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10th Smart Grid Conference (SGC)

作者： Memari, Mehran Karimi, Ali Hashemi-Dezaki, Hamed Univ Kashan Fac Elect & Comp Engn Kashan Iran

ISBN: (纸本)9781665419574

The challenges of active distribution networks (ADNs) have received a great deal of attention due to the increase in the penetration of distributed generations (DGs). The uncertainties of renewable DGs adversely affect the ADNs performance;thus, reliability evaluation of ADNs considering uncertainties is important. The analytical and Monte Carlo Simulation (MCS) methods are used for studying the uncertainties, while MCS is more popular than analytical methods. The main challenge of the MCS method is its computation time. In this paper, a new scenario-based reliability evaluation method using particle swarm optimization (pso) clustering algorithm is proposed, which can significantly reduce the computation time of reliability evaluation in comparison with MCS. Also, the optimal number of clusters is obtained in the introduced method. Test results of applying the introduced method to the real 20 kV distribution network of the Barzok region of Kashan in Iran illustrate its effectiveness and advantages.

关键词： Renewable distributed generations Reliability evaluation Scenario-based method pso algorithm Monte Carlo Simulation

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Time-optimal Trajectory Planning of Dulcimer Music Robot Based on pso algorithm 32

Time-optimal Trajectory Planning of Dulcimer Music Robot Bas...

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32nd Chinese Control And Decision Conference (CCDC)

作者： Zhang, Weimin Fu, Shixiong China Univ Geosci Sch Mech & Elect Informat Wuhan 430074 Peoples R China

ISBN: (纸本)9781728158556

For a dulcimer music robot that strikes a dulcimer, fast and high-frequency striking is a key requirement, so the time optimization of the trajectory planning of the robot arm is the first problem to be solved in motion control. In this paper, the kinematics modeling and solving are firstly completed by using the D-H parameter method. Then the steps of trajectory planning by interpolation and the application of basic pso algorithm are introduced. As for the deficiency of only velocity constraint, we propose an improve pso algorithm considering complete kinematic constraints of all joints, which can ensure that the optimal trajectory planned is reasonable. Finally, the simulation experiments of time optimization and trajectory planning are carried out in MATLAB. Experiments show that after optimizing the interpolation time by the improved pso algorithm under the kinematic constraints, the total time of trajectory planning of the robot is greatly reduced by 74.35%;and the planned time-optimal trajectory curves are continuous and smooth, which meets the requirements of motion stability of the manipulator. As a result, the efficiency of the improved pso algorithm applied to time-optimal trajectory planning of robot is verified.

关键词： Dulcimer Music Robot Time-optimal Trajectory Planning pso algorithm

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Predict Prices of Second‐hand House Using GBDT algorithm and pso algorithm

Frontiers in Economics and Management

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Frontiers in Economics and Management 2021年第11期2卷 513-524页

作者： Hanyu Zhu Hongbo Li

Due to the continuous rise of house prices, the Second-hand housing market is becoming more and more prosperous in large-scale cities. This paper will comprehensively consider the attributes of Second-hand houses and surrounding environmental factors, and make a prediction of the transaction price of Second-hand houses in Beijing using the GBDT regression algorithm, a classical algorithm in fields of ensemble learning. The experimental data comes from a well-known Second-hand housing trading platform in China, and we use the public map service API to collect the information of supporting facilities around the searched Second-hand house. Besides, we use Tableau to visually analyze the data in the preprocessing process. pso algorithm is used to adjust the parameters of GBDT algorithm to improve its performance. Through computational experiments, based on a large number of actual transaction data, it is verified that the proposed prediction algorithm is better than lasso regression algorithm on a number of evaluating indicators.

关键词： Regression Prediction GBDT algorithm pso algorithm Data Visualization

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pso algorithm for UAV autonomous path planning with threat and energy cost optimization 12

PSO algorithm for UAV autonomous path planning with threat a...

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12th Conference on Reconnaissance and Electronic Warfare Systems (CREWS)

作者： Konatowski, Stanislaw Pawlowski, Piotr Mil Univ Technol Fac Elect Inst Radioelect 2 Gen Witolda Urbanowicza St PL-00908 Warsaw Poland Mil Unit 4653 PL-84313 Siemirowice Poland

ISBN: (数字)9781510627864

ISBN: (纸本)9781510627864

The pso (Particle Swarm Optimization) algorithm uses a population of single particles, randomly distributed over the function search space, in order to construct an optimal flight path. During the algorithm iteration execution, each particle evaluates its fitness function according to the actual position. Then, every particle moves towards a direction dependent on its actual best position and the position of the best particle so far. The procedure ends when the iteration limit is reached or fitness criterium is met. In the presented autonomous UAV 3D path planning method, a pso algorithm is used to build a feasible path, optimized in terms of fuel and threat cost. The process begins when the UAV detects or receives information about threats appearing on its primary trajectory. The population of particles moves in the search space of three variables, which are the angles of pitch, roll and yaw. These angles determine the spatial orientation of the UAV, indicating its direction of movement in each step. Further waypoints are chosen with consideration of the distance to the target and violation of threat areas. As a final result, the pso algorithm constructs a suboptimal, feasible path which could be used as a reference trajectory for the UAV's automatic control system. Simulation results turned out to be completely repeatable and indistinguishable, despite the stochastic nature of the algorithm, which proves its great optimization abilities. Moreover, its short execution time (within seconds) allows this procedure to be used in real time applications.

关键词： path planning UAV pso algorithm

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Introduced a new method for enhancement of intrusion detection with random forest and pso algorithm

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SECURITY AND PRIVACY 2021年第2期4卷

作者： Ajdani, Mahdi Ghaffary, Hamidreza Islamic Azad Univ Dept Comp Sci Ferdows Branch Ferdows Iran

As computer networks expand, attacks and intrusions into these networks have increased. In addition to firewalls and other intrusion prevention equipment, other systems, such as IDS (Metrics), are designed to provide enhanced security in computer systems, including the purpose of monitoring intrusive and intrusive activities. Intrusive allocation system can be considered effective if the high intrusion rate is slightly misleading, and in this article a new way to classify it is abnormal (infiltration) in the host or network. UNSW-NB15 and KDD-Cup'99 Datasets Introducing Random Forest and pso algorithm. In this paper, training data and label data used with the random forest algorithm. After creating a random forest algorithm, provide test data. We use the data stored in train step, which is actually a copy of the data, so that when performing the test step, the same training data can be compared with categorize using a pso algorithm. In in order to show the accuracy of the proposed method, an example of the confusion matrix formed in the code that showed performance of all methods and modes studied is compared based on accuracy and time that the pso algorithm has always been able to take less time, which is quite acceptable and predictable. Improves correct diagnosis of correct detection rate in that report was 75.94% and in the proposed method in this article it reached 97%. With the proposed method, learning speed has been greatly increased and accuracy is acceptable.

关键词： behavioral pattern allotment data mining pso algorithm random Forest algorithm

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Modelling the nonlinear relationship between CO2 emissions and economic growth using a pso algorithm-based grey Verhulst model

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JOURNAL OF CLEANER PRODUCTION 2019年 207卷 214-224页

作者： Wang, Zheng-Xin Li, Qin Zhejiang Univ Finance & Econ Sch Econ Hangzhou 310018 Zhejiang Peoples R China Zhejiang Univ Finance & Econ Ctr Reg Econ & Integrated Dev Hangzhou 310018 Zhejiang Peoples R China

A new method for discussing the relationship between CO2 emissions and economic growth is proposed using grey systems theory. GDP and CO2 emissions per capita are separately regarded as the input to, and output of, a grey system to establish a non-equigap grey Verhulst model (NE grey Verhulst model). To avoid the errors resulting from substituting a difference equation for a differential equation in grey modelling theory, the derived non-equigap grey Verhulst model (DNE grey Verhulst model) is deduced. Moreover, the structural parameters of the model are optimised using a particle swarm optimisation (pso) algorithm in an attempt to further improve modelling accuracy. Based on data relating to CO2 emissions and GDP per capita in China from 1990 to 2014, empirical research is conducted which shows that the relationship between CO2 emissions and economic growth exhibits an inverted U-shape and the emissions are in a rapid growth stage on the left of the curve. It is predicted that CO2 emissions per capita will continue to rise from 2016 to 2020 and will not reach their peak before 2030, so the Chinese government should take effective measures to reduce carbon emissions. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Grey systems theory pso algorithm Non-equigap grey Verhulst model CO2 emissions Economic growth

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Cluster tree topology construction method based on pso algorithm to prolong the lifetime of ZigBee wireless sensor networks

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2019年第1期2019卷 1-13页

作者： Yu, Yang Xue, Bo Chen, Zhuyang Qian, Zhiwen Jiangsu Univ Technol Sch Elect Informat Engn Changzhou 213001 Peoples R China

For wireless sensor networks (WSNs) based on ZigBee technology, the network topology plays an important role for improving the energy efficiency and the network lifetime. An appropriate construction method of network topology should be designed for saving the energy of the battery in each network node so as to prolong the lifetime of ZigBee WSNs. In this paper, a novel cluster tree topology construction method based on particle swarm optimization (pso) algorithm is proposed. In order to transform the network topology construction problem into an energy consumption optimization problem, an evaluation function reflecting the network energy consumption is designed, and the network topology is mapped into a particle population individual suitable for the pso algorithm. In order to prolong the network lifetime as long as possible, two network topology reconstruction methods with the pso algorithm based on fixed and variable energy thresholds are further proposed, respectively. The simulation results show that the proposed methods can prolong the lifetime of ZigBee WSNs effectively.

关键词： Cluster tree topology pso algorithm ZigBee Wireless sensor networks Lifetime

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Optimal tuning of FOPID controller based on pso algorithm with reference model for a single conical tank system

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SN APPLIED SCIENCES 2019年第7期1卷 758页

作者： Rajesh, R. Sri Krishna Coll Technol Dept Instrumentat & Control Engn Coimbatore Tamil Nadu India

The fractional order proportional integral derivative controller (FOPID) replaces the conventional PID controller for its immense merits such as its simple structure, better set point tracking, high disturbance rejection, higher capability of handling model uncertainties in nonlinear and real time applications. This paper addresses the effectiveness of the FOPID controller on a level control of single conical system in real time. It is one of the classical nonlinear control problem and its shape not only contributes the proper mixing of liquids and also guarantee to drainage of solid wastes. This study, a dual loop controller is proposed and constructed with a master process and slave process for a level control of a single conical tank system. In the slave process, the output response obtained by the traditional PID controller combined with the conical tank reference model and compared with the output response of the master process. The obtained error signal is used to dynamically correct the parameters of the FOPID controller in the master process. The tuning of FOPID controller is a challenging task due to its presence of extra parameters and it efficiently carried out by particle swarm optimization (pso) algorithm. The obtained result reveals that the Proposed pso optimized FOPID controller with reference model demonstrated the better set point tracking, smooth controller response than other conventional integer order controllers.

关键词： FOPID controller Single conical tank system Reference model pso algorithm

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An Investigation of pso algorithm-Based Back Analysis on the Three-Dimensional Seepage Characteristics of an Earth Dam

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INDIAN GEOTECHNICAL JOURNAL 2019年第2期49卷 232-240页

作者： Chen, Shoukai Liu, Xinfei North China Univ Water Resources & Elect Power Sch Water Conservancy Zhengzhou 450011 Henan Peoples R China Henan Key Lab Water Environm Simulat & Treatment Zhengzhou 450045 Henan Peoples R China Henan Water Environm Management & Ecol Rehabil Ac Zhengzhou 450011 Henan Peoples R China Collaborat Innovat Ctr Water Resources Efficient Zhengzhou 450011 Henan Peoples R China

In view of the problem of seepage safety and the character of dangerous reservoir earth dam, the 3D seepage of FEM back analysis was studied. Based on a reservoir project, the rationality of prototype observation data in recent years is analyzed, and the effective monitoring point and its observation data are selected for back analysis. The simulation calculation model is built, and the permeability coefficient of key materials and seepage characteristics of calculation area of earth dam are obtained after using particle swarm optimization (pso) algorithm as the inversion algorithm and using FEM as the seepage field algorithm method of improved nodal virtual flux. The results shows that the pso, which has high efficiency with back analyzing the permeability coefficient of materials in the dam and satisfactory accuracy, can meet the requirements of engineering, and a large seepage gradient in overflow point and boundary of earth dam, which is unfavorable for dam seepage stability, is produced when the problem of contact erosion is also existed in connection part of earth dam section and masonry dam section.

关键词： Reservoir earth dam Seepage Back analysis pso algorithm Permeability coefficient

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Pattern synthesize of a cylindrical conformal array antenna by pso algorithm

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2020年第4期30卷 1-8页

作者： Alizadeh, Mohammad Mahdi Hosseini, Seyyed Esmail Shiraz Univ Dept Commun & Elect Sch Elect & Comp Engn Shiraz Iran

Pattern synthesize of conformal array antennas is often a challenging problem. Various optimization algorithms such as genetic, particle swarm optimization (pso), and invasive weed optimization have already been used for pattern synthesizing of conformal arrays. In this paper, a focused beam is synthesized for a quarter cylindrical conformal array antenna using the pso algorithm with small computations. The desired pattern is a focused beam at theta = 90 degrees and phi = 45 degrees with 10 degrees beamwidth in elevation and 15 degrees beamwidth in azimuth with -20 dB side-lobe level. This method can be used in general for synthesizing arbitrary desired patterns and array geometries.

关键词： array antenna conformal cylindrical array pattern synthesize pso algorithm

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