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共 35127 条记录，以下是801-810 订阅

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Deep Learning Based Optimization of UAV Orbital Paths 6

Deep Learning Based Optimization of UAV Orbital Paths

引用

6th ieee international conference on Power, intelligent Computing and systems, ICPICS 2024

作者： Li, Zhanghan Chen, Yuandian School of Automation Guangdong University of Technology Guangzhou510006 China School of Physics and Optoelectronic Engineering Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9798350374315

UAV path planning is an important part of UAV technology, and genetic algorithms and ant colony algorithms are used for it in UAV path planning tasks. When facing some unknown environments, the performance of classical algorithms is less satisfactory. For the path planning problem of a single UAV, this paper proposes the APF-DDQN model using the artificial potential field method combined with the multi-intelligence body algorithm DDQN. The model utilizes the dominance function as a metric for selecting action values and measuring the goodness of the tie-breaking values of all actions. © 2024 ieee.

关键词： Unmanned aerial vehicles (UAV)

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ResNet50 for Accurate Plant Leaf Disease Detection and Classification 2

ResNet50 for Accurate Plant Leaf Disease Detection and Class...

引用

2nd international conference on intelligent cyber Physical systems and Internet of Things (ICoICI)

作者： Rani, Ritu Gupta, Sheifali Chitkara Univ Inst Engn & Technol Rajpura 140401 Punjab India

ISBN: (纸本)9798331540661;9798331540678

ResNet50 deep learning network in this research report obviously finds plant diseases. Divided into "Healthy," "Powdery," and "Rust," the data compiles 1530 images overall and generates testing, training, and sets. Every image is modified and scaled using techniques of validation data augmentation aimed to increase variance. ResNet50 models gain from pre-trained weights to be multi-class classification focused. Changes in learning rate and early training phase stopping help to prevent overfits. To ensure good performance, the model is assessed with accuracy, precision, recall, F1-score, and confusion matrix. Plotting of training and validation accuracy and loss curves helps one to track learning development. After that, the model is ready for use with an easy interface;field testing is carried out to confirm its performance on fresh data. Consistent updates and active learning strategies help to guarantee ongoing development. This approach seeks to generate an accurate, scalable, efficient system for plant disease classification thereby improving agricultural output and sustainability.

关键词： Plant Disease Classification ResNet50 Deep Learning Image Recognition Agricultural technology Disease Detection Convolutional Neural Networks (CNN) ect

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Enhanced Agricultural Methods and Sustainable Farming Through IoT and AI technology 2

Enhanced Agricultural Methods and Sustainable Farming Throug...

引用

2nd international conference on intelligent cyber Physical systems and Internet of Things (ICoICI)

作者： Manivannan, K. Gowda, Dankan, V Pavan, B. H. V. V. S. R. K. K. Aravindh, S. Nithisha, C. Tanguturi, Rama Chaitanya VSB Engn Coll Dept Informat Technol Karur Tamil Nadu India BMS Inst Technol & Management Dept Elect & Commun Engn Bangalore Karnataka India Bonam Venkata Chalamayya Inst Technol & Sci Dept ECE Amalapuram Andhra Pradesh India Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci & Dept Comp Sci & Engn Chennai Tamil Nadu India Mohan Babu Univ Sch Comp Dept Data Sci Tirupati Andhra Pradesh India PACE Inst Technol & Sci Dept Comp Sci & Engn Ongole Andhra Pradesh India

ISBN: (纸本)9798331540661;9798331540678

The combination of IoT and AI technologies in the future promises to disrupt agriculture positively while trying to solve problems affecting the sector through embracing technological advances. The following paper focuses on the development of an IoT and AI framework for enhancing practices in agriculture through real-time control and smart control. Wireless IoT sensors are placed in the farms to monitor important parameters of farms like moisture content, temperature, humidity etc and health of crops. Consequently, data is harvested to assist with accurate irrigation, climatic regulation, and early diagnosis of disease. From the experimental results observed it became clear that resource utilization was boosted by 25% of lesser water usage while crop yields were boosted by as much as 30%. It also early identifies crop diseases, hence cutting crop losses by 15%. Such is crucial to stress that the results obtained reveal the ability of the system to improve the sustainability and productivity of agriculture. Future work will comprise the fine-tuning of the AI model, enhancement of sensors, and their incorporation with other smart technologies besides adapting this strategy for various agricultural conditions, hence the importance of smart solutions in the promotion of eco-friendly farming.

关键词： Internet of Things Artificial Intelligence Sustainable Farming Agriculture technology Precision Farming Smart Agriculture

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Exploration of Trust-Based Collaborative Intrusion Detection System Development: A Survey 2

Exploration of Trust-Based Collaborative Intrusion Detection...

引用

2nd international conference of intelligent Methods, systems and Applications, IMSA 2024

作者： Pawar, Tejaswini Rao, Jyoti Patil, Pramod Dr. D. Y. Patil Institute of Technology Pune India

ISBN: (纸本)9798350362633

The rapid increase in cyber breaches has made intrusion detection systems (IDSs) an essential tool for protecting personal and organizational assets. Computer networks grow in size and complexity, standalone IDSs face challenges in identifying advanced and sophisticated threats such as Distributed Denial of Service (DDoS) attacks. To address such issue development and deployment of collaborative intrusion detection system (CIDS) have become essential in today's cyber security landscape to protect against evolving and advanced cyber threats, ensuring the safety and security. These systems aim to enhance the detection capabilities by sharing relevant information and collaborating together to detect and respond to advanced threats. Trust mechanisms play an important role in establishing and maintaining trust relationships between distributed nodes, which improves the overall efficiency and robustness of intrusion detection in CIDS. In this survey we summarizing existing research on trust-based CIDS, identifying challenges, and outlining future directions. The survey aims to highlight the importance and potential of trust-based collaborative intrusion detection systems and inspire researchers to explore innovative solutions. © 2024 ieee.

关键词： Network intrusion

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Evaluation and Improvement of Distribution System Resilience under Damage Conditions 2

Evaluation and Improvement of Distribution System Resilience...

引用

2nd international conference on cyber-Energy systems and intelligent Energy, ICCSIE 2024

作者： Hu, Bojun Wei, Xiongwei Liu, Peiran Li, Qingxia Zhang, Xueyang College of Systems Engineering National University of Defense Technology Changsha China

ISBN: (纸本)9798350373318

Events of high impact but low frequency such as wars and extreme weather are likely to cause cluster dis-connection of the distribution network and even large-scale power outages, which will have a negative impact on economic development and social stability. In this context, firstly, two uni-versal network resilience evaluation indexes, load configuration redundancy and balance of communication network is proposed. Then, the graph theory is used, considering the interaction of communication network and power grid, to abstract network topology model, the genetic algorithm and K-Shell algorithm are innovatively combined to optimize the load configuration of the communication network topology. The effectiveness of the proposed method is verified by experiments. © 2024 ieee.

关键词： Power distribution networks

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Towards a Responsive Security Operations Center for UAVs 20

Towards a Responsive Security Operations Center for UAVs

引用

20th ieee international Wireless Communications and Mobile Computing (ieee IWCMC) - Green and intelligent Communications

作者： Tlili, Fadhila Ayed, Samiha Fourati, Lamia Chaari Univ Technol Troyes LIST3N Troyes France Natl Sch Elect & Telecommun Sfax Sfax Tunisia Sfax Univ Digital Res Ctr Sfax Lab Signals Syst aRtificial Intelligence NeTworkS SM RTS Sfax Tunisia Sfax Univ Digital Res Ctr Sfax CRNS Lab Signals Syst Artificial Intelligence NeTworkS SM RTS Sfax Tunisia

ISBN: (纸本)9798350361261;9798350361278

Unmanned Aerial Vehicles (UAVs) industry has experienced rapid growth and widespread adoption across various sectors. This increased affordability of UAVs has led to their extensive use, making them valuable assets for critical missions. However, the growing reliance on UAVs has also exposed them to various attacks. Multiple researchers have proposed frameworks based on different technologies to address these issues. Among these, AI-based frameworks and intrusion detection systems have emerged as prominent solutions for detecting UAV attacks. Due to the existing vulnerabilities, it is crucial to implement additional security measures to protect UAV processes. In this regard, a responsive Security Operations Center (SOC) offers a suitable solution to bridge this gap. This paper explores the need for a SOC specifically tailored for UAVs, focusing on cyber awareness and control measures. We emphasize the importance of control mechanisms within a SOC to ensure the protection of UAVs. We propose a responsive security solution for UAVs by integrating a SOC within an AI-based framework. The detection and mitigations expected through combining SOC in an AI-based IDS are promising. They indicate the effectiveness of the chosen techniques, which guarantees UAVs security.

关键词： UAVs Security Operations Centers Artificial Intelligence Intrusion detection systems cyber-attacks

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Automated Data Collection and Analysis for intelligent Maintenance of Electrical systems 6

Automated Data Collection and Analysis for Intelligent Maint...

引用

6th ieee international conference on Power, intelligent Computing and systems, ICPICS 2024

作者： Yu, Wenduo Guo, Zongjin Suo, Pengxiang Hui, Shengxuan Wang, Zhijia Liu, Guangyu State Grid Yingkou Power Supply Company Yingkou China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374315

The rapid development of industrial automation technology has made intelligent maintenance of electrical equipment the key to ensuring production and safety. The purpose of this article is to conduct an in-depth study of automated data collection and analysis technology in the intelligent maintenance of electrical facilities. Utilizing cutting-edge multi-sensor data integration technology and sophisticated data analysis methods, we implement continuous tracking of equipment operation conditions and forward-looking predictions of possible failures. We use vibration, temperature, current, and other sensing equipment to implement wireless information exchange to enable instant data transmission, as well as random forest algorithms and support vector machines for in-depth analysis. The research results show that the intelligent maintenance system significantly improves the fault identification rate and accurate forecasting capabilities while reducing the length of unexpected shutdowns and maintenance costs. The final judgment shows that intelligent maintenance technology plays an indispensable role in the field of power system maintenance, which effectively increases the stability of the machine and the company's competitive advantage. © 2024 ieee.

关键词： Wireless communication Wireless sensor networks Costs Accuracy Production Data collection Power system stability Maintenance Sensors Data communication

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A Two-Stage Extended Kalman Filter-Based Approach Against FDI cyber-Attack in intelligent and Connected Vehicles 11

A Two-Stage Extended Kalman Filter-Based Approach Against FD...

引用

11th international conference on Vehicle technology and intelligent Transport systems, VEHITS 2025

作者： Sun, Bin Yang, Shichun Wang, Yu Lu, Jiayi Cao, Yaoguang School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beihang University Beijing China

ISBN: (纸本)9789897587450

With the widespread integration of artificial intelligence and telecommunication technologies in vehicles, the challenge of cybersecurity in intelligent and Connected Vehicles (ICVs) has gained significant attention. A typical and high-risk cyber-attack technique involves False Data Injection (FDI) into sensors through the network, resulting in deviations in subsequent planning and control algorithm outcomes. Existing approaches suffer from limited robustness, being suitable only for simple models or requiring extensive data for the training model, which limits their practicality. Therefore, this paper proposes a method based on a Two-stage Extended Kalman Filter (TSEKF), which not only detects cyber-attacks but also restores the vehicle’s true motion state, thereby enhancing the robustness of vehicle ego state perception. The experimental results demonstrate that the proposed method exhibits strong performance across various motion scenarios, offering an effective solution for the safe operation of ICVs. Copyright © 2025 by SCITEPRESS - Science and technology Publications, Lda.

关键词： cyber attacks

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Enhancing Substation automation by RTU Design Optimization and Database Standardization for Improved Operational Efficiency in Tata Power-DDL 9

Enhancing Substation Automation by RTU Design Optimization a...

引用

9th ieee international conference for Convergence in technology, I2CT 2024

作者： Sharma, H.C. Bagchi, Shrinjoy Mogha, Abhinav Tata Power -DDL Technical Services Delhi India

ISBN: (纸本)9798350394474

In India, despite escalating electricity demand, distribution companies' grapple with high Aggregate Technical & Commercial Losses (AT&C) and technological gaps. A digitized distribution grid, prioritizing "Information Value"over "Energy Value,"serves as an automated network ensuring efficient and reliable energy supply. Substation automation, driven by advanced supervisory control and data acquisition (SCADA) systems, facilitates centralized monitoring and control of the entire Power System Network. Modern electronics, computational platforms, and field devices, particularly the Remote Terminal Unit (RTU), are integral to this automation. The RTU collects data from downstream intelligent Electronic Devices (IEDs) on diverse electrical equipment, forming a complex ecosystem. While these IEDs drive the digital revolution in utilities, their increasing integration with RTUs poses vulnerabilities, leading to electronic hang conditions. RTU breakdowns result in zero visibility for a grid substation, impacting system reliability, and contributing to heighten System Average Interruption Duration Index (SAIDI), MU Loss, prolonged Mean Time to Restore (MTTR), and inaccurate load forecasts. This paper explores methodologies for optimizing Substation RTU performance, addressing hardware, software, and network design enhancements. © 2024 ieee.

关键词： SCADA systems

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A Multi-agent Reinforcement Learning Based CR Allocation Approach For Multi-Scenario Advertising systems 6

A Multi-agent Reinforcement Learning Based CR Allocation App...

引用

6th ieee Advanced Information Management, Communicates, Electronic and automation control conference, IMCEC 2024

作者： Liu, Chang Ye, Yun Zhang, Liang Fan, Ruming Chen, Yucheng Zhang, Kai Chan, Wai Kin Victor Tsinghua University Intelligent Transportation and Logistics Systems Laboratory Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China Ant Group China

ISBN: (纸本)9798350316520

The goal of a recommender system is to recommend the most suitable items to a user from a large number of candidate items. The computational cost increases with the number of user requests and the complexity of the service or model. Under limited computing resource, how to make a tradeoff between computing cost and business benefit has become an important issue. This study focus on computation allocation (CR) optimization in multi-scenario advertising systems. A well designed multi-step MDP model is introduced, with each agent managing CR control task in their respective scenario. The MAPPO-CR algorithm is developed to enhance convergence and improve allocation performance through tailored differential rewards and cooperative mechanism. Experiments demonstrate significant improvements in convergence speed, allocation revenue and scalability, highlighting the effectiveness of the proposed allocation algorithm for complex dynamically changing online environments. © 2024 ieee.

关键词： Recommender systems

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