检索结果-内蒙古大学图书馆

On-line data splicing power flow analysis method based on sensitivity

ENERGY REPORTS 2021年 7卷 326-333页

作者： Lu, Jun Zhang, Lu Lu Shi, Dong Yu Li, Tie Tang, Jun Ci Cui, Dai China Elect Power Res Inst Power Syst Res Inst 15 Xiaoying East Rd Beijing 100192 Peoples R China State Grid Liaoning Elect Power Supply Co Ltd Ningbo Rd 18 Shenyang 110006 Peoples R China

This paper proposes an online data splicing power flow analysis method based on sensitivity analysis. Since the step-down transformer in the whole network data is usually equivalent to the 220 kV side, the equipment below 220 kV is not modeled in detail, and the provincial network data is modeled to 110kV and 35 kV voltage level equipment in detail. Different levels of modeling have a greater impact on the accuracy of stability analysis and calculation. Therefore, the purpose of improving data accuracy is achieved by splicing the entire network data (external network) and provincial network data (internal network). This paper is based on the sensitivity analysis method to stabilize the tie-line power by adjusting the output of the external network units, and form the whole network data that can accurately analyze the stability characteristics of the provincial network. The problem of power flow deviation caused by the voltage and angle deviation of the nodes at both ends of the regional tie line during the data splicing process is solved. Through the actual application of splicing the entire network and Hunan Provincial Network data, the effectiveness and necessity of the proposed method have been verified. (C) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： data splicing Sensitivity Power control

来源：评论

学校读者我要写书评

暂无评论

Robust Adaptive Cubature Kalman Filter for Attitude Determination in Wearable Inertial Sensor Networks 17th

Robust Adaptive Cubature Kalman Filter for Attitude Determin...

引用

17th International conference on Wireless Algorithms, Systems, and Applications (WASA)

作者： Zhao, Hongkai Wang, Huihui Wang, Zhelong Liu, Long Qiu, Sen Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China Dalian Univ Technol Key Lab Intelligent Control & Optimizat Ind Equip Minist Educ Dalian 116024 Peoples R China Dalian Neusoft Univ Informat Dalian 116024 Peoples R China

ISBN: (纸本)9783031192135;9783031192142

Attitude analysis and recognition can be applied in wearable computing for medical assistance, motor-function assessment and dexterous human-robot interaction. The main problems, however, are serious drift and instability during traditional motion measurement fusion methods due to the high dynamic complexity of limb movements. To the best of our knowledge, it is the first attempt to employ an adaptive robust cubature Kalman filtering algorithm in the human attitude analysis based on wearable inertial sensors with time-varying state-process noise. Experiment results show that the adaptive robust CKF algorithm based on quaternion and gyroscope error modeling proposed in this paper can solve motion attitude solution. Lastly, we compare our method with CKF and EKF algorithm, the proposed algorithm can effectively improve the precision of attitude analysis.

关键词： Cubature Kalman filter Body sensor network Sensor fusion Adaptive factor Robust filter

来源：评论

学校读者我要写书评

暂无评论

Intelligent Quality control System for Polymeric Films Based on Big data processing and Mathematical modeling of Technological processes

Intelligent Quality Control System for Polymeric Films Based...

引用

International conference on control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Tamara Chistyakova Andrey Polosin Anton Damrin Computer-Aided Design and Control System Department Saint Petersburg State Institute of Technology (Technical University) Saint Petersburg Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

An intelligent system is described for the formation of advice to managerial production staff on quality control of polymeric films of a wide range in a routine mode and in case of emergency situations that are associated with defective films. The system is designed to control extrusion calendering production of films. The production is distinguished by its multi-stage nature, flexibility of the hardware design of the stages, the presence of a recycle for returning waste for processing, a large number and complexity of connections between the parameters of raw materials, equipment, technological mode and product quality indicators, the lack of quality control of the intermediate (extrudate) from which the film is made. Production data is characterized by a large volume, high generation velocity and a variety of sources. The complexity of the control object has required the creation of algorithms for processing its big data to predict product quality based on machine learning methods and the construction of multivariate models for describing an industrial facility. Regression analysis, artificial neural networks and boosting decision trees are used to build predictive models. The choice of method depends on the type of distribution law of production data, their volume and requirements for accuracy and processing speed. The models for describing an industrial facility are deterministic mathematical models of technological processes at the production stages for calculating unmonitored quality indicators of extrudate and film, a base of expert knowledge about emergency situations, their reasons and recommendations for elimination for forming advice to operators, as well as a data bank of film types, production line configurations, monitored and calculated production parameters for adjusting the system to hardware and technological design of production and the range of its products. Testing using data from industrial production of polyvinyl chloride-based packaging films

关键词： Films process control Production Quality control Predictive models control systems Mathematical models data models Raw materials Polymers

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection and Functional Testing for Automotive CAN Communication

Anomaly Detection and Functional Testing for Automotive CAN ...

引用

Annual IEEE Systems conference

作者： Md Al Maruf Akramul Azim Department of Electrical Computer and Software Engineering Ontario Tech University Canada

ISBN: (数字)9798350358803

ISBN: (纸本)9798350358810

Integrated vehicle dynamics control systems require real-time communication among their components to improve performance and process efficiency. This communication relies on the use of sensor data, hardware interfaces, transmission protocols, and control strategies, which all have an impact on the system’s reliability. However, as the number of functionalized electronic control units (ECUs) and wiring systems increases, advanced control systems encounter complex functional and cybersecurity issues. To mitigate this complexity, the automotive industry widely employs the controller Area Network (CAN) communication bus. Nevertheless, the inherent vulnerabilities of CAN and the rich interfaces with external environments increase the systems’ susceptibility to soft errors caused by uncertainty factors such as process changes. Therefore, detecting abnormalities in automotive CAN communication is *** paper introduces a machine learning (ML)-based anomaly detection framework to identify anomalies through CAN messages, extracting key features and employing ML models for predictive analysis. It also uses Triple Modular Redundancy (TMR) for trusted ML computation in anomaly detection. The study provides a comparative analysis of various ML algorithms, highlighting the effectiveness of Deep Neural Networks in identifying anomalies within both synthetic and real Hyundai CAN data for a wheel speed control system, showcasing the framework’s capability to enhance system reliability and security.

关键词： Protocols Machine learning algorithms Accuracy Computational modeling Artificial neural networks control systems Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Utilizing Modern Large Language Models (LLM) for Financial Trend analysis and Digest Creation

Utilizing Modern Large Language Models (LLM) for Financial T...

引用

International conference on control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Andrei Lazarev Dmitrii Sedov Department of Control and Applied Mathematics Moscow Institute of Physics and Technology Moscow Russia Institute for Statistical Studies and Economics of Knowledge HSE University Moscow Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

The exponential growth of information presents a significant challenge for researchers and professionals seeking to remain at the forefront of their fields and this paper introduces an innovative framework for automatically generating insightful financial digests using the power of Large Language Models (LLMs), specifically Google's Gemini Pro. By leveraging a combination of data extraction from OpenAlex, strategic prompt engineering, and LLM-driven analysis, we demonstrate the automated example of creating a comprehensive digests that generalize key findings, identify emerging trends. This approach addresses the limitations of traditional analysis methods, enabling the efficient processing of vast amounts of unstructured data and the delivery of actionable insights in an easily digestible format. This paper describes how LLMs work in simple words and how we can use their power to help researchers and scholars save their time and stay informed about current trends. Our study includes step-by-step process, from data acquisition and JSON construction to interaction with Gemini and the automated generation of PDF reports, including a link to the project's GitHub repository for broader accessibility and further development.

关键词： Navigation Large language models Finance Market research Technology forecasting Mathematical models Internet Prompt engineering data mining Software development management

来源：评论

学校读者我要写书评

暂无评论

ADM1-Guided Optimization of anaerobic digestion Model Parameters via Whale Optimization Algorithm

ADM1-Guided Optimization of anaerobic digestion Model Parame...

引用

Advances in Electrical and Communication Technologies (ICAECOT), International conference on

作者： Messili Oualid Chaabna Abdelhani Semcheddine Samia Power Electronic and Industrial Control Laboratory (LEPCI) UFAS Setif1 Setif Algeria

ISBN: (数字)9798350353754

ISBN: (纸本)9798350353761

Anaerobic Digestion (AD) technology, known for its waste recycling and environmental clean-up capabilities, also generates renewable energy in the form of biogas. The need to reduce dependence on fossil fuels has extensively stimulated interest in this process. The process is known for its complexity, high sensitivity, and potential for instability, which is inherently reflected in the models describing it. Models contain uncertain parameters and highly sensitive to process noise. Parameter identification plays a crucial role during modeling and is a delicate task preceding control law development. It is mandatory to have the best possible estimates of a model that guarantees efficient predictions. This paper focuses on the optimization of stoichiometric and kinetic coefficients of the Acidogenesis Methanogenesis 2 model (AM2). We present in this study the use of the Whale Optimization Algorithm (WOA) to optimize AM2 model parameters and validate the results using data acquired from a Anaerobic Digestion Model $\mathbf{N}^{\circ} 01$ (ADM1). The identification algorithm was implemented in MATLAB 2018. To validate the effectiveness of our proposed approach, we conduct a comparative analysis with Genetic Algorithm (GA). The results, despite certain limitations, underscore the robustness of WOA for parameter estimation.

关键词： Renewable energy sources Parameter estimation Sensitivity Biological system modeling Whale optimization algorithms data models Robustness Recycling Optimization Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

ISSM and 6S Management Model in Computer Laboratory Big data- A Case Study of Sanda University

ISSM and 6S Management Model in Computer Laboratory Big Data...

引用

Informatics Education and Computer Technology Applications (IECA), International conference o

作者： Xiang Chen Yiching Hsieh Jing Cao Jincong Chen Chaochun Shen College of Art Design and Media Sanda University Shanghai China

ISBN: (数字)9798350375336

ISBN: (纸本)9798350375343

Multimedia computer labs are an important part of systematic education for universities, and the management and operation of the labs are related to students and computer education. This study analyzes the “Information System Success Model” (ISSM) from DeLong & McLean (2003) takes the computer labs of Sanda University as a case study, and collects and analyzes the data from the labs in the past three years to provide big data support for the labs’ operation, and helps to optimize the labs’ resource allocation after the research and analysis of the 6S management model.

关键词： Analytical models Systematics Computational modeling Laboratories Education process control data models

来源：评论

学校读者我要写书评

暂无评论

Aspect-Based Sentiment analysis for Virtual Reality Roaming System

Aspect-Based Sentiment Analysis for Virtual Reality Roaming ...

引用

International conference on Communications, Information System and Computer Engineering (CISCE)

作者： Biqing Wang School of Mathematics and Computer Tongling University Tongling China

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

Through sentiment analysis technology, NPCs (Non-Player-controlled Character) in virtual reality roaming system are able to recognize the user's emotional state and react accordingly. In aspect-based sentiment analysis, NLP techniques often use manually constructed features combined with machine learning models for classification. However, these methods are complex in feature engineering and lack generalisation capabilities. At the same time, traditional models often ignore the importance of local context for the correct classification of the sentiment polarity of aspect term, and process all input data indiscriminately. In order to solve the above problems and improve the processing efficiency of aspect-based sentiment analysis, an attention weight decay mechanism is proposed. On this basis, a multi-module model is constructed by fusing BERT, BiLSTM and TextCNN, and the performance of the model is verified experimentally. This model can be better applied to virtual reality roaming systems.

关键词： Solid modeling Sentiment analysis Analytical models Recurrent neural networks Computational modeling Virtual reality Bidirectional control

来源：评论

学校读者我要写书评

暂无评论

Intelligent Assisted Navigation for Ships Using Edge Computing and Neural Networks

Intelligent Assisted Navigation for Ships Using Edge Computi...

引用

Intelligent Computing and Robotics (ICICR), International conference on

作者： Wenge Cheng Department of Maritime Technology Tianjin Maritime College Tianjin China

ISBN: (数字)9798350372274

ISBN: (纸本)9798350372281

In order to meet the requirements of high real-time and stability in the process of ship navigation, this paper applies an intelligent auxiliary means based on edge computing and convolutional neural network (CNN). The edge computing platform is deployed on the ship, and sensors and cameras are used to collect surrounding data. The convolutional neural network models are trained to accurately recognize and classify different types of obstacles, and real-time environmental perception and analysis are performed. Intelligent driving assistance decisions such as automatic obstacle avoidance, path planning, and speed control are provided based on the analysis results. The research results indicate that the average recovery time of the system is between 5.8 minutes and 29.5 minutes, with an accuracy of 0.97 in obstacle recognition tasks. The method can achieve intelligent assistance for ship navigation with high real-time performance and stability.

关键词： Navigation Computational modeling Velocity control Real-time systems Stability analysis Path planning Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

analysis Model for Decentralized Lending Protocols 22

Analysis Model for Decentralized Lending Protocols

引用

11th International Symposium on Information and Communication Technology, SoICT 2022

作者： Pham, Viet-Bang Trinh, Tuan-Dat Hanoi University of Science and Technology Viet Nam

ISBN: (纸本)9781450397254

Decentralized Finance (DeFi)-An ecosystem of financial applications built on top of blockchain technology-has kept powering ahead and attracted a large amount of capital in just a few years. As the core part of the DeFi ecosystem, decentralized lending protocols allow users to become lenders or borrowers in a completely decentralized fashion, such that an individual has complete control over their funds at all times. Collecting, analyzing, and visualizing lending data are crucial as these lending protocols are growing steadily. This paper presents an analysis model for decentralized lending protocols. Our main contributions are as follows. (i) We analyze and compare the top lending protocols;(ii) We present a general model to collect and process a large amount of data from multiple lending protocols in an exact and efficient manner;(iii) We design and implement a lending visualization system with various charts divided into three categories, i.e., lending market overview, token analysis, and user analysis. © 2022 ACM.

关键词： Finance

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：