loss of Peak Power Probability (LPPP) and minimize the system cost. And the former is related to the reliability of the system while the latter relates to whether production prototype so the two optimization objectives are important. An improved particle swarm algorithm was presented to optimal size the hybrid power system. Here the mutation operator of genetic algorithm was introduced and the acceleration factor could change with time. The optimization results show that: the improved particle swarm algorithm can well solve the hybrid power system for multi-objective optimization problems.

关键词： Multi-objective optimal sizing Hybrid power particle swarm optimization algorithm Solar electric vehicle (SEV)

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Performance Evaluation of particle swarm optimization algorithm for Optimal Design of Belt Pulley System

Performance Evaluation of Particle Swarm Optimization Algori...

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4th International Conference on swarm, Evolutionary, and Memetic Computing (SEMCCO)

作者： Sabarinath, Pandurengan Thansekhar, M. R. Saravanan, R. KLN Coll Engn Pottapalayam 630611 India JCT Coll Engn & Technol Coimbatore Tamil Nadu India

ISBN: (纸本)9783319037530;9783319037523

The present scenario in the design of machine elements includes the minimization of weight of the individual components in order to reduce the overall weight of the machine elements. It saves both cost and energy involved. Belts are used to transmit power from one shaft to another by means of pulleys which rotate at the same speed or different speeds. Generally, the weight of pulley acts on the shaft and bearings. In the present study, minimization of weight of a belt pulley system has been investigated. particle swarm optimization algorithm (PSO) is used to solve the above mentioned problem subjected to a set of practical constraints and it is compared with the results obtained by Differential Evolution algorithm (DEA). Our results indicate that PSO approach handles our problem efficiently in terms of precision and convergence and it outperforms the results presented in the literature.

关键词： Optimal Design Belt pulley system particle swarm optimization algorithm

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An effective particle swarm optimization algorithm for flexible job-shop scheduling problem

An effective particle swarm optimization algorithm for flexi...

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5th International Conference on Industrial Engineering and Systems Management (IEEE IESM)

作者： Nouiri, Maroua Jemai, Abderezak Ammari, Ahmed Chiheb Bekrar, Abdelghani Niar, Smail Carthage Univ INSAT Inst MMA Lab Tunis Tunisia King Abdulaziz Univ Fac Engn Jeddah 21413 Saudi Arabia Univ Lille Nord France F-59000 Lille France UVHC TEMPO Lab PSI Team F-59313 Valenciennes France UVHC LAMIH Lab DIM Team F-59313 Valenciennes France

ISBN: (纸本)9782960053241

Flexible job-shop scheduling problem (FJSP) is very important in many research fields such as production management and combinatorial optimization. The FJSP problems cover two difficulties namely machine assignment problem and operation sequencing problem. In this paper, we apply particle swarm optimization (PSO) algorithm to solve this FJSP problem aiming to minimize the maximum completion time criterion. Various benchmark data taken from literature, varying from Partiel FJSP and Total FJSP, are tested. Computational results proved that the PSO developed is enough effective and efficient to solve flexible job-shop scheduling problem.

关键词： flexible job-shop scheduling problem makespan particle swarm optimization algorithm routing and scheduling

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Research on Electronic Materials with Design of a down-conversion mixer Based on particle swarm optimization algorithm

Research on Electronic Materials with Design of a down-conve...

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2nd International Conference on Function Materials and Nanotechnology (FMN 2013)

作者： Shan, Huilin Zhang, Yinsheng Nanjing Univ Informat Sci & Technol Nanjing 210044 Jiangsu Peoples R China

ISBN: (纸本)9783037858059

This paper presents principles of a down-converted mixer for four sub-harmonic and proposes a particle swarm optimization algorithm as a global search algorithm, and the performance equation is used as the assessment of the mixer circuit optimization method. Dielectric substrate adopts Electronic Materials with RF/Duroid 5880 whose dielectric constant is 2.20 and 5mil in thickness. The optimization algorithm can quickly get optimal results. The simulation results show that this mixer achieves higher 1 dB compression point, loss of frequency conversion which is less than 15 dB and good linearity.

关键词： particle swarm optimization algorithm Sub-harmonic mixer down-converted mixer

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Research on Optimal Hydroelectric Power Generation Balance Problem Based on particle swarm optimization 3

Research on Optimal Hydroelectric Power Generation Balance P...

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3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

作者： Zhang, Xinyu Huaqiao University School of Information Science and Engineering Xiamen China

ISBN: (纸本)9798350318180

In this paper, we established an optimization model based on particle swarm optimization and calculated the hydroelectric conversion efficiency of Lake Mead and Lake Powell with the height of water level under the constraint conditions by particle swarm optimization to provide a reference for developing a reasonable water allocation plan. © 2023 IEEE.

关键词： particle swarm optimization algorithm Water allocation water level

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Parameter Estimation of Photovoltaic Cell Model Based on Improved particle swarm optimization 3

Parameter Estimation of Photovoltaic Cell Model Based on Imp...

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2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023

作者： Yang, Bofei Zhao, Shuke Zhi, Haijie Nanjing University of Posts and Telecommunications Nanjing China Nanjing University of Aeronautics and Astronautics Nanjing China Karamay Karamay China

ISBN: (纸本)9798350341546

In the process of photovoltaic system converting solar energy into electric energy, the PV model is established. The parameters of the model have a large impact on the conversion performance and efficiency. For the purpose of accurate identification of circuit model parameters, an improved optimization algorithm based on particle swarm optimization is adopted, which combines the optimization strategy and hybrid algorithm proposed in recent years, It makes up for the fact that traditional particle swarm algorithms tend to be stuck in local optimal solutions and search efficiency decreases in multi-dimension. such as easy to fall into the local optimal solution and the decline of search efficiency in multi-dimensional. The improved algorithm is applied to the parameter identification of PV models with a single diode, and the accuracy of the algorithm is verified. The original particle swarm optimization algorithm and the optimization algorithm are simulated and the difference between the simulation data and the experimental data is calculated. The experiment shows that the Root-mean-square deviation (RMSE) of the optimized algorithm is far less than that of the original particle swarm optimization algorithm, the measurement results of current and voltage are closer to the true values, and the parameter identification is more accurate. Satisfied the needs of practical applications. © 2023 IEEE.

关键词： Parameter identification particle swarm optimization algorithm Single diode model

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