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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Han, Guangming Xiao, Shenyang Wang, Shihao Zhu, Youxiang Lv, Xinquan Information Telecommunications Company State Grid Shandong Electric Power Company Jinan250001 China

ISBN: (纸本)9798350319125

With the rapid development of Internet and the wide application of intelligent technology, power communication network has become an important part of modern power system. However, network security threats are also increasing, which poses a great challenge to the security of power communication network. Therefore, it is of great practical significance to study how to predict the security situation of power communication network and find and prevent security risks in time. © 2023 IEEE.

关键词： education innovation and entrepreneurship for college students pso optimization algorithm statistical theory

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Three-Dimensional Stability Analysis of Tailings Pond Based on pso-Kriging Model

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INDIAN GEOTECHNICAL JOURNAL 2024年 1-13页

作者： Shi, Kaidong Huang, Deyong Lv, Shiwei Peng, Chenxin Duan, Zefeng Kunming Univ Sci & Technol Fac Land Resource Engn Kunming 650093 Yunnan Peoples R China

In the process of tailings accumulation, multiple factors lead to obvious spatial differences and uneven distribution of the physical characteristics of tailings. However, a large number of physical experiments are required to study these characteristics, and although these experiments can be repeated, there are systematic errors and high costs, so an approximate model can be constructed for mechanical learning to predict how to solve this problem and become the key to the stability analysis of tailings ponds. In this paper, we start by constructing an improved Kriging model, and determine the actual characteristics of geological parameters through actual tailings pond sampling. Firstly, the physical and mechanical parameters that have a great influence on the stability of tailings ponds, natural bulk density, cohesion, and internal friction angle are selected as interpolation characteristic parameters. By comparing different optimization methods, an improved pso-Kriging interpolation model was proposed from the perspective of spatial variability. According to the cross-validation between the improved model and the original model, the prediction discrete plots and correlation coefficient values of the pso-Kriging model and the traditional Kriging model were analyzed. The results show that compared with the traditional model, the correlation coefficient values of the new model on the three tailings parameters are increased by 0.035, 0.151, and 0.117, respectively, indicating that the new model not only improves the accuracy of prediction, but also better captures the prediction trend. On the basis of the construction of the pso-Kriging interpolation model and the reliability verification of the model, a set of characteristic mechanical parameters of the interpolation points in line with the actual situation of the tailings pond were obtained, the mechanical parameters of the tailings were interpolated, and the three-dimensional numerical model of the tailings pond wa

关键词： Tailings pond Stability analysis Kriging interpolation pso optimization algorithm 3D numerical simulation

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Seismic performance analysis of adjacent eccentric structures based on pso algorithm

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STRUCTURES 2023年 50卷 39-51页

作者： Zhang, Shangrong Tang, Xiang Liu, Liangkun Lv, Huan Li, Shihao Ningxia Univ Sch Civil & Hydraul Engn Yinchuan 750021 Peoples R China Dongguan Univ Technol Sch Environm & Civil Engn Dongguan 523808 Peoples R China

Adjacent structures connected by dampers can effectively prevent collisions and attenuate the response of these structures. An early simplified model was investigated using a two-dimensional model. However, this model disregarded the effect of torsional response due to eccentricity. The eccentric arrangement of dampers owing to the non-parallel centroid between adjacent structures has not been considered in existing research. Here, the vibration equation of adjacent structures connected to a Kelvin damper was derived to study the torsional response under earthquake excitation. Furthermore, a pso (Particle Swarm optimization) algorithm was adopted to conduct a parametric study. Additionally, the damping effects of adjacent structures were compared using various damper layout schemes. The results show that the structural displacement was reduced by 50% by connecting dampers between adjacent structures. Placing dampers in the middle of a structure has a greater damping control effect than placing them on the side columns. However, the optimal damper layout must be chosen based on the diverse eccentric combinations and control goals of the adjacent structures. A damper can be arranged eccentrically to increase its damping control effect on an adjacent structures by 50% to 75%. The weakening of the edge effect on the damping effect should be considered when choosing the control objective for damper optimization. This weakening impact can reduce the damping effects by 50% and lead to greater deformation of the side column. The response of adjacent structures can be controlled macroscopically by uti-lizing the translation-torsional energy ratio as the control goal. However, a high fundamental frequency ratio of adjacent structures should be avoided.

关键词： Adjacent eccentric structures Torsional response Eccentric arrangement of damper Damping control pso optimization algorithm

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Prediction of Road Rutting Depth Based on pso-CatBoost 9

Prediction of Road Rutting Depth Based on PSO-CatBoost

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9th International Conference on Computer and Communication Systems (ICCCS)

作者： Xing, Zhen-zhen Hao, Jun Pei, Li-li Weng, Yu-han Li, Hang-ying Changan Univ Sch Informat Engn Xian Peoples R China Changan Univ Sch Data Sci & Artificial Intelligence Xian Peoples R China

ISBN: (纸本)9798350350227;9798350350210

The rutting depth is one of the important indicators for evaluating the performance of road use. Accurately predicting the Rutting Depth Index (RDI) can timely detect and solve the problem of road damage, ensuring driving safety. This article constructs a multi influencing factor dataset for RDI prediction by integrating road detection, climate, and traffic flow data from the AB expressway in Shaanxi Province, China. By comparing the prediction results of four models, namely Random Forest(RF), XGBoost, CatBoost, and LightGBM, it was found that XGBoost and CatBoost has the highest accuracy on the test dataset. To further improve the predictive precision of above model, we utilized the Particle Swarm optimization (pso) technique to meticulously adjust the hyperparameters of both XGBoost and CatBoost. The experimental results show that using the pso-XGBoost and pso-CatBoost models to predict RDI, the R2 scores reached 0.8029 and 0.8135, respectively. Compared with the XGBoost and CatBoost models, the accuracy improved by 0.0655 and 0.022, respectively. This indicates that the application of pso significantly enhances the predictive accuracy of both XGBoost and CatBoost models for road rutting prediction, with the pso-CatBoost model demonstrating superior performance. Consequently, it provides valuable data for road maintenance strategies.

关键词： road rutting depth index integrated algorithm CatBoost pso optimization algorithm

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Global optimization control for nonlinear full-car active suspension system with multi-performances

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IET CONTROL THEORY AND APPLICATIONS 2021年第14期15卷 1882-1905页

作者： Chen, Chung-Cheng Chen, Yen-Ting Univ Technol City Coll Dongguan Dongguan Guangdong Peoples R China Natl Chung Hsing Univ Dept Elect Engn Taichung Taiwan 1 Wenchang RdLiaobu Town Dongguan 523419 Guangdong Peoples R China

In this article, based on feedback linearized approach and linear quadratic regulator optimization control approach using particle swarm optimization, the almost disturbance decoupling, input amplitude reduction, tuning parameter optimization, controllable convergence rate, improved suspension and globally exponential stability multi-performances of highly nonlinear multi-input multi-output full-car uncertain system are simultaneously achieved without applying any nonlinear function approximator including neural network approach and fuzzy logic approach. The article proposes a new method to achieve the optimal control matrices of LQR such that the composite controller can reduce the amplitudes of system control inputs. Determination of the LQR tuning parameters is conventionally determined via trial and error approach. In addition to being very troublesome, it is difficult to find the globally best tuning matrices with LQR method. This study has first proposed the convergence rate formula of the nonlinear system response as the fitness function of LQR approach by using pso optimization algorithm to take the place of the conventional trial and error method and locally Jacobian linearized approach under the guarantee of globally exponential stability. The simulation results show how the full-car system can be controlled optimally and satisfactorily and confirm the superiority of the proposed method.

关键词： linear quadratic regulator optimization control approach conventional trial Optimisation techniques nonlinear systems system control inputs particle swarm optimisation improved suspension feedback linearized approach globally best tuning matrices full-car system error method fuzzy logic neural nets function approximation highly nonlinear multiinput multioutput neural network approach controllable convergence rate Mechanical components Stability in control theory control system synthesis linear quadratic control nonlinear system response Control system analysis and synthesis methods Nonlinear control systems pso optimization algorithm error approach LQR approach convergence rate formula LQR tuning parameters matrix algebra globally exponential stability multiperformances asymptotic stability global optimization control optimal control matrices fuzzy logic approach disturbance decoupling feedback Algebra nonlinear function approximator nonlinear control systems Interpolation and function approximation (numerical analysis) input amplitude reduction uncertain systems Optimal control particle swarm optimization locally Jacobian linearized approach LQR method suspensions (mechanical components) optimal control linearisation techniques parameter optimization composite controller nonlinear full-car active suspension system

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Design and Analysis of Multi-Mode Distributed Array with Hybrid optimization Method

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APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL 2021年第12期36卷 1526-1534页

作者： Fang, Shutao Li, Weiming Ren, Wu Xue, Zhenghui Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China

In this paper, we presented an improved hybrid optimization method to construct distributed array with two identical sub-arrays, which is mainly applied on airplanes as the front-end of communication and detection system. According to different demands on array's gain and operating distances, the proposed method presents a scheme of implementation of two operate modes by optimizing elements' positions and excitations. Two sub-arrays are able to work together to realize high gain when the object is quite far away, and one sub-array is able to work alone when the object is relatively close. This method is presented based on Particle Swarm optimization (pso) method and convex method, accomplishing that peak sidelobe level (PSLL) of whole array is lowered under-10 dB, and PSLLs of sub-arrays are lowered under-20 dB by supplementing some auxiliary units and re-optimizing array's excitation distribution. In the procedure of optimization, the hybrid method is designed catering to multiple constraints according to the requirements of practical application. A specific example for synthesizing reconfigurable distributed array is provided and the sensitivity of obtained performance affected by interference of optimized results is discussed.

关键词： convex optimization differential evolu-tion algorithm distributed array synthesis grating lobe suppression pso optimization algorithm

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Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

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BUILDINGS 2021年第12期11卷 577页

作者： Ma, Ziyuan Zhang, Jingxiao Philbin, Simon P. Li, Hui Yang, Jie Feng, Yunlong Ballesteros-Perez, Pablo Skitmore, Martin Lanzhou Jiaotong Univ Sch Civil Engn Lanzhou 730070 Peoples R China Changan Univ Sch Econ & Management Xian 710064 Peoples R China London South Bank Univ Nathu Puri Inst Engn & Enterprise Sch Engn London SE1 0AA England Changan Univ Sch Civil Engn Xian 710061 Peoples R China China Rd & Bridge Corp Beijing 100027 Peoples R China Univ Politecn Valencia Dept Proyectos Ingn Camino Vera S-N Valencia 46022 Spain Bond Univ Fac Soc & Design Robina Q4229 Australia

With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (pso) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site.

关键词： dynamic quality monitoring system BeiDou Navigation Satellite System information technology construction quality management RBF neural network pso optimization algorithm

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Model Free Control of Electrically Driven Manipulator by Optimized Linear Extended State Observer, based on Voltage Control Strategy 6

Model Free Control of Electrically Driven Manipulator by Opt...

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6th RSI International Conference on Robotics and Mechatronics (IcRoM)

作者： Saleki, Amir Fateh, Mohammad Mehdi Shahrood Univ Technol Dept Elect & Robot Engn Shahrood Iran

ISBN: (纸本)9781728101279

This paper presents a new approach for robot manipulator control, based on voltage control strategy. The novelty of this paper is providing a model-free control system with optimized parameters. In this approach, it is not necessary to have dynamic equations and parameters of robot and its motors. Uncertainties and disturbances of each joint of the robot manipulator is estimated by a Linear Extended State Observer (LESO), and the convergence of estimated variables to actual variables has been analyzed. After estimating the disturbances, a proportional controller is used to tracking the reference trajectory. LESO and controller design parameters have been determined using the pso algorithm. Simulation results depicted that the proposed model-free controller has a satisfactory performance for reducing the position tracking error.

关键词： Model-Free control Voltage Control Strategy Linear Extended State Observer pso optimization algorithm

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PCA-based pso-BP neural network optimization algorithm 27

PCA-based PSO-BP neural network optimization algorithm

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27th Chinese Control and Decision Conference, CCDC 2015

作者： Shi, Lan Tang, Xu Lv, Jianhui College of Information Science and Engineering Northeastern University Shenyang Liaoning China

ISBN: (纸本)9781479970179

BP neural network inherits many disadvantages such as slow convergence speed and easily converging to local minimum. The input data generally has a high-dimensional feature. To improve the performance of neural network, we propose a novel algorithm. Before inputting the data into the neural network, this algorithm reduces the dimension of the data with PCA algorithm. Then, this algorithm simplifies the structure of the neural network and reduces the amount of computation combined with pso-BP algorithm. Simulation results experiments demonstrate that the proposed algorithm improves the overall efficiency of neural networks, which proves that PCA-Based PSP-BP algorithm is better than pso-BP algorithm © 2015 IEEE.

关键词： BP neural network Data dimensionality reduction pso optimization algorithm Principal Component Analysis

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PCA-Based pso-BP Neural Network optimization algorithm

PCA-Based PSO-BP Neural Network Optimization Algorithm

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第27届中国控制与决策会议

作者： Lan Shi Xu Tang Jianhui Lv College of Information Science and Engineering Northeastern University

BP neural network inherits many disadvantages such as slow convergence speed and easily converging to local *** input data generally has a high-dimensional *** improve the performance of neural network,we propose a novel *** inputting the data into the neural network,this algorithm reduces the dimension of the data with PCA ***,this algorithm simplifies the structure of the neural network and reduces the amount of computation combined with pso-BP *** results experiments demonstrate that the proposed algorithm improves the overall efficiency of neural networks,which proves that PCA-Based PSP-BP algorithm is better than pso-BP algorithm

关键词： BP neural network pso optimization algorithm Principal Component Analysis Data dimensionality reduction

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