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检索条件"任意字段=3rd IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024"

共 316 条记录，以下是91-100 订阅

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Control System of Bamboo Splitting Machine Based on STM32 and HMI 3

Control System of Bamboo Splitting Machine Based on STM32 an...

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3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Liang, Guojian Zhou, Shuwen Li, Chuang Lyu, Jiayang Luo, Hongbo Shi, Meijuan He, Dongkang Liuzhou Vocational and Technical College Liuzhou China

ISBN: (纸本)9798350380989

The general control system of bamboo splitting machine is controlled by Programmable Logic Controller (PLC), which is one of the most expensive devices in industrial automation control system. For some small enterprises or occasions with limited budget, the cost may become a limiting factor. Moreover, the technical threshold is high. Programming and debugging of PLC require professional technical personnel, and a relatively solid theoretical foundation of automation control is needed. Therefore, for some enterprises with lower technical levels, the use and maintenance may pose certain difficulties. To solve this problem, we have designed a set of bamboo splitting machine control system based on STM32 and touch screen. In the selection of HMI hardware, we choose a 2K touch screen with support for ten-point touch on the notebook computer, and equipped with a 64-bit processor chip i5-1135G7 based on the Intel core as the core processor. In terms of touch interface design, we introduce the comprehensive design of database technology and HMI interaction technology. In terms of HMI software interface programming, we adopt the method of object-oriented programming to achieve data communication transmission with the touch screen, upper computer and equipment. Through the Modbus-crc16 communication protocol, direct communication between STM32 and computer touch screen hardware is achieved. After debugging, the system runs stably with fast response speed and wide applicability. It reduces the reliance on traditional HMI hardware and speeds up the product development cycle. The design can achieve the desired display and control effects in the bamboo splitting machine system, providing a new way for the development of the bamboo splitting machine control system. © 2024 ieee.

关键词： bamboo cutting machine control system data interaction object-oriented

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A Comparison of YOLOv8 and DEtection TRansformer in the Context of Tear Meniscus Height Calculation Based on Ocular Surface Videos 3

A Comparison of YOLOv8 and DEtection TRansformer in the Cont...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Wang, Mini Han Lee, Simon Ming-Yuen Hou, Guanghui Liu, Yunxiao Liu, Haoyang Lin, Zhiyuan Zeng, Peijin Hu, Wenhan Yu, Yang Fang, Xiaoxiao Zhou, Ruoyu Chong, Kelvin K.L. The Faculty of Data Science City University of Macau China Zhuhai People's Hospital Zhuhai Hospital Affiliated with Jinan University Zhuhai China The Hong Kong Polytechnic University Hong Kong Guangdong Medical University Zhuhai China Guangdong Medical University Dongguan China Beijing Institute of Technology Zhuhai China Zhuhai Institute of Advanced Technology Chinese Academy of Sciences Zhuhai China Perspective Technology Group Zhuhai China

ISBN: (纸本)9798350380989

This study is the first investigation related to the application of advanced object detection algorithms, specifically You Only Look Once version 8 (YOLOv8) and DEtection TRansformer (DETR), in the realm of TMH detection. The research leverages a dataset comprising 152 ocular surface videos captured by the Keratograph 5M, undertaking a thorough comparison of architectural distinctions, advantages, and drawbacks between YOLOv8 and DETR. Performance metrics, encompassing mean Average Precision (mAP), specificity, recall, F1-score, and Frames Per Second (FPS), were meticulously evaluated, with an input size set at 640x640 pixels. The inquiry delves into the potential benefits of implementing AI-based methods for TMH detection, emphasizing their applications in ophthalmology and the management of dry eye conditions. The utilization of YOLOv8 and DETR algorithms facilitates automated analysis of anterior segment videos, markedly diminishing the manual workload for clinicians. Furthermore, these methodologies yield objective and consistent TMH measurements, thereby refining the precision of assessments and bolstering the reliability of dry eye diagnosis. Additionally, AI-based methods enable early detection of TMH alterations and timely interventions in cases of dry eye syndrome. © 2024 ieee.

关键词： Deep learning Object Detection Ophthalmology tear meniscus height Yolo

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Task Allocation of Financial Robots Based on RPA and big data algorithms 3

Task Allocation of Financial Robots Based on RPA and Big Dat...

引用

3rd ieee international conference on Distributed Computing and electrical Circuits and Electronics, ICDCECE 2024

作者： Wei, Qiqi Chongqing Vocational Institute Of Engineering JiangJin ChongQing China

ISBN: (纸本)9798350318609

With the continuous progress of technology, more and more enterprises are adopting automation technology to replace traditional financial work models. The use of financial robots can improve the accuracy and efficiency of task allocation, and improving the overall work efficiency of enterprises is still an urgent problem to be solved. This article combined Robotic Process Automation (RPA) and big data algorithms to optimize the fuzzy C-means clustering algorithm model by adjusting the membership function. The model was integrated into the RPA framework based on the characteristics of financial tasks and combined with big data algorithms to achieve task allocation. The experimental results showed that the highest accuracy of task allocation for financial robots based on RPA and big data algorithms was 98.63%. When assigning tasks of the same type, the accuracy was better than that of financial robots based on manually formulated rules, up to 14.51 %. This indicates that task allocation for financial robots based on RPA and big data algorithms can be applied in practice. © 2024 ieee.

关键词： big data

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Renewable energy generation prediction and optimization control based on intelligent algorithms and big data 3

Renewable energy generation prediction and optimization cont...

引用

3rd international conference on Energy, Power and electrical Technology, ICEPET 2024

作者： Jiang, Jiawei Qufu Normal University Rizhao China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352658

Renewable energy, as one of the main development directions in the current energy field, mainly faces issues such as power generation load prediction, production prediction, and facility maintenance prediction. Therefore, this article took the main direction of renewable energy, namely photovoltaic power generation, as an example and proposed collecting and analyzing massive data such as lighting and power generation faced by photovoltaic power generation systems through big data analysis. Then, based on intelligent algorithms (SaDE-BPNN), the power generation was predicted, and the system control was optimized by tracking the sun's concentrated light. Finally, this article validated the effectiveness of intelligent algorithms and big data analysis through comparative testing divided into three groups. The test results showed that the accuracy of using only the LSTM (Long Short-Term Memory) prediction model was 87.1%. The accuracy of further adding big data analysis was 89.8%, and the accuracy of further adding intelligent algorithms was 96.4%. Therefore, this study found that intelligent algorithms and big data analysis could effectively improve the accuracy of renewable energy generation prediction. © 2024 ieee.

关键词： data accuracy

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Research on User Demand Mining and Repurchase Behavior Prediction Algorithm Selection Based on big data

Research on User Demand Mining and Repurchase Behavior Predi...

引用

electrical engineering, big data and algorithms (eebda), ieee international conference on

作者： Tingwei Zhou Shanghai University Shanghai China

Based on the text data of authoritative skin care community, this study analyzes the user's needs and summarizes six topics on the premise that it has the option of repurchase intention. We need to calculate the emotional scores of six topics of each text data and contact the repurchase intention, thus constructing a feature data set, and then exploring which machine learning method is used to predict the repurchase behavior of online community review texts, which is relatively more accurate and reliable.

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Automatic Machine Learning Participation in Power Load Forecasting Under the Background of big data 3

Automatic Machine Learning Participation in Power Load Forec...

引用

3rd international conference on Energy, Power and electrical Technology, ICEPET 2024

作者： Zhang, Xueqiu Han, Jinshan North China Electric Power University School of Economics and Management Beijing China

ISBN: (纸本)9798350352658

Power load forecasting is one of the important tasks in controlling system costs, and accurate and effective load forecasting can reasonably arrange the operating status of power grid generators. Machine learning, as an important prediction method, has gradually become an important choice for complex load forecasting. However, due to the numerous machine learning methods, it is difficult to accurately and effectively select suitable algorithms in different regions when selecting prediction methods, and the parameter settings of algorithms often require debugging. This article is based on the automatic machine learning platform PyCaret, analyzing the convenience and effectiveness of automatic selection algorithms, and comparing them with the prediction accuracy of grey prediction and neural network algorithms. The results indicate that using existing platforms can accurately fit data and achieve portable and effective power load forecasting. © 2024 ieee.

关键词： Load forecasting Machine learning PyCaret

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big data Analytics for electrical Systems using Machine Learning algorithms 3

Big Data Analytics for Electrical Systems using Machine Lear...

引用

3rd ieee international conference on Technology, engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Satyanarayana, Salava V. Madhavi, Pillalamarri Hyderabad Institute of Technology and Management Electrical and Electronics Engineering Hyderabad India

ISBN: (纸本)9798350397819

big data Analytics plays a vital role in every electrical industry to analyze the large amount of data received from their dispatch centers. Typically, data retrieved from electrical systems like Generation, Transmission, and distribution will be analyzed using many control systems like SCADA and HMI without any human intervention. To analyze this data as per industry 4.0, Every system should be automated by integrating the data into the internet of things along with cyber security systems. With consideration of industry 4.0 standards, in view of effective optimized operational maintenance of electrical systems in the future, this paper provides intelligent predicted data by analyzing current and existing data that is fetching from electrical systems i.e., Various state electrical utility data files. The available data of electrical systems can be analyzed by using various Supervised Machine learning algorithms and this paper verified the accuracy of various machine learning algorithms by analyzing the predicted data by each algorithm. © 2023 ieee.

关键词： data Analytics

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Neural Network algorithms and big data Technology in the Construction of Intelligent data Models 3

Neural Network Algorithms and Big Data Technology in the Con...

引用

3rd ieee international conference on Distributed Computing and electrical Circuits and Electronics, ICDCECE 2024

作者： Ma, Lijie He, Yong Wuhan Donghu University Foundational Courses Department Hubei Wuhan China

ISBN: (纸本)9798350318609

It is a very difficult question to process and store large-scale data. The purpose of this article is to explore the application of neural network algorithms and big data technologies in the construction of intelligent data models. The LSTM model used in the article extracts features from the input data through learning, and classifies, predicts, and makes decisions based on these features;secondly, data mining techniques are selected to discover potential patterns and correlation laws, and provide more comprehensive information support for the construction of intelligent data models. The article summarizes the application fields of neural network algorithms and big data technologies in the construction of intelligent data models, and shows the great potential of neural network algorithms and big data technologies in improving data analysis and decision-making capabilities. The research results show that the F1 value of the method in this paper is between O. 85-0. 95, and the combination of neural network algorithm and big data technology has achieved remarkable results in the construction of intelligent data models. © 2024 ieee.

关键词： Long short-term memory

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Application of Computer big data Technology in Marine Ecological Diversity Detection

Application of Computer Big Data Technology in Marine Ecolog...

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electrical engineering, big data and algorithms (eebda), ieee international conference on

作者： Zhang Yubai Xu Daohuan Zhou Xiangjun Shandong Marine Forecast and Hazard Mitigation Service Qingdao China

In this paper, the Access2000 software is used for classification entry, statistical analysis, comprehensive assessment and external input of Marine ecological data. VB-ADO data access mode is used to manage the database. We call the corresponding data for processing to build a complete Marine fishery ecological environment information database. This database can realize the input of phytoplankton, zooplankton, fish eggs and larvae, residual toxins of organisms and so on. It has many services such as statistical query, comprehensive evaluation and output printing. The system can carry out the investigation and assessment of the fish resources in the sea area of China. This system has important theoretical and practical significance for the ecological environment assessment and management of Marine areas in China.

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Research on Visualization Technology of data Mining Based on rd-SOM (Radar-Self-Organizing Map) Clustering Algorithm 3

Research on Visualization Technology of Data Mining Based on...

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3rd international conference on Cloud Computing, big data Application and Software engineering, CBASE 2024

作者： Ma, Bing Li, Dongsheng Liu, Xiaotan Mai, Yiyuan Qin, Shasha PLAA Infantry College PLAA Infantry College Shijiaozhuang Hebei China Hunan Changsha75841 China Hainan Hospital of Chinese PLA General Hospital Hainan Sanya China

ISBN: (纸本)9798331506582

With the continuous development of data storage, analysis, processing and other technologies, people are eager to visualize the mining process of complex data, and data mining visualization technology is gradually applied to all fields of society, which greatly improves the efficiency of data mining [1]. The author starts with data visualization technology, studies data preprocessing and algorithms, and proposes data mining visualization technology of rd-SOM clustering algorithm by analyzing the existing problems in the current SOM clustering algorithm, so as to improve the current algorithm and obtain higher data utilization rate. © 2024 ieee.

关键词： data assimilation

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