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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68880 条记录，以下是1431-1440 订阅

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Research on 3D Target State Estimation technology of Helicopter Fire Control System 2

Research on 3D Target State Estimation Technology of Helicop...

引用

2nd international conference on Artificial Intelligence and computer Information technology, AICIT 2023

作者： Tian, Jia Zhai, Mo Zhang, Zhiqi Chen, Hongzheng Sheng, Shouzhao College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350302950

In view of the inaccuracy of target state estimation in helicopter high maneuvering flight and the fact that a single model can not cover all maneuvering forms of the target, considering the timeliness and accuracy of the solution of the fire control system, the target model selected by the Interacting Multiple Model must be simple enough. An interacting multiple model algorithm based on constant velocity, constant acceleration and coordinated turning motion model are proposed in this paper. The algorithm is combined with the smoothing algorithm to improve the reliability and accuracy of maneuvering target state estimation, and the extended Kalman filter is used to improve the adaptive ability and robustness of the algorithm. The simulation results show that the three-dimensional target state estimation technology based on interacting multiple model smoothing algorithm improves the accuracy and reliability of target state estimation and has good practical application value. © 2023 IEEE.

关键词： Fire control systems

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Sensor Subsets Selection for ASPN Based on Environment Awareness 20

Sensor Subsets Selection for ASPN Based on Environment Aware...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Liu, Chunzhi Gao, Wei Fan, Shiwei Zhang, Ya Wang, Qingxin Li, Guangmin Wang, Yanyan Harbin Institute of Technology School of Instrumentation Science and Engineering 92 Xidazhi Street Heilongjiang Harbin China

ISBN: (纸本)9798350320831

This paper studies the sensor subset selection problem in the All-Source Positioning and Navigation (ASPN). Our research is based on the factor graph structure, which realizes the plug-and-play function of sensors. We summary the influence of the environment on sensors, and obtain an environment description method suitable for this problem. Sensor data evaluation is based on the DBSCAN clustering algorithm. Experimental results demonstrate that our approach can realize sensor selection and switching under dynamic conditions. © 2023 IEEE.

关键词： Clustering algorithms

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Fatigue Load Prediction of Large Wind Turbine by Big Data and Deep Learning

Fatigue Load Prediction of Large Wind Turbine by Big Data an...

引用

2023 IEEE international conference on Electrical, automation and computer Engineering, ICEACE 2023

作者： Wu, Jiayue Yang, Qinmin Jin, Nanlin Xxi'An Jiaotong-Liverpool University Low Carbon Electrical Power and Energy Technology Suzhou China College of Control Science and Engineering Zhejiang University Hangzhou China Xi'An Jiaotong-Liverpool University Department of Computing Suzhou China

ISBN: (纸本)9798350309614

This paper introduces a fatigue load prediction framework for the nacelle of wind turbines utilizing operational data sourced from the supervisory control and data acquisition (SCADA) system of a Wind Farm. The primary objective revolves around achieving precise fatigue load predictions for the nacelle, forecasting 15 minutes in advance. Firstly, a series of data preprocessing steps were implemented on the wind turbine data procured from the SCADA system to enhance the model's generalization capability and robustness, including 3-Sigma outlier detection, sample point selection, as well as filtering and de-noising techniques. Then, the gate recurrent unit (GRU) was tuned and trained as the optimal model for long time-series forecasting of SCADA parameter channels. Subsequently, the support vector regression (SVR) model, refined with grid search methodology, was employed to establish the intricate relationship between SCADA parameters and fatigue loads. Finally, the predicted SCADA parameter values were fed into the optimized SVR model to derive fatigue load prediction results for wind turbines. Experimental results indicated that the proposed model framework can effectively predict fatigue loads on the nacelle of wind turbines utilizing the SCADA data in real scenarios. © 2023 IEEE.

关键词： GRU SCADA system.fatigue loads SVR wind turbine

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Multi-Objective Optimal Control of Wastewater Treatment Processes Constrainted by Energy-Saving and Effluent Qualities 6

Multi-Objective Optimal Control of Wastewater Treatment Proc...

引用

6th international conference on Robotics, Control and automation Engineering, RCAE 2023

作者： Zhang, Jing Yan, Haoming Chen, Hongtian Xu, Shuiqing Liu, Yiqi School of Automation Science & Engineering South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou510640 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China College of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China

ISBN: (纸本)9798350315301

Considering the high energy consumption problem in the wastewater treatment process, this paper proposes a multi-objective optimization control scheme based on NSGA-II algorithm. The proposed scheme can not only ensures meet effluent quality requirements but also can achieves energy cost savings. This method takes the aeration energy consumption and pumping energy consumption of the system as the optimization goal with the effluent water quality being the constraint condition. At the same time, the adaptive fuzzy PID controller is designed to ensure the control accuracy and stability of the controlled system. The results of simulation experiments validated in benchmark simulation platform, BSM1, show that, compared with PI control and single-objective optimization control, the proposed optimization scheme in this paper can achieve the desired quality of the effluent water withmore energy-saving. © 2023 IEEE.

关键词： Energy utilization

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Improving the Accuracy of Iris Recognition Based on Attention Mechanism 6

Improving the Accuracy of Iris Recognition Based on Attentio...

引用

6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Wang, Zike Wang, Jianguo Zhong, Lei Xi'an Technological University School of Computer Science and Engineering Xi'an China Xi'an Technological University Research Institute of Artificial Intelligence and Data Science Xi'an China

ISBN: (纸本)9798350305388

Iris recognition algorithms are becoming more and more widely used in daily life, and the accuracy requirements for iris recognition algorithms are getting higher and higher. Therefore, in this paper, an improved Shufflenetv2 algorithm is proposed as a way to improve the speed and accuracy of current iris recognition algorithms in daily life. In this paper, deep and shallow features are filtered by using the channel attention mechanism, which enables the model to acquire feature representations of both underlying and high-level semantics. In addition, in the loss function, this paper uses the focal loss function instead of the cross entropy loss function to achieve a solution to the imbalance between the number of positive and negative samples and prevent too much learning to negative sample features. By validating on the CASIA-Iris-Thousand dataset, which is commonly used in iris recognition tasks, the proposed model achieves an equal error rate (EER) of 1.66% compared to the Shufflenetv2 model, which has an EER of 5.3%, and optimizes by 3.64%. The model proposed in this paper can effectively improve the accuracy of iris recognition. © 2023 IEEE.

关键词： Convolutional neural networks

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Optimization of SVM Based on IPSO Algorithm for Tool Life Prediction 6

Optimization of SVM Based on IPSO Algorithm for Tool Life Pr...

引用

6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Gao, Xianghong Cao, Yan Xi'an Technological University School of Mechanical and Electrical Engineering Xi'an China Xi'an Technological University School of Computer Science and Engineering Xi'an China

ISBN: (纸本)9798350305388

As the basic parts of workshop processing, the life of the tool will affect the processing efficiency and processing quality, and the life of the tool will be affected by a variety of uncertain factors in the processing process, which makes it difficult to accurately predict. In order to improve the prediction accuracy, an improved IPSO algorithm was proposed to optimize the penalty factor c and kernel parameter g of SVM based on particle swarm optimization (PSO). Firstly, the influencing parameters of tool life are analyzed and the experimental data are extracted, and then the data is brought into the IPSO-SVM model to obtain the predicted data. IPSO algorithm can realize the adaptive change of inertia weight and introduce asynchronous learning formula to dynamically adjust the learning factor, which can effectively improve the prediction accuracy of tool life. Compared with the traditional PSO-SVM prediction model, the average relative error and average absolute error of IPSO-SVM are reduced by 5.275% and 5.006% respectively, which indicates that the SVM model optimized by IPSO algorithm has higher prediction accuracy. © 2023 IEEE.

关键词： Forecasting

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QRAM: Quantum technology for Random Access Memory 26

QRAM: Quantum Technology for Random Access Memory

引用

26th international conference on computer and Information technology, ICCIT 2023

作者： Tabassum, Tamanna Akter, Fatema Ahsanullah University of Science and Technology Dept of Computer Science and Engineering Bangladesh Green University Bangladesh Dept of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350359015

The domain of computing, commonly referred to as quantum computing, is dedicated to the development of computer technology that is based on the fundamental principles of quantum theory, elucidates the behavior of matter and energy on the atomic and subatomic scales. In the realm of quantum computing, quantum memory serves as the quantum-mechanical equivalent of conventional computer memory. Quantum memory plays a pivotal role in the development of several quantum information processing devices, including but not limited to a synchronization tool that enables the matching of multiple procedures in a quantum computer, a quantum gate that preserves the identity of any given state, and a method for transforming preset photons into on-demand photons. To take advantage of the fundamental capabilities of quantum computing to perform parallel calculations at incredibly high speeds, a Quantum-based Random Access Memory (QRAM) architecture is proposed herein. This architecture utilizes basic quantum CNOT, V, and V+ gate operations to enable the implementation of basic quantum AND, OR, NOT, and NOR operations, respectively. © 2023 IEEE.

关键词： Ancilla bit QRAM Architecture Quantum RAM Cell

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Robotic process automation of calculating investments in a business project 23

Robotic process automation of calculating investments in a b...

引用

12th international conference on Software and computer Applications, ICSCA 2023

作者： Hafenscherer, Michael Mezhuyev, Vitaliy Tschand, Martin FH Joanneum University of Applied Sciences Werk-VI-Straße 46 Kapfenberg8605 Austria

ISBN: (纸本)9781450398589

Robotic process automation (RPA) technology currently gains importance in business practice as it enables the automation of business processes and thus a significant increase in business efficiency. This paper aims to investigate the impact of RPA on the specific business process of investment costing using a software robot for the projects of an energy supply company. For this purpose, an automated calculation tool was developed with Microsoft Power Apps and Microsoft Power Automate. The application of the proposed tool shows potential by significantly reducing the working time of employees for recalculating project investments based on different parameters. The developed RPA tool can be extended to calculate other types of standard investments. The results are aimed at managers pursuing the potential for business process automation. © 2023 Copyright held by the owner/author(s).

关键词： Robotics

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Seismic landslide detection based on Transformer and RNN algorithm

Seismic landslide detection based on Transformer and RNN alg...

引用

2023 IEEE international conference on Sensors, Electronics and computer Engineering, ICSECE 2023

作者： Yang, Qingru Zhang, Xin Xie, Yuxuan Huang, Shuhong Kong, Junfeng Zhang, Xiaoyu Chengdu China Chengdu University of Technology College of Mechanical and Electrical Engineering Chengdu China Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu China

ISBN: (纸本)9798350313734

This paper proposes a seismic landslide detection method based on Transformer and RNN algorithm. This method uses seismic data and topographic data as inputs, encodes the data through the Transformer model, and then inputs the encoded data into the RNN model for classification. In the training process, we use the cross entropy loss function and Adam optimizer. To verify the effectiveness of the method, we used public data sets for experiments, and the results show that our proposed method can significantly improve the accuracy of seismic landslide detection. In addition, we interpret the results by visualization method and analyze the performance of the model under different parameters. Our method is expected to provide effective support for earthquake landslide prediction and early warning. © 2023 IEEE.

关键词： Seismology

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Street Light Monitoring and Controlling System Using RaspberryPi and Zigbee Protocol 7

Street Light Monitoring and Controlling System Using Raspber...

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2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Gokhale, Pratik Deshpande, Shantanu Page, Saurabh Bagul, Mandar Bundele, Ashwini Pune Institute of Computer Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350304268

Street Lighting System is a crucial part of society's amenities and environment. Today's systems consume enormous amounts of electrical energy, for the automation of switches on/off of street lights. This results in a huge loss of energy and money at the same time which needs an efficient system to be developed. We propose a Smart Lighting System which replaces the traditional timer and photocell-based street lighting and outdoor lighting control. It is a complete integrated solution consisting of a Zigbee-based Node integrated with every street light fixture or outdoor lighting fixture, and operating software that uses a Master-Slave concept to control every Node (Slave) from the coordinator module (Master). With energy-saving initiatives, putting the latest technologies in use, this system has the potential to save energy as well as be an effective adaptable way of constructing a lighting system. The system will be deployed on a cloud platform through which the application is remotely accessible. © 2023 IEEE.

关键词： IOT based system Lighting System Raspberry Pi Zigbee

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