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MODGF: Multi-Objective Optimization Approach for Directed Greybox Fuzzing 25

MODGF: Multi-Objective Optimization Approach for Directed Gr...

引用

25th IEEE international conferences on High Performance computing and Communications, 9th international conference on Data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zuo, Xueying Song, Yubo Mao, Run Qin, Zhongyuan Sun, Xin School of Cyberspace Security Southeast University Nanjing China Internet Technology Center State Grid Zhejiang Electric Power Co. Ltd. Research Institute Hangzhou China

ISBN: (纸本)9798350330014

Directed Greybox Fuzzing employs code analysis to predict critical paths or potential vulnerabilities. Multi-objective optimization is a challenge to Directed Greybox Fuzzing. Current approaches employ evolutionary algorithms which may trap in local optima during mutation operation procedure. In this paper, we propose MODGF, a Directed Greybox Fuzzing method based on the elitist multi-objective evolutionary algorithm. The key insight of our approach is to get a more diverse distribution along the Pareto front during evolutionary iterations, which speed the convergence of the test cases. In MODGF, we use function distance, basic block distance, and seed distance as objective functions, and calculate distance metrics of the nearest neighbor solutions to infer the distribution density of solutions. We further introduce convergence measure and diversity measure as fitness values to ensure that the generated test cases are more uniformly distributed with more vulnerability types. In comparison to AFL and AFL-GO, the experiment reveals that MODGF exhibits significant performance enhancements in terms of convergence time, target function coverage, and vulnerability triggering efficiency. © 2023 IEEE.

关键词： Multiobjective optimization

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A Quadratic Boost Two-Stage Transformerless Inverter for Single Phase Photovoltaic applications 3

A Quadratic Boost Two-Stage Transformerless Inverter for Sin...

引用

3rd international conference on Power, Control and computing Technologies, ICPC2T 2024

作者： Neti, Sukhdev Singh Singh, Varsha Pattnaik, Swapnajit N.I. T. Raipur Dept. of Electrical Engg. Raipur India

ISBN: (纸本)9798350349207

The compact structure and highly efficient per-formance of the transformer-less inverter (TLI) are gaining popularity for the photovoltaic (PV) application. A decrease in the size of the TLI is possible by removing the bulky /heavy transformer from the conventional PV inverter system. It results in a loss of isolation, and a direct connection between PV and the grid is established through inverters. The direct connection causes the variation of common mode voltage (CMV) during the inverter operation, which further leads to the leakage current. This paper presents a two-stage TLI configuration for five-level output voltage. The front end uses two inductors and two capacitors to provide quadratic boost output to an inverter for multilevel output voltage. A common ground configuration (CGC) helps to mitigate leakage current. Level-shifted pulse width modulation (LS- PWM) is used to accomplish inverter control. Further, the voltage and current stress of the inverter are analyzed for each switch for selecting the power components. The TLI is verified in both MATLAB/Simulink environment and experimentally in the laboratory. © 2024 IEEE.

关键词： Pulse width modulation

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A Multivariate Heterogeneous O&M Knowledge Base Construction Method Based on Cloud Platform 9

A Multivariate Heterogeneous O&M Knowledge Base Construction...

引用

9th international conference on Intelligent computing and Signal Processing, ICSP 2024

作者： Li, Zhihong Chen, Liang Wang, Huaiyu Feng, Zhipeng Han, Xiao Li, Yan Shao, Danni Information and Communication Branch of State Grid Corporation of China Beijing China

ISBN: (纸本)9798350376548

The Operations Knowledge Base provides integrated services for operations knowledge from different cloud service providers, including troubleshooting experience, configuration management information, and performance monitoring data. By building a knowledge base, operators can quickly retrieve the information they need, significantly improving the speed and accuracy of problem solving. With the development of artificial intelligence and natural language processing technology, the O&M knowledge base can also provide intelligent services and applications, such as intelligent search, automatic fault diagnosis, and intelligent recommendation, to improve user experience and efficiency. However, implementing these features requires solving complex technical problems such as semantic understanding, knowledge reasoning, and so on. Based on the current cloud platform O&M knowledge system and business model, this paper constructs a multi-dimensional cloud platform O&M knowledge base, mines the knowledge association relationship with the help of natural language processing technology, and forms a visual knowledge graph network covering the whole domain of the cloud platform. At the same time, a method of building a multi-heterogeneous O&M knowledge base based on cloud platform is explored and verified to improve the efficiency and quality of cloud O&M. © 2024 IEEE.

关键词： Cloud platforms

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Research on insulator recognition algorithm based on deep learning

Research on insulator recognition algorithm based on deep le...

引用

2022 international conference on Cloud computing, Big Data applications and Software Engineering, CBASE 2022

作者： Kuang, Fan Cui, Jianhua Dai, Xiliang Zhang, Cheng Dongguan Power Supply Bureau of Guangdong Power Grid Corporation Dongguan523000 China

ISBN: (纸本)9798350396393

Unmanned aerial vehicle (UAV) was gradually replacing manual inspection of transmission lines to detect the state of insulators. In this paper, based on the image data source collected by UAV inspection, a method of insulator feature recognition and location by multi-scale grid was established based on deep learning theory. Under the structure of multi-scale grid recognition algorithm, feature extraction module, scale scaling module, classification and regression module were designed. After training and testing of the image data, the results of insulator identification and location were obtained. And the results showed that this method could effectively identify the characteristics of insulators. © 2022 IEEE.

关键词： Antennas

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Exploring Adaptive Data Acquisition Technology for Chip-based Communication Transmission Link 3

Exploring Adaptive Data Acquisition Technology for Chip-base...

引用

3rd IEEE international conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Tian, Lin Zhu, Yifeng Zheng, Wulue Li, Renxin China Southern Power Grid Ehv Transmission Company Guangdong Guangzhou China

ISBN: (纸本)9798350318609

In recent years, with the rapid development of applications such as mobile internet and the Internet of Things, the amount and speed of data transmission have been continuously increasing, which has also brought about a higher demand for signal quality. Due to the complex working environment in which the communication system operates, there are many uncertain factors and interference sources. Therefore, how to adapt and optimize the transmission link in a dynamic and ever-changing working environment, thereby improving transmission quality and data transmission rate, is a key issue that urgently needs to be solved in the field of communication. This paper proposes a chip based adaptive data acquisition technology scheme to address the issues of traditional data acquisition methods being unable to adapt to different communication links for data acquisition speed and system real-time performance. By analyzing the communication quality of different communication transmission links and ensuring the data acquisition rate, the sampling rate is adaptively adjusted according to different communication transmission links. The experimental results show that this scheme can adaptively adjust the acquisition rate according to the amount of data while meeting the real-time requirements of the system. This method can effectively prevent data distortion and has higher energy efficiency. © 2024 IEEE.

关键词： Data acquisition

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Application of Edge computing in Smart grid 3

Application of Edge Computing in Smart Grid

引用

3rd international conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2022

作者： Liu, Ran Yang, Runan Wang, Zhigang Sun, Xiaobo Fibrlink Communications Co. Ltd Beijing China State Grid Information & Telecommunication Group Co. Ltd Beijing China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

The development of the Internet of Things has promoted the development of smart grids. Edge computing, as one of the key technologies for Internet of Things applications, provides data services at the edge of the system through the integration of network, storage, computing and other technologies to solve the problem of real-time processing of a large amount of data. This paper focuses on the analysis of how edge computing technology is combined with power grid services. The article first analyzes the key technologies and characteristics of edge computing, and finally discusses the application of edge computing in smart grids. © 2022 IEEE.

关键词： Smart power grids

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Weather Forecasting Using Advanced Artificial Intelligence Techniques Based on Swin Transformer Network 2

Weather Forecasting Using Advanced Artificial Intelligence T...

引用

2nd international conference on Distributed computing and Optimization Techniques, ICDCOT 2024

作者： Kavitha, S. Nagamani, H.S. Sumanth, S. Pareek, Piyush Kumar Mageswari, P. Uma Nitte Meenakshi Institute of Technology Department of Mca Bangalore India Govt. Smt Vhd Central Institute of Home Science Department of Computer Science Bengaluru India Government College for Women Department of Computer Science and Applictaions Kolar India Nitte Meenakshi Institute of Technology Department of AI/ML Bangalore India Presidency College Department of Computer Applications Bangalore India

ISBN: (纸本)9798350382952

It is still difficult for weather prediction (NWP) representations to exactly anticipate rainfall, especially the highest rainfall events. The severely intermittent character rainfall, together with subgrid-scale are critical to the multi-scale dynamics that produce rainfall, might be the reasons for this. Because of this inherent fallibility of weather prediction model projections, it is standard practice to fix these forecasts by post-processing the model's output. To improve weather prediction, the study suggests using a Spectral Swin Transformer Network (SSTN). An operating high-resolution model system, the PRUFS model, which runs for East China at 3 km grid intermissions, was used to test the model. The 311 conventional ground-based weather stations to collect data on 2 m temperature, 2 m relative speed. A year's worth of historical PRUFS perfect outputs and surface comments make up the training dataset for SSTN, while two real-time SSTN outputs form the basis of the act evaluation. © 2024 IEEE.

关键词： Weather forecasting

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Health Insurance Cost Prediction Model Based on Big Data Analysis

Health Insurance Cost Prediction Model Based on Big Data Ana...

引用

2024 international conference on computing, Robotics and System Sciences, ICRSS 2024

作者： Zhai, Yantao Tai, Qiang Zhao, Yinping Wang, Ping Feng, Ying State Grid Information & Telecommunication Co. Ltd. Beijing branch Beijing China

ISBN: (纸本)9798331511296

This research seeks to create a model for predicting health insurance costs using big data analysis techniques, and methodically presents the entire procedure from gathering data, preparing it, engineering features, selecting models, and establishing them. Initially, samples from the US health insurance dataset were utilized for data cleaning and preprocessing to maintain data quality and consistency. Subsequently, through feature selection and dimensionality reduction techniques, key features highly correlated with medical expenses, such as age, gender, type of chronic disease, and historical medical expenses, were extracted. Based on these features, a deep learning model was used to predict health insurance expenses, and the prediction accuracy and stability were improved through model evaluation and optimization strategies. The research results show that the constructed prediction model has high accuracy and good generalization ability in practical applications. Through case analysis of actual data, the application effect of the model in personalized premium pricing, risk management and resource allocation is verified, which can help insurance companies more accurately predict medical expenses and provide decision support. This study provides powerful tools and methods for risk management and cost control in the health insurance industry, which has important practical significance. © 2024 IEEE.

关键词： Prediction models

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Design and Implementation of Power Dispatching Automation System Based on Deep Learning 5

Design and Implementation of Power Dispatching Automation Sy...

引用

5th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Shao, Mingchun Jia, Peng Wang, Chen Jin, Yiqi State Grid Henan Energy Interconnection Electric Power Design Institute Co. Ltd Zhengzhou450000 China State Grid Henan Economic Research Institute. Ltd Zhengzhou450000 China State Grid Zhengzhou Electric Power Supply Company Zhengzhou450000 China

ISBN: (纸本)9798350310603

The power prediction, state estimation and fault diagnosis methods based on deep learning are introduced. Take the cloud platform of electric power automation as the analysis object to study its architecture. The modified particle swarm optimization algorithm is combined with the structural topology of the cloud resource scheduling model to establish three-level data nodes. A new scheduling method for deep learning cloud computing system based on particle swarm optimization is proposed. By analyzing the information of primary equipment, secondary equipment and surrounding environment, the "dual core"model of power network is constructed. The real-time monitoring and forecasting of power system are carried out in the forecasting subsystem. Finally, through the analysis of the application case of artificial intelligent control system, the system has a wide range of applications. © 2023 IEEE.

关键词： Particle swarm optimization (PSO)

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Using Virtualization Approaches to Solve Deep Learning Problems in Voluntary Distributed computing Projects 9th

Using Virtualization Approaches to Solve Deep Learning Probl...

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9th Russian Supercomputing Days international conference, RuSCDays 2023

作者： Kurochkin, Ilya Papanov, Valeriy Institute for Information Transmission Problems of Russian Academy of Sciences Moscow Russia The National University of Science and Technology MISIS Moscow Russia

ISBN: (纸本)9783031494345

The task of training deep neural networks on a large amount of data requires a lot of resources. The solution of such a problem is often impossible to carry out on one computing device in an adequate time. Distributed computing systems can be used to solve deep learning problems. Such systems may consist of heterogeneous computing nodes with different computing power. To implement deep learning on a distributed heterogeneous system, it is necessary to solve the problem of utilization of all available resources. The solution to this problem is to configure the task delivery system of a distributed system. And to expand the number of computing nodes involved, it is necessary to use virtualization. The article discusses two types of virtualization for grid systems when solving deep learning problems. The features of the implementation of computational applications for training deep neural networks for solving the problem of image classification are discussed. The results of distributed deep learning on a public grid system are discussed. A comparative analysis of two virtualization approaches is given. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Virtualization

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