检索结果-内蒙古大学图书馆

5th Asia Energy and Electrical Engineering symposium (AEEES)

作者： Zhang, Ruixiang Yuan, Meng Jin, Zhaorui Zhu, Ziyu Chen, Yuanhui Wang, Yu Sun, Yaojie Zhao, Longjun Fudan Univ Sch Informat Sci & Technol Shanghai Peoples R China Fudan Univ Inst Six Sect Econ Shanghai Peoples R China Fudan Univ Acad Engn & Technol Shanghai Peoples R China Shanghai Engn Res Ctr Artificial Intelligence & I Shanghai Peoples R China

ISBN: (纸本)9781665490542

Short-term load forecasting is necessary for the safety and high efficiency of power system. In recent years, a large number of artificial intelligence-based methods have been used for short-term load forecasting by researchers, among which deep learning methods such as long short-term memory (LSTM) has been proved to be better at load forecasting. However, in the process of constructing LSTM models, data processing and hyperparameter selection tend to depend on experience, resulting in relatively slow modeling speed. This study proposes a short-term load forecasting method with singular spectrum analysis (SSA), LSTM network and whale optimization algorithm (WOA). SSA is used to decompose and reorganize the load sequence, and the WOA is used to optimize the hyperparameters of the LSTM network. The results show that the proposed method performs better than the benchmark in the three counties of the United States used for verification and comparison, that is, SSA-WOA-LSTM can be used to improve the accuracy of the short-term load forecasting.

关键词： short term load forecasting singular spectrum analysis whale optimization algorithm long short-term memory hyperparameter optimization

来源：评论

学校读者我要写书评

暂无评论

Visualizing Program Behavior: A Study of Enhanced Program Diagrams Using LLM

Visualizing Program Behavior: A Study of Enhanced Program Di...

引用

Frontiers in Education (FIE) Conference

作者： Ying Li Runze Yang ShiJie Gui Peng Shi Xuefei Huang Da Yang Xiaozhou Zhang Yiming Gai School of Computer Science and Engineering Beihang University Beijing China Key Laboratory of Data Science and Intelligent Computing International Innovation InstituteBeihang University Hangzhou China

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This paper aims to address the difficulties faced by novice programmers in grasping code structure and execution flow, improving programming thinking, and pinpointing code errors with accuracy. It proposes providing students with program behavior diagrams based on large language models (LLMs) and visualization techniques to achieve personalized guidance. Specifically, these program behavior diagrams include programming thinking visualization diagrams and code vulnerability visualization diagrams. A programming thinking visualization diagram employs static code analysis to gather code structure information, combined with the structured chain-of-thought method to collectively optimize the LLM. This enables the LLM to explain each interpretable part of the code from top to bottom, detailing the programming concepts, and displaying them on a modularized code structure diagram. The code vulnerability visualization diagram primarily utilizes the fine-tuned LLM, optimizing it based on program analysis and clustering analysis methods to accurately identify vulnerabilities in student code and display them on a code flow diagram. Its feature is to visually display to students the error location, error information, and the impact of errors on program flow, rather than providing the programming answers. Lastly, through experiments and statistical analysis of actual teaching data, this paper serves a demonstration that the enhanced models used in the visualization diagram generation process have a noticeable effect on mainstream LLMs, and that visualization diagrams hold significant value for students at different stages of learning.

关键词： Location awareness Analytical models Codes Accuracy Statistical analysis large language models Education data visualization Optimization methods Programming profession

来源：评论

学校读者我要写书评

暂无评论

Generating Cardiovascular data by Integration of Physiological Information

Generating Cardiovascular Data by Integration of Physiologic...

引用

Computational Intelligence in Health and Medicine (CIHM), ieee symposium on

作者： Johannes Kummert Alexander Schulz Moriz Habigt Maike Stemmler Christina Kohler Dirk Abel Rolf Rossaint Barbara Hammer Machine Learning Group Bielefeld University Bielefeld Germany Anaesthesiology Clinic RWTH Aachen University Aachen Germany Institute of Automatic Control RWTH Aachen University Aachen Germany

ISBN: (数字)9798331508333

ISBN: (纸本)9798331508340

Medical data is a valuable resource that is under privacy constraints and often requires a substantial effort and cost to obtain. This is the case for physiological cardiovascular data that is among others utilized to develop assistive heart devices. In the present work, we aim to improve a GAN based generative approach from the literature by integrating physiological knowledge in form of pressure-value curves together with a dynamic time warping cost function into the model. We demonstrate that our adapted model generates more realistic cardiovascular signals as measured by targeted physiological markers and showcase that such generated signals can be used to improve a downstream task on real data.

关键词： Heart Adaptation models visualization data privacy Time series analysis Focusing Inspection Linear programming Physiology data models

来源：评论

学校读者我要写书评

暂无评论

On Private Server Implementations and data visualization for LoRaWAN

On Private Server Implementations and Data Visualization for...

引用

International Conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： Sheikh Tareq Ahmed Annamalai Annamalai Prairie View A&M University Prairie View Texas USA

The paper titled “On Private Server Implementations and data visualization for LoRaWAN” explores the implementation of private LoRaWAN servers for secure and scalable data transmission in Internet of Things (IoT) applications. The authors present a detailed analysis of the existing server implementations and propose a novel architecture for private server deployment. The paper also addresses the challenges associated with data visualization in LoRaWAN networks and presents a comprehensive solution for efficient data representation using advanced visualization techniques. The proposed implementation is evaluated through experiments and simulations, and the results demonstrate the feasibility and effectiveness of the proposed architecture for secure and scalable IoT applications. The paper concludes with a discussion on the future directions for research in this area, highlighting the need for further investigation on the scalability and security of LoRaWAN networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Channel analysis and Adaptation for Distributed Blind Equalizer on Sensor Network in Long-Distance Communication System 7

Channel Analysis and Adaptation for Distributed Blind Equali...

引用

7th World symposium on Communication Engineering, WSCE 2024

作者： Chi, Sulin Shimamura, Tetsuya Otemon Gakuin University Osaka567-8502 Japan Saitama University Graduate School of Science and Engineering Saitama338-8570 Japan

ISBN: (纸本)9798331542825

Distributed blind estimation has received much attention, as the unknown transmitted data signal can be estimated based on the received signal at each sensor node without knowledge of the transmission channel in long-distance communication systems. The performance of distributed blind equalization is easily affected by transmission channels. However, there are very few studies in investigating the effect of channel conditions on distributed blind equalization. Therefore, in this paper, 4 types of transmission channels, the Nyquist, the raised-cosine, the minimum-phase and the non-minimum phase channels, are considered for the distributed blind equalizer. In order to mitigate the effect of a large step-size on the noise enhancement for distributed blind equalization under noisy-channel conditions, a smaller initial step-size \mu is set initially. Then, an adjustable step-size approach is proposed to analyze the performance of the distributed blind equalization under different channels based on the equalizer error. This approach determines whether to adjust a smaller initial step-size to a larger step-size. The proposed approach is analyzed repeatedly over M input data samples of the distributed blind equalization. In the computer simulations, the average mean-square error (MSE) and average symbol-error rate (SER) are used to evaluate the performance of the distributed blind equalization. The computer simulation results show significant improvement in the performance of the distributed blind equalizer with the adjustable step-size approach. © 2024 ieee.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

A Distributed Algorithm for Force Directed Edge Bundling 10

A Distributed Algorithm for Force Directed Edge Bundling

引用

10th ieee symposium on large data analysis and visualization (LDAV)

作者： Tuyishime, Yves Pan, Yu Yu, Hongfeng Univ Nebraska Lincoln NE 68583 USA

ISBN: (纸本)9781728184685

Existing edge bundling algorithms typically require the global information structure of a graph. Therefore, with a simple division of the edges of a graph, it is challenging to conduct edge bundling in a distributed environment and achieve scalable performance. We select a representative edge bundling algorithm, Force-Directed Edge Bundling (FDEB), and parallelize it in a distributed environment. Particularly, to address the difficulties of partitioning and distributions of a large graph among processors, we first create a high dimensional space to represent the data distribution of a graph in FDEB. Second, we map each edge as a data point in this high dimensional space, and then partition and distribute the point cloud among processors. In this way, we can significantly reduce the data communication across processors, and ensure each processor assigned with a similar workload.

关键词： Human-centered computing visualization visualization techniques Graph drawings

来源：评论

学校读者我要写书评

暂无评论

Analyzing File Access Patterns on large-Scale HPC Systems: Opportunities for File Prefetching 31

Analyzing File Access Patterns on Large-Scale HPC Systems: O...

引用

31st International symposium on Modeling, analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2023

作者： Karimi, Ahmad Maroof Paul, Arnab K. Choi, Jong Youl Wan, Lipeng Wang, Feiyi Oak Ridge National Laboratory Oak RidgeTN United States Bits Pilani K. K. Birla Goa Campus Goa India Georgia State University AtlantaGA United States

ISBN: (纸本)9798350319484

This paper explores the potential opportunities for implementing file prefetching techniques on large-scale high-performance computing (HPC) systems. Specifically, we investigate the file access patterns of various applications across multiple scientific domains using two years' worth of Darshan I/O traces obtained from the Summit supercomputer. We identify recurring trends and patterns which indicate that prefetching can be effectively leveraged to improve data access performance on HPC systems. This study serves as a valuable reference for system architects and developers in the HPC community, providing insights into the opportunities and challenges associated with enabling file prefetching on large-scale HPC systems. © 2023 ieee.

关键词： Supercomputers

来源：评论

学校读者我要写书评

暂无评论

Implementation and Application of a Knowledge Service for AUV Mission Explainability

Implementation and Application of a Knowledge Service for AU...

引用

International symposium on Underwater Technology

作者： Jeremy Paul Coffelt Peter Kampmann Michael Beetz Subsea Solutions Rosenxt Group Bremen Germany Institute for Artificial Intelligence University of Bremen Bremen Germany

ISBN: (数字)9798331534189

ISBN: (纸本)9798331534196

This paper presents a knowledge service aimed at enhancing mission explainability in subsea robotics operations. The proposed system consists of an AI agent that chains together specialized large language models (LLMs) and a graph database to enable natural language querying and interactive visualization. The graph database models entities and relationships relevant to subsea inspection and maintenance, such as clients, industries, sites, vehicles, sensors, and underwater scene elements, including pipeline components and seafloor characteristics. The browser-based GUI aims to allow stakeholders—including field teams, robot developers, industry clients, and regulatory agencies—to intuitively interact with mission data, supporting post-mission analysis and explainability. Using pipeline inspections as a case study, we illustrate the potential of this approach and discuss future developments needed to advance this framework toward a practical solution for subsea robotics.

关键词： Industries Service robots large language models Pipelines Natural languages Sensor phenomena and characterization Inspection Robot sensing systems Visual databases Underwater technology

来源：评论

学校读者我要写书评

暂无评论

Tac-Miner: Visual Tactic Mining for Multiple Table Tennis Matches

引用

ieee TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2021年第6期27卷 2770-2782页

作者： Wang, Jiachen Wu, Jiang Cao, Anqi Zhou, Zheng Zhang, Hui Wu, Yingcai Zhejiang Univ State Key Lab CAD&CG Hangzhou Zhejiang Peoples R China Zhejiang Univ Dept Sport Sci Hangzhou Zhejiang Peoples R China

In table tennis, tactics specified by three consecutive strokes represent the high-level competition strategies in matches. Effective detection and analysis of tactics can reveal the playing styles of players, as well as their strengths and weaknesses. However, tactical analysis in table tennis is challenging as the analysts can often be overwhelmed by the large quantity and high dimension of the data. Statistical charts have been extensively used by researchers to explore and visualize table tennis data. However, these charts cannot support efficient comparative and correlation analysis of complicated tactic attributes. Besides, existing studies are limited to the analysis of one match. However, one player's strategy can change along with his/her opponents in different matches. Therefore, the data of multiple matches can support a more comprehensive tactical analysis. To address these issues, we introduced a visual analytics system called Tac-Miner to allow analysts to effectively analyze, explore, and compare tactics of multiple matches based on the advanced embedding and dimension reduction algorithms along with an interactive glyph. We evaluate our glyph's usability through a user study and demonstrate the system's usefulness through a case study with insights approved by coaches and domain experts.

关键词： Sports data visualization Games Visual analytics Task analysis Pattern matching Correlation table tennis tactic multiple matches glyph

来源：评论

学校读者我要写书评

暂无评论

Sensitive data Classification of Imbalanced Short Text Based on Probability Distribution BERT in Electric power industry

Sensitive Data Classification of Imbalanced Short Text Based...

引用

2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms, PRMVIA 2023

作者： Zhang, Wensi Liang, Xiao Zhang, Yifang Su, Hanchen State Grid Smart Grid Research Institute Co.Ltd. Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory Beijing China

ISBN: (纸本)9798350346596

The exploitation of big data in industrial fields faces several challenges, such as data privacy and security, data integration and interoperability, and data analysis and visualization. data privacy and security is a major concern, as the data collected from industrial fields often contain sensitive information. Due to the particularity of the industrial field, there are challenges in the utilization of big data. 1. The distribution of different categories data is extremely uneven;2. There are a large number of industry terms in the short texts that constitute the metadata, which makes semantic representation difficult. These two challenges have a large impact on the application performance of existing models. In order to resolve the problems above, this paper proposes a pre-training model based on probability distribution, which for the classification of sensitive data in the power industry. The model consists of three modules: 1. The data enhancement module adopts the technology of synonym expansion and noise introduction, so that the model can extract the classification features of sensitive data with a small proportion;2. The pre-training module adopts the BERT model, which can obtain the semantics of industry terms in short texts;3. The probability prediction module is used to regularize the distribution of test data to meet the training data. Compared with the traditional classification model and the classification model based on deep learning, the F1-score can be improved by 36.68% and 6.39%. © 2023 ieee.

关键词： Probability distributions

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：