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检索条件"任意字段=2021 4th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2021"

共 251 条记录，以下是101-110 订阅

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End-to-End control Method for Unmanned Vehicle Based on Knowledge Distillation 6

End-to-End Control Method for Unmanned Vehicle Based on Know...

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2023 6th international conference on advanced algorithms and control engineering, icaace 2023

作者： Zhu, Bingbing Gan, Haiyun Lin, Weiwen School of Automobile and Transportation Tianjin University of Technology and Education Tianjin300222 China

In order to construct a lightweight end-to-end autonomous driving model, knowledge distillation technology is introduced into the construction of the model. the model is composed of a vehicle trajectory orientation marker point prediction algorithm and a motion control algorithm. the prediction algorithm uses the Resnet34 with high precision as a teacher network and the Squeezenet with fast speed as a student network. Based on the knowledge distillation technology, the prediction ability of the teacher network is transferred to the student network so that the student network can predict a marker point accurately and quickly. the control algorithm is constructed based on the integral-differential model, and the predicted marker point is converted into lateral control commands of a vehicle. through the experimental analysis of the complexity of the model, prediction accuracy of the marker point, and actual vehicle deployment effect, it is verified that the proposed model can control a vehicle to drive accurately and uniformly along a lane line trajectory. © Published under licence by IOP Publishing Ltd.

关键词： Distillation

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Impact of uncertainty sources on the voltage control of active distribution grids 4

Impact of uncertainty sources on the voltage control of acti...

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4th international conference on Smart Energy Systems and Technologies (SEST)

作者： Pau, Marco De Din, Edoardo Ponci, Ferdinanda Pegoraro, Paolo Attilio Sulis, Sara Muscas, Carlo Rhein Westfal TH Aachen Inst Automat Complex Power Syst Aachen Germany Univ Cagliari Dept Elect & Elect Engn Cagliari Italy

ISBN: (纸本)9781728176604

advanced distribution management systems are increasingly required to operate today's distribution grids and to deal with the challenges brought by both renewable sources and new loads. In particular, voltage control strategies are essential to handle possible anomalies in the voltage profile of the grid. In the field implementation of voltage control algorithms, several uncertainty factors can potentially affect the operation of the control strategy and degrade its performance. this paper aims at investigating the impact brought by different sources of uncertainty on the control actions defined by a centralized voltage control algorithm. A sensitivity analysis is conducted to identify how the control output is affected by both different levels and types of input uncertainty. In particular, the performed analysis provides an insight on how uncertainties prevent the correct operation of the voltage control. To avoid this, safety margins may be used, which however lead to higher costs for the associated control actions. Tests performed on a sample low voltage grid show the implications arising due the presence of uncertainties and highlight the benefits achievable when improving the accuracy of the monitoring system.

关键词： Active Distribution Grids Distributed Energy Resources Voltage control State Estimation Measurement Uncertainty Line Parameters Sensitivity Analysis

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Mitigating Current Spikes in VFD Induction Motor by Optimizing Motor Design and control Parameters 4

Mitigating Current Spikes in VFD Induction Motor by Optimizi...

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4th international conference on Electrical, Computer and Communication Technologies, ICECCT 2021

作者： John, Sunny V. Rama Rao, K.S. Srinivasa Rao, R. Nagarjuna Fertilizers and Chemicals Limited Electrical Department Kakinada India Jawaharlal Nehru Technological University School of Renewable Energy and Environment Kakinada India UCEK Jawaharlal Nehru Technological University Department of Electrical and Electronics Engineering Kakinada India

ISBN: (纸本)9781665414807

Variable Frequency Drives (VFD) are used extensively in process plants to save energy. While there are advantages in operating pumps using VFD driven induction motors, issues crop up when there is a change in operating conditions. this paper analyzes one such issue that was faced in a hazardous chemical process plant. the currents of a 730 HP, 4-pole VFD driven induction motor-pump system were found to be spiking abnormally when operated at low frequency. To mitigate the problem, the system is tested at various low frequency conditions. Prony and Hilbert methods are used to analyze the current spikes. Intelligent optimization methods like Simulated Annealing, Genetic Algorithm, Particle Swarm Optimization and Artificial Bee Colony are used to redesign the motor so as to achieve sufficient power at low frequency. Using the optimal redesign values obtained thus, the Taguchi method is operated on the control to get the optimal control parameters for the VFD. the results obtained are compared with the practical values recorded in the test conditions. they are found comparable thus validating the optimization methodology used in this paper. © 2021 IEEE.

关键词： Genetic algorithms

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Research on the Application of Gradient Descent Algorithm in Machine Learning 4

Research on the Application of Gradient Descent Algorithm in...

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4th international conference on Computer Network, Electronic and Automation, ICCNEA 2021

作者： Wang, Xin Yan, Liting Zhang, Qizhi School Of Electrical Engineering Xi'an Shiyou University Xi'an China Shaanxi Provincial Key Lab Of Oil And Gas Well Measurement And Control Technology Xi'an Shiyou University Xi'an China

ISBN: (纸本)9781665444866

the gradient descent algorithm is a type of optimization algorithm that is widely used to solve machine learning algorithm model parameters. through continuous iteration, it obtains the gradient of the objective function, gradually approaches the optimal solution of the objective function, and finally obtains the minimum loss function and related parameters. the gradient descent algorithm is frequently used in the solution process of logical regression, which is a common binary classification approach. this paper compares and analyzes the differences between batch gradient descent and its derivative algorithms - stochastic gradient descent algorithm and mini- batch gradient descent algorithm in terms of iteration number, loss function through experiments, and provides some suggestions on how to pick the best algorithm for the logistic regression binary task in machine learning. © 2021 IEEE.

关键词： Machine learning

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Simulation study on genetic algorithm control of hydrogen fuel cell gas supply system 4

Simulation study on genetic algorithm control of hydrogen fu...

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4th international conference on Mechanical, Electric and Industrial engineering, MEIE 2021

作者： Cheng, Rong Chen, Jing Cheng, Nanding Xiao, Chun School of Automation Wuhan University of Technology Wuhan430070 China Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory Xianhu Hydrogen Valley Foshan528200 China

Fuel cell as a new clean energy, its advantages of high efficiency, low emission and low noise have attracted the attention of domestic and foreign governments and scholars. To this end, based on the requirement analysis of the hydrogen fuel cell gas supply system, this paper focuses on the genetic algorithm optimization PID control strategy of the hydrogen fuel cell gas supply system. the simulation model is built on the Matlab/Simulink platform and compared with the conventional PID algorithm in the model. the simulation results show that the comprehensive index of PID control algorithm optimized by genetic algorithm is better than that of conventional PID algorithm, which proves the improvement effect of the proposed control strategy on the dynamic response of the gas supply system. © Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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11th international conference on advanced Materials Research, ICAMR 2021 in conjunction with 5th international conference on Civil and Building Materials, ICCBM 2021 and 4th international conference on advanced Energy Materials, ICAEM 2021

11th International Conference on Advanced Materials Research...

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11th international conference on advanced Materials Research, ICAMR 2021 in conjunction with 5th international conference on Civil and Building Materials, ICCBM 2021 and 4th international conference on advanced Energy Materials, ICAEM 2021

ISBN: (纸本)9783035718317

the proceedings contain 18 papers. the special focus in this conference is on advanced Materials Research. the topics include: Synthesis of the cofs: From design principle to synthetic reactions;cobalt molybdate incorporated thermoset composites: Preparation and characterization;influence study of the plastic deformation mode on the micro-indentation mechanical properties for the pure molybdenum;engineering modified mesoporous silica catalysts through porosity and surface acidity control for selective production of dme;improved coating adhesion on polymers with novel laser machining pre-treatment;comparative studies on vs2 bilayer and vs2/graphene heterostructure as the anodes of li ion battery;interaction of viscoelastic tube with inner nonuniform coating of variable thickness and rigid cylindrical insert;a 3d dynamic molecular dynamics simulation study: Diffusion of two types of sphere janus colloidal particles;fabrication and characterization the properties of decorative tile from white cement and waste glass powder;durability and mechanical properties of self-compacting concrete incorporating recovered filler from hot mix asphalt plants and recycled fine aggregate;support vector machine (Svm)-based optimal design procedure of fly ash blended concrete;r-curve characterization of crumb rubber modified asphalt mixtures incorporating warm mix additive at low temperatures;progressive collapse resisting capacity of rc flat slab buildings with varying spans and storey heights;effects of recycled aggregate replacement rate on compression mechanical behavior of concrete based on base force element method;make full advantage of new system-research on the design, construction and use of low-energy and industrialized icf house in guanzhong rural areas of china;one-part geopolymer synthesis of greek fly ash.

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Internal control Evaluation of Small and Micro Enterprises' Sales Process Based on Fuzzy Neural Network 4

Internal Control Evaluation of Small and Micro Enterprises' ...

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4th international conference on Computer Network, Electronic and Automation, ICCNEA 2021

作者： Zhang, Shuping Zhang, Dan An Kang University Department Of Economics And Management Shaanxi Ankang China

ISBN: (纸本)9781665444866

the identification of internal control defects is an important basis for judging whether an enterprise's internal control is effective, and an important part of internal control evaluation. this study applies fuzzy neural network technology to the identification of defects in internal control sales, discusses the establishment of an internal control defect identification model to realize the identification and diagnosis of internal control defects in the company's sales process, and solves the problem that the current defect identification is overly dependent on the professionalism and judgment of the evaluators and is mainly diagnosed after the fact, leading to lack of identification and early warning during the incident. this article provides a feasible path for the research and development of the automatic identification and tracking of internal control defects in the sales process of enterprises, and also provides an example for the discussion of the combination of artificial intelligence and internal control. © 2021 IEEE.

关键词： Fuzzy neural networks

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Speed Regulation of Converter-Driven DC Motors Via a Discrete-Time Reduced-Order GPIO with Genetic Algorithm 4

Speed Regulation of Converter-Driven DC Motors Via a Discret...

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4th international conference on Communication, Information and Computing Technology, ICCICT 2021

作者： Vikhe, P.S. Tiwary, N.K. Kadu, C.B. Mandhare, V.V. Jadhav, V.K. Department Instrumentation & Control Engineering Pravara Rural Engineering College Loni India Department of Computer Engineering Pravara Rural Engineering College Loni India Department Instrumentation & Control Engineering Pravara Rural Engineering College Loni India

ISBN: (纸本)9781665404303

the aim of this work is to design a speed controller for DC motor tuning PID controller. To obtain an output with minimum errors, PID parameters are selected using bio-inspired optimization technique of Genetic Algorithm. the system with second order is used to control the speed. this work deals with optimization approach based on bio-inspired in controllers and its merits over traditional is discussed and implemented with help of MATLAB Simulink. DC motor is interfaced to Arduino via Motor driver circuitry. Discrete-Time Reduced-Order GPIO with Genetic algorithm computes parameter of PID controller. thus, Arduino controls DC motor according to computed parameters. the optimization technique putforward in this work can also be applicable for systems having higher order, to provide effective system output having minimum errors. ©2021 IEEE

关键词： Genetic algorithms

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Study on the Identification, Risk Evaluation and control of the Dangerous and Harmful Factors of Power Enterprise Database 4

Study on the Identification, Risk Evaluation and Control of ...

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4th IEEE international conference on Electronics and Communication engineering, ICECE 2021

作者： Li, Xiaoxue Fang, Nengwei Li, Yunpeng Li, Yan Tan, Dong Fan, Bo Hu, Yuan Xin, Ya Big Data Center Beijing Aerospace Data Co. Ltd. Beijing China General Headquarters Beijing Aerospace Data Co. Ltd. Beijing China Conformity Department Institute of Technology International Standard Co. Ltd. Beijing China General Headquarters Chengdu Aerospace Science and Industry Big Data Institute Ltd Chengdu China

ISBN: (纸本)9781728194226

As an important part of the energy industry, power generation enterprises have complex production process and environment, and many hazard risk factors. the importance of its safety management has gradually become a consensus. Compared with traditional safety management methods, risk pre control emphasizes the planning of prevention and control in advance. Its theoretical basis is to comprehensively and systematically identify and evaluate all hazards and harmful factors. In order to determine the main risk sources and harmful factors, clarify the management focus and direction, formulate more targeted and advanced management measures, prevent the development of hidden dangers and accidents caused by improper risk control, and realize intrinsic safety. "4M" mainly comes from the theory of "safety management of human, machine, media and 4m elements" put forward by Japanese scholar Shigeru nishima. Under the guidance of 4m barrier theory, power enterprises have formed a set of risk pre control models for identifying, evaluating and formulating measures, and established "operation activity risk", "maintenance operation activity risk" and "regional environmental risk""Equipment", "failure risk" and "management risk" are five standard basic risk databases. the standard basic risk database identifies hazards, hazards and eco-environmental factors, comprehensively analyzes and evaluates hazard consequences, occurrence possibility, hazard degree and accident type, and puts forward corresponding control measures and behavior standards. ©2021 IEEE

关键词： Hazards

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Short-Term Photovoltaic Power Interval Prediction Based on VMD and GOA-KELM algorithms 4

Short-Term Photovoltaic Power Interval Prediction Based on V...

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4th IEEE international conference on Electronics Technology, ICET 2021

作者： Sun, Wenxuan Wang, Anna Zhang, Tao Northeastern University College of Information Science and Engineering Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781728176734

Affected by environmental factors such as irradiance and atmospheric temperature, the output power of photovoltaic power generation shows a high degree of randomness, intermittency and fluctuation. When large-scale photovoltaic energy is connected to the power grid, it will pose a challenge to the security and stability of the power grid. To solve the problem that the prediction accuracy of current photovoltaic power time series is not high and there is no reference interval for the prediction results, a photovoltaic short-term power interval prediction model based on variational mode decomposition (VMD) and improved grasshopper algorithm (GOA)-Kernel Extreme Learning Machine (KELM) is presented. the prediction model first uses VMD algorithm to decompose the original data and get several subsequences with lower complexity;then uses grey correlation method to select the subsequences with higher degree of association with the original data and divide them into low-frequency, medium-frequency and high-frequency sequences;then establishes a kernel limit learning machine prediction model optimized by grasshopper algorithm, and makes the subsequences with higher degree of association from the original sequence. the training of mid-frequency and high-frequency sequences obtains the set of prediction errors from the predicted and actual values and the model. Finally, the density curve of error function is calculated using the kernel density estimation method (KDE). Based on this curve, the prediction intervals with 85% and 90% confidence are established to realize the interval prediction of photovoltaic power. © 2021 IEEE.

关键词： Variational mode decomposition

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