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Smart Tool Development for Customized Charging Services to EV Users

WORLD ELECTRIC VEHICLE JOURNAL 2022年第8期13卷 145页

作者： Zambrano Galbis, Alberto Anton Garcia, Moises Martinez Garcia, Ana Isabel Karatzas, Stylianos Chassiakos, Athanasios Lazari, Vasiliki Ageli, Olympia ETRA Dept Technol Valencia 46018 Spain Univ Patras Civil Engn Dept Rion 26500 Greece

E-mobility is a key element in the future energy systems. The capabilities of EVs are many and vary since they can provide valuable system flexibility services, including management of congestion in transmission grids. According to the literature, leaving the charging process uncontrolled could hinder some of the present challenges in the power system. The development of a suitable charging management system is required to address different stakeholders' needs in the electro-mobility value chain. This paper focuses on the design of such a system, the TwinEV module, that offers high-value services to electric vehicles (EV) users. This module is based on a Smart Charging Tool (SCT), aiming to deliver a more user-central and cooperative approach to the EV charging processes. The methodology of the SCT tool, as well as the supportive optimization algorithm, are explained thoroughly. The architecture and the web applications of TwinEV module are analyzed. Finally, the deployment and testing results are presented.

关键词： electric vehicles charging stations smart charging optimization algorithm

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A Modified Sparrow Search algorithm with Application in 3d Route Planning for UAV

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SENSORS 2021年第4期21卷 1224-1224页

作者： Liu, Guiyun Shu, Cong Liang, Zhongwei Peng, Baihao Cheng, Lefeng Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China Guangzhou Univ Sch Elect & Commun Engn Guangzhou 510006 Peoples R China

The unmanned aerial vehicle (UAV) route planning problem mainly centralizes on the process of calculating the best route between the departure point and target point as well as avoiding obstructions on route to avoid collisions within a given flight area. A highly efficient route planning approach is required for this complex high dimensional optimization problem. However, many algorithms are infeasible or have low efficiency, particularly in the complex three-dimensional (3d) flight environment. In this paper, a modified sparrow search algorithm named CASSA has been presented to deal with this problem. Firstly, the 3d task space model and the UAV route planning cost functions are established, and the problem of route planning is transformed into a multi-dimensional function optimization problem. Secondly, the chaotic strategy is introduced to enhance the diversity of the population of the algorithm, and an adaptive inertia weight is used to balance the convergence rate and exploration capabilities of the algorithm. Finally, the Cauchy-Gaussian mutation strategy is adopted to enhance the capability of the algorithm to get rid of stagnation. The results of simulation demonstrate that the routes generated by CASSA are preferable to the sparrow search algorithm (SSA), particle swarm optimization (PSO), artificial bee colony (ABC), and whale optimization algorithm (WOA) under the identical environment, which means that CASSA is more efficient for solving UAV route planning problem when taking all kinds of constraints into consideration.

关键词： unmanned aerial vehicle optimization algorithm modified sparrow search algorithm route planning

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Modifled PSO algorithm for solving planar graph coloring problem

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Progress in Natural Science:Materials International 2008年第3期 353-357页

作者： Guangzhao Cui a, Limin Qin a, Sha Liua, Yanfeng Wang a, Xuncai Zhang b, Xianghong Cao a a College of Electrical and Electronic Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China b Research Institute of Biomolecular Computer, Huazhong University of Science and Technology, Wuhan 430074, China

The graph coloring is a classic NP-complete problem. Presently there is no effective method to solve this problem. Here we propose a modifled particle swarm optimization (PSO) algorithm in which a disturbance factor is added to a particle swarm optimizer for improv- ing its performance. When the current global best solution cannot be updated in a certain time period that is longer than the disturbance factor, a certain number of particles will be chosen according to probability and their velocities will be reset to force the particle swarm to get rid of local minimizers. It is found that this operation is helpful to improve the performance of particle swarm. Classic planar graph coloring problem is resolved by using modifled particle swarm optimization algorithm. Numerical simulation results show that the per- formance of the modified PSO is superior to that of the classical PSO.

关键词： Planar graph coloring problem PSO optimization algorithm

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Experimental method for modal parameter identification of civil engineering structures based on improved wavelet transform

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RESULTS IN ENGINEERING 2023年 20卷

作者： He, Ran Li, Hui Tang, Jia Hu, Zhangqi Zhang, Zaihua Hunan City Univ Coll Civil Engn Yiyang 413000 Peoples R China

With the continuous acceleration of the global construction industry, many structural infrastructure structures in China have been put into use for decades. They are very prone to damage due to fatigue. The modal parameter identification of civil engineering construction can evaluate the safety status of infrastructure structures. In view of this, an identification system of civil engineering structure modal parameters is proposed based on improved wavelet transform. In the process, the mode shape was chosen as the method of wavelet transform. The data was discretized by selecting the actual data of a high-speed railway station combined with sensors and wavelet transform. Finally, the correct identification of the modal parameters of civil engineering structures is realized. The data shows that under normal conditions where there is only white noise interference, the waveform of the structure is relatively stable, and the amplitude fluctuation is in the [-2,3] interval. At the same time, the average amplitude of the structure is in the [2.2, -1.5] interval under normal conditions. In addition, the positive and negative extreme points are 3.7 and -2.3, respectively. This indicates that the structure amplitude fluctuation is in a dynamic and stable state under normal circumstances. The optimized wavelet transform method identifies a total of four orders in the first six natural frequencies. The minimum error is 0.11%, the maximum error is 1.50%, and the average error of the first four natural frequencies is 0.578%. In addition, based on the comparison of theoretical and identification values of longitudinal vibration shapes, the proposed method can successfully detect abnormal values at the 10th and 18th nodes. From the above results, it shows that the wavelet transform method has high accuracy and small error in frequency identification. It meets the requirements of identifying the natural frequency parameters of the structure. From the calculation, the method propos

关键词： WT Discretization Modal parameter identification Scale Vibration mode optimization algorithm

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Training artificial neural networks using self-organizing migrating algorithm for skin segmentation

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SCIENTIFIC REPORTS 2024年第1期14卷 1-13页

作者： Diep, Quoc Bao Truong, Thanh-Cong Zelinka, Ivan Van Lang Univ Fac Mech Elect & Comp Engn Sch Technol Ho Chi Minh City Vietnam Univ Finance Mkt Fac Informat Technol Ho Chi Minh City Vietnam VSB TUO Fac Elect Engn & Comp Sci Dept Comp Sci 17 Listopadu 2172-15 Ostrava 70800 Czech Republic VSB Tech Univ Ostrava Quantum Comp Lab IT4Innovat 17 Listopadu 2172-15 Ostrava 70800 Czech Republic

This study presents an application of the self-organizing migrating algorithm (SOMA) to train artificial neural networks for skin segmentation tasks. We compare the performance of SOMA with popular gradient-based optimization methods such as ADAM and SGDM, as well as with another evolutionary algorithm, differential evolution (DE). Experiments are conducted on the skin dataset, which consists of 245,057 samples with skin and non-skin labels. The results show that the neural network trained by SOMA achieves the highest accuracy (93.18%), outperforming ADAM (84.87%), SGDM (84.79%), and DE (91.32%). The visual evaluation also reveals the SOMA-trained neural network's accurate and reliable segmentation capabilities in most cases. These findings highlight the potential of incorporating evolutionary optimization algorithms like SOMA into the training process of artificial neural networks, significantly improving performance in image segmentation tasks.

关键词： Skin segmentation Swarm intelligence optimization algorithm SOMA Artificial neural networks Computer vision

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3-D Model Matching Based on Distributed Estimation algorithm

3-D Model Matching Based on Distributed Estimation Algorithm

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21st Chinese Control and Decision Conference

作者： Chen Ying Ji Zhicheng Hua Chunjian Jiangnan Univ Sch Commun & Control Engn Wuxi 214122 Peoples R China Jiangnan Univ Sch Mech Engn Wuxi 214122 Peoples R China

ISBN: (纸本)9781424427239

In a three-dimensional (3-D) model-based objects tracking and recognition system, the key problem of objects location is to establish the relationship between 2-D objects image and 3-D model. Based on 3-D model projection and 2-D image feature extraction, a modified Hausdorff distance is used to establish the matching function. The relationship between matching parameters are described with a probability model, and the distribution of parameter evolves towards the direction of dominant character through probability model learning and the corresponding operation, which is proposed to solve the problem of overmany iteration and slow constringency velocity The experiments show that the optimal matching parameters between 3-D model and 2-D image feature can be found accurately and efficiently, and then the accurate object location is completed.

关键词： object location model-based matching distributed estimation optimization algorithm

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Study on GPS Attitude Determination Technology Based on QPSO algorithm

Study on GPS Attitude Determination Technology Based on QPSO...

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7th World Congress on Intelligent Control and Automation

作者： Xia, Kewen Zhang, Xinying Gao, Jinyong Zhang, Ling Hebei Univ Technol Tianjin 300401 Peoples R China

ISBN: (纸本)9781424421138

In order to improve the precision of attitude operator in GPS attitude determination, based on Quantum-behaved Particle Swarm optimization(QPSO) algorithm, a new GPS carrier phase searching technology of attitude determination is proposed. In favor of the ambiguity function method's fitness function, quantum behavior is introduced to enhance the ability of global searching to achieve the GPS fast determination. The simulations show the QPSO algorithm applied to solve benchmark functions is stable, fast of the searching speed and have a high accuracy. The actual application shows the method used in GPS attitude operator based on QPSO algorithm is able to search in the complex space, and the precision is high, the speed is rapid and the application effect is notable.

关键词： GPS attitude determination QPSO optimization algorithm

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A determinant elimination method for bottleneck assignment and generalized assignment problems

A determinant elimination method for bottleneck assignment a...

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International Conference on Measurement, Instrumentation and Automation (ICMIA 2012)

作者： Wu Wenbo Jia Yufu Sun Hongxing Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114045 Peoples R China

ISBN: (纸本)9783037855454

The bottleneck assignment (BA) and the generalized assignment (GA) problems and their exact solutions are explored in this paper. Firstly, a determinant elimination (DE) method is proposed based on the discussion of the time and space complexity of the enumeration method for both BA and GA problems. The optimization algorithm to the pre-assignment problem is then discussed and the adjusting and transformation to the cost matrix is adopted to reduce the computational complexity of the DE method. Finally, a synthesis method for both BA and GA problems is presented. The numerical experiments are carried out and the results indicate that the proposed method is feasible and of high efficiency.

关键词： bottleneck assignment generalized assignment problems determinant elimination optimization algorithm pre-assignment problem

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Research on time-delayed vibration reduction control of 1/4 vehicle semi-active suspension system with three degrees of freedom

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ADVANCES IN MECHANICAL ENGINEERING 2024年第9期16卷

作者： Guo, Yong Xu, Guang-Fei Duan, Cai-Yun Shandong Business Inst Yantai 264670 Shandong Peoples R China Liaocheng Univ Liaocheng Peoples R China

This paper is dedicated to the fundamental research of the mechanical model of a 1/4-vehicle semi-active suspension system with time-delayed state feedback control during wheel vertical displacement. The strategy combining the "equivalent harmonic excitation" optimization algorithm with the particle swarm optimization algorithm is proposed in this paper. Through the optimization and solution of time-delayed feedback control parameters of the 1/4 vehicle semi-active suspension system, the dynamic response of the vehicle suspension system before and after parameter optimization is studied. The research results indicate that, compared to passive control, time-delayed feedback control of wheel vertical displacement can significantly improve the smoothness, handling stability, and safety of vehicle operation.

关键词： Time-delayed feedback control semi-active suspension equivalent harmonic excitation optimization algorithm dynamic response

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Application of forecasting strategies and techniques to natural gas consumption: A comprehensive review and comparative study

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 129卷

作者： Tian, Ning Shao, Bilin Bian, Genqing Zeng, Huibin Li, Xiaojun Zhao, Wei Xian Univ Architecture & Technol Sch Management Xian 710055 Shaanxi Peoples R China Xian Univ Architecture & Technol Sch Informat & Control Engn Xian 710055 Shaanxi Peoples R China Shandong Acad Sci Informat Res Inst Jinan Peoples R China Qilu Univ Technol Shandong Acad Sci Res Ctr Digital Humanities Jinan Peoples R China

Accurate forecasting of natural gas consumption (NGC) plays an important role in energy supply, energy trading, economic effects and environmental sustainability. NGC forecasts can be used to adjust production and supply plans to improve gas efficiency and reduce carbon emissions and supply chain waste. This paper reviews the research progress on NGC in the past decade, analyzes the typical characteristics of different forecasting strategies, and highlights 163 studies in terms of the technical aspects of feature processing methods, data decomposition methods, forecasting models and optimization algorithms. It also systematically elaborates the application of statistical models, machine learning models, grey models, logistic regression and their combinations in predictive models. Bibliometric methods are also utilized to dissect research hotspots and summarize cutting-edge trends in the field. It is worth mentioning that in the terms of hybrid model structures, the application and performance of various model structures are described and evaluated. In this paper, the future development is discussed from spatiotemporal characteristics, studying reasonable data decomposition layers and fusion models, considering potential data privacy issues, and developing artificial intelligence-supporting models and interpretable frameworks. This paper is expected to provide a multi-technology reference for natural gas forecasting and help researchers to select and develop more accurate forecasting techniques and strategies.

关键词： Natural gas consumption forecasting Forecasting strategy Data decomposition Feature selection and extraction optimization algorithm

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