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Evaluation of problems and countermeasures in marketing teaching based on cloud computing data aggregation algorithm

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SN APPLIED SCIENCES 2023年第5期5卷 1-12页

作者： Shen, Weinan Suzhou Vocat Univ Sch Management Suzhou 215000 Jiangsu Peoples R China

In this study, we present a highly practical marketing course. Through learning marketing, we can cultivate students' ability to analyze, solve and practice problems. Therefore, this paper would study the problems encountered in the marketing course through cloud computing technology and propose corresponding countermeasures, so as to better improve students' ability to analyze and solve problems and enhance the effectiveness of the classroom. This paper also analyzed the data aggregation algorithm based on particle swarm optimization (PSO) algorithm. The results showed that when other conditions were the same, only 6 students approve of the traditional marketing teaching mode, accounting for 12%;there were 44 people who did not approve, accounting for 88%. This number was more than half;49 students recognized the optimized marketing teaching mode, accounting for 98%;there was 1 person who did not approve, accounting for 2%. The proportion of people who did not approve after optimization was far less than that of the traditional model, which showed that cloud computing data aggregation algorithm could find out the problems in marketing teaching and provide correct countermeasures to solve them, so that the teaching model could be optimized. (1) The data aggregation algorithm based on cloud computing has a good optimization effect on the evaluation of marketing teaching problems and countermeasures, indicating a new direction for future research. (2) The combination of cloud computing and data aggregation algorithm is not only a novel research perspective, but also a perfect idea. (3) Marketing course is a very important course in today's society. The study of its teaching problems and countermeasures evaluation will help students improve their learning efficiency and enhance their ability to adapt to the society.

关键词： Marketing teaching Cloud computing Data aggregation algorithm Analysis of problems and countermeasures particle swarm optimization algorithm

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Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach

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International Journal of Agricultural and Biological Engineering 2023年第1期16卷 66-72页

作者： Lifeng Xu Zhongzhu Yang Zusheng Huang Weilong Ding Gerhard Buck-Sorlin College of Computer Science&Technology Zhejiang University of TechnologyHangzhou 310026China IRHS INRAEAGROCAMPUS OUESTUniversite d’AngersSFR 4207 QUASAV42 rue Georges Morel49071 BeaucouzécedexFrance

With the development of aviation agricultural technology,the number of farmers adopting the use of drones in daily agricultural activities is growing rapidly in recent *** these,a large portion constitutes agricultural drones being used in pest control and crop protection practices,*** spraying of *** pesticides with drones have proven to be faster than other traditional *** the downside,flight time and range of Unmanned Aerial Vehicles(UAV)are often ***,a proper arrangement of flight height and velocity will greatly improve spraying efficiency.A new strategy to optimize the flight parameters,*** height and flight velocity,for fixed-wing UAV with a 3D simulation-based approach together with an automatic optimization algorithm was proposed in this *** find the optimal parameters for a UAV to fly and spray under certain environmental conditions,a three-dimensional model of the target crop was established first,followed by a detailed simulation of droplet *** a demonstration case,a grass model was developed and used as the target plant,and a physics-based method was used to simulate realistically the movement of the droplets in the air as well as the interaction between the droplets and the plant to obtain the droplet deposition rate under the specified operating ***,the standard particle swarm optimization(PSO)algorithm was used to optimize the UAV operating parameters to obtain the best operating *** results indicate that using the standard PSO algorithm to optimize the operating parameters of the drone could significantly improve the deposition rate and find the best operating parameters.

关键词： unmanned aerial vehicle droplet deposition 3D simulation particle swarm optimization algorithm

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Lyapunov Control of High-Dimensional Closed Quantum Systems Based on particle swarm optimization

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IEEE ACCESS 2020年 8卷 49765-49774页

作者： Guan, Xiaoke Kuang, Sen Lu, Xiujuan Yan, Jiazhen Univ Sci & Technol China Dept Automat Hefei 230027 Peoples R China Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei 230027 Peoples R China

For high-dimensional closed quantum systems, this paper proposes a novel quantum Lyapunov control scheme based on the particle swarm optimization algorithm and achieves a high-probability population transfer of the system to a non-isolated target eigenstate in the LaSalle invariant set under usual smooth Lyapunov control laws. Via a quadratic Lyapunov function with unknown parameters, a control law with the unknown parameters is designed;based on the LaSalle invariance principle and the energy-level connectivity graph, the stability of the system is analyzed;by using the particle swarm optimization algorithm, a set of optimal parameters is obtained to achieve the control goal. In particular, we propose a path planning method based on the energy-level connectivity graph to determine the initial values of the unknown parameters, which is such that the optimization algorithm can efficiently and conveniently find a set of optimal solutions of the unknown parameters. Numerical simulation experiments on a five-level quantum system and a three-qubit system demonstrate that the proposed Lyapunov control scheme based on the particle swarm optimization algorithm has a good control effect.

关键词： Lyapunov methods Sociology Statistics particle swarm optimization Control systems Quantum entanglement High-dimensional quantum systems Lyapunov control particle swarm optimization algorithm parameter optimization initial values energy-level connectivity graph

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Design and optimization of power supply communication system for indoor wheeled inspection robots

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年

作者： Su, Renqi Shen, Hongming Huang, Yin Zhao, Shun Huaneng Zhejiang Energy Dev Co Ltd Clean Energy Branch Room 303Huaneng Bldg Hangzhou 310022 Peoples R China Huaneng Zhejiang Energy Dev Co Ltd Hangzhou Peoples R China

The existing power supply and communication system for indoor wheeled patrol robots relies on magnetic coupling mechanisms, but magnetic coupling mechanisms rarely meet the stability requirements of the system. In response to the challenge, a magnetic resonance-based wireless power and signal transmission system for robots is designed in this paper. It proposes transmitter coil switching control technology and receiver continuous energy harvesting technology, and establishes a communication model for one-to-many reception under different system states during motion. Based on this, a mathematical model for optimizing the structure of the magnetic coupling mechanism among transmitter and receiver coils was established. Optimal parameter values were determined using an enhanced particle swarm optimization algorithm (EAPSO). Experimental outcome implies that the transmission efficiency of the proposed method is 87.9%, representing an improvement of 4.8%-20.5%, and it can achieve efficient system stability control.

关键词： indoor wheeled patrol robot power supply and communication system magnetic coupling resonance particle swarm optimization algorithm transmitter and receiver coils

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Mechanism of time-delay feedback control of suspension damping with an annular vibration-absorbing structure

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JOURNAL OF VIBROENGINEERING 2023年第8期25卷 1561-1582页

作者： Chen, Yajie Ma, Kehui Ren, Chuanbo Nan, Yang Zhou, Pengcheng Shandong Univ Technol Sch Transportat & Vehicle Engn Zibo 255000 Peoples R China

With the aim of enhancing both the ride comfort and the safety of the vehicle, we propose a new type of suspension with an annular vibration-absorbing structure, and establish a 3-DOF 1/4 vehicle model. The structure parameters and time-delay feedback control parameters are determined by particle swarm optimization algorithms, which take the root mean values of body acceleration, suspension dynamic deflection, and tire dynamic displacement as their optimization objectives. We analyze the stability of the suspension control system to ensure the stability of the time-delay control system through the Routh-Hurwitz stability criterion, characteristic root method, and stability switching method. Then, we compare and analyze the response characteristics of conventional suspension, new suspension without time-delay feedback control, and new suspension with time-delay feedback control under simple harmonic excitation and random excitation. The results show that the new suspension with time-delay feedback control has a significant damping effect on the body under the premise of ensuring the stability of the system.

关键词： suspension structure vehicle vibration damping time-delay feedback control stability analysis particle swarm optimization algorithm

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Research on Comprehensive Control of Power Quality of Port Distribution Network Considering Large-Scale Access of Shore Power Load

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Energy Engineering 2023年第5期120卷 1185-1201页

作者： Yuqian Qi Mingshui Li Yu Lu Baitong Li Tianjin University Tianjin300110China

In view of the problem of power quality degradation of port distribution network after the large-scale application of shore power load,a method of power quality management of port distribution network is *** on the objective function of the best power quality management effect and the smallest investment cost of the management device,the optimization model of power quality management in the distribution network after the large-scale application of large-capacity shore power is *** on the balance between the economic demand of distribution network resources optimization and power quality management capability,the power quality of distribution network is considered *** proposed optimization algorithm for power quality management based on Matlab and OpenDSS is proposed and analyzed for port distribution *** simulation results show that the proposed optimizationmethod can maximize the power qualitymanagement capability of the port distribution network,and the proposed optimization algorithm has good convergence and global optimization finding capability.

关键词： Shore power harmonic control multi objective optimization particle swarm optimization algorithm

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D-PSO: An optimization algorithm for Wireless Sensor Network Layout in Power Systems 9

D-PSO: An Optimization Algorithm for Wireless Sensor Network...

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9th International Conference on Automation, Control and Robotics Engineering (CACRE)

作者： Ma, Pengwei Zhu, Yuanjiao Sun, Zheng Wei, Jingyi Luo, Yunchen Zhou, Jie Shihezi Univ Coll Informat Sci & Technol Shihezi Peoples R China

ISBN: (纸本)9798350350319;9798350350302

The effective deployment of wireless sensor networks (WSNs) is a crucial foundation for the intelligent development of power systems. To address the optimization of wireless sensor distribution in power systems, this paper proposes a novel method named the Distributed particle swarm optimization algorithm (D-PSO). This method mitigates the premature convergence issue of heuristic algorithms by introducing a regional operator. Additionally, considering the high-interference environment in power systems, relay node strategy (RNS) is incorporated to ensure communication quality. Simulation results validate the effectiveness and superiority of the D-PSO method and demonstrate the necessity of the RNS. Compared to some advanced particle swarm algorithms, this method better balances energy consumption, coverage, and communication quality, thereby significantly enhancing the overall performance of the wireless sensor network.

关键词： wireless sensor network power systems particle swarm optimization algorithm

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Automatic scheduling and control technology of pump gate clusters of regional water conservancy project

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DESALINATION AND WATER TREATMENT 2023年 293卷 82-88页

作者： Sun, Aijun Hu, Donghui Shan, Chengju Wang, Jun Yuyao Water Resources Bur Ningbo 315470 Peoples R China Zhejiang Univ Water Resources & Elect Power Hangzhou 310018 Peoples R China

With the frequent regional flood disasters in recent years, the study of automatic scheduling and control technology of pump gate clusters has become crucial in related academic circles. Here, an automatic flood control and scheduling model for pump and gate clusters of water conservancy projects is constructed by combining hormone regulation and particle swarm algorithm. The model can regulate the maximum discharge flow and maximum water level of reservoirs according to the actual situation in order to achieve flood prevention and consumption prevention. The model is validated using two reservoirs in city A as an example. The results show that the maximum dis-charge flow of the two reservoirs after the model treatment is 1,996.16 and 16,738.28 m3/s, which reduces the incidence of flooding in city A. In addition, after the optimal flood control scheduling, the maximum water levels of the once-in-a-century flood and once-in-two-centuries flood in city A become 80.41 and 81.66 m, respectively, which are in the safe water level range. The study is of great significance for the reduction of flooding.

关键词： Regional water conservancy project Pump gate clusters Hormone regulation particle swarm optimization algorithm Scheduling and control

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Hierarchical Optimal Scheduling Strategy for Electric Vehicles with Dynamic Time-of-Use Tariff

Hierarchical Optimal Scheduling Strategy for Electric Vehicl...

引用

International Conference on Wireless Power Transfer (ICWPT)

作者： Wang, ChuangXin Chen, Zhong Changsha Univ Technol Sch Elect & Informat Engn Changsha Peoples R China

ISBN: (纸本)9789819708796;9789819708772;9789819708765

The disorderly charging tactics of large-scale electric vehicle (EV) will lead to the increase of peak-valley load difference of the power grid and destroy the stability of the power system. In order to solve this problem, considering the peak adjustment demand of the grid side and the different demands of the users on the charging amount and charging cost, this paper proposes a hierarchical optimization scheduling method based on the dynamic TOU time segment model. This method updates the load curve according to the load information of each EV when it is connected to the grid. Meanwhile, the dynamic time-of-use electricity price model proposed in this paper is used to dynamically update the peak-valley electricity price of the EV. Among them, the upper layer model takes the minimum variance of the total load of the grid as the objective function, and the lower layer model takes the minimum deviation of the agent scheduling plan, the maximum amount of charging and the minimum cost of charging as the objective function, and adopts the improved PSO algorithm to optimize the charging (discharging) tactics of each EV. Finally, the simulation analysis is carried out with a concrete example. The results show that this method can effectively reduce the peak-valley difference of load demand curve on the premise of ensuring the travel demand and economic benefits of EV owners.

关键词： particle swarm optimization algorithm user responsiveness electric vehicle orderly charge and discharge

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The Mechanism of the Role of Big Data Knowledge Management in the Development of Enterprise Innovation

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2023年第6期14卷 1364-1372页

作者： Yan, Guangyu Ma, Rui Chengdu Polytech Dept Sci Res Chengdu 610041 Peoples R China Chengdu Univ Tradit Chinese Med Hlth & Rehabil Coll Chengdu 611137 Peoples R China

The effectiveness and efficiency of enterprise knowledge management depends on the effectiveness and efficiency of the enterprise's implementation of knowledge management. Big data technology can collect, analyse and apply the massive amount of data in an organisation to support the implementation of knowledge management. Therefore, exploring the role of big-data knowledge management in the development of enterprise innovation will help enterprises to better implement knowledge management. Based on this, the study aims to propose a model for predicting big data knowledge management and enterprise innovation development for high-tech enterprises in China. The study firstly used Principal Component Analysis (PCA) to decrease the dimensionality of the model, and then used the particle swarm algorithm to optimize BP neural network (PSO-BP). Network (PSO-BP) was used to evaluate enterprise knowledge management and enterprise innovation development. The results of the study show that the absolute values of the relative errors of the pre-processed model do not exceed the 5% threshold, and only the relative errors of some indicators are relatively large, such as X5 and X7, with values of 4.5% and -3.8%, indicating that the model has a good performance in predicting the innovation effect of enterprises.

关键词： Big data knowledge management BP neural network algorithm enterprise innovation development principal component analysis particle swarm optimization algorithm correlation analysis

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