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共 285 条记录，以下是181-190 订阅

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Intelligent Monitoring system for Farms Based on Human-Computer Interaction and Automatic control Algorithms 1

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13th international conference on Frontier computing, FC 2023

作者： Qin, Gong Zou, Li School of Mechanical and Electrical Engineering Hubei Three Gorges Polytechnic Hubei Yichang443000 China College of General Education Hubei Three Gorges Polytechnic Hubei Yichang443000 China

ISBN: (数字)9789819992997

ISBN: (纸本)9789819992980

With the continuous development of livestock and poultry industry, monitoring of livestock and poultry farms has become more and more important. the monitoring of livestock and poultry farms mainly includes instrument monitoring and environmental parameter monitoring. the purpose of this paper is to study the farm intelligent monitoring system based on human-computer interaction and automatic control algorithm. In view of the real situation and problems encountered in the industrial development of China’s livestock and poultry farming industry, the current situation of environmental monitoring of livestock and poultry farms at home and abroad is analysed. Based on the research of wireless sensor network and human-computer interaction technology, a livestock and poultry environmental monitoring system based on automatic control algorithm technology was designed and developed. the automatic control algorithm was tested and the experiment showed that the overall error of the system was small. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Wireless sensor networks

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Application of Data Fusion Algorithms in the Data Processing of Intelligent Greenhouses 1

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13th international conference on Frontier computing, FC 2023

作者： Li, Jinguang Li, Dan College of Information and Control Engineering Jilin Institute of Chemical Technology Jilin Jilin City China Electrical and Information Engineering College Jilin Agricultural Science and Technology University Jilin Jilin City China

ISBN: (数字)9789819992997

ISBN: (纸本)9789819992980

Greenhouses can ensure the normal growth of crops in extreme environments. With the popularization of social intelligence, how to build an efficient and accurate environmental monitoring system to ensure that crops have suitable growth conditions is a top priority. In order to effectively solve the problem of data missing and large data errors caused by sensor collection in intelligent greenhouses under extreme environments, this paper uses data preprocessing and multi-sensor fusion algorithms to ensure the accuracy of data. the effectiveness of the data fusion algorithm is verified through data transmission experiments. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Crops

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Efficient and Low-Cost Monitoring of Sea Ice thickness Using Shipborne Vibration Sensors and Machine Learning: A Novel Approach 13

Efficient and Low-Cost Monitoring of Sea Ice Thickness Using...

引用

13th ieee international conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2023

作者： Zhang, Han Quan, Xiyu Yang, Le Li, Yuefang Han, Leng Deng, Dongli Li, Weishi Lv, Xiaoyong Zhao, Yuliang Detachment 60 PLA Unit 92493 Huludao125000 China School of Control Engineering Northeastern University at Qinhuangdao Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China Experimentalist with Northeastern University at Qinhuangdao Qinhuangdao066000 China

ISBN: (纸本)9798350315196

Sea ice is a significant factor in ship navigation, and accurately identifying its thickness is crucial for timely decision-making to ensure ship structural integrity and personnel safety. However, current methods for sea ice thickness measurement, such as shipborne imaging devices and synthetic aperture radar altimeters, have limitations such as high costs, difficulties in data acquisition, and poor timeliness. In this article, we present an approach to detect sea ice thickness using a combination of sensors and machine learning techniques. Vibration signals from ship-ice collisions are collected using acceleration vibration sensors, undergo data preprocessing and time-domain alignment, and the true value of sea ice thickness is obtained through field measurements and a sea ice image information identification system. Time-frequency domain features are extracted, and feature quantity optimization is performed, followed by machine learning regression algorithms to predict sea ice thickness. Experimental results show that excellent regression results can be obtained using a single node for thickness prediction, with an R2 value of 0.908 and an RMSE of 1.374 cm. Our findings demonstrate that analyzing vibration signals generated by ship-ice collisions during vessel navigation can effectively identify sea ice thickness. this approach provides a practical and cost-effective alternative for sea ice thickness measurement and identification in the field. © 2023 ieee.

关键词： thickness measurement

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An Improved Resource Management Algol-ithm for Distributed systems

An Improved Resource Management Algol-ithm for Distributed S...

引用

international Phoenix conference on Computers and Communications (IPCCC)

作者： Kee Koon Chua J. Carothers Department of Electrical and Computer Engineering University of Arizona Tucson Tucson AZ USA

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A Hierarchical Framework for Vehicle-to-Grid (V2G) Distributed control Combining Peer-to-peer Blockchain with systemic Scheduling 13

A Hierarchical Framework for Vehicle-to-Grid (V2G) Distribut...

引用

13th international conference on Power and Energy systems, ICPES 2023

作者： Wei, Yifan Zhu, Yimin Qin, Yudi Li, Yalun Wang, Hewu Han, Xuebing Lu, Languang Ouyang, Minggao Tsinghua University State Key Laboratory of Automotive Safety and Energy Beijing China Nanyang Technological University School of Mechanical and Aerospace Engineering Singapore Singapore Beijing LianYu Technology Co. Ltd. Beijing China

ISBN: (纸本)9798350345063

To achieve the carbon peak and neutrality target in China, the future electricity system will face the challenge of a high level of intermittent renewable energy, in which the energy storage will become the bottleneck. Vehicle-to-grid (V2G) is one of the most promising technologies to provide large-scale short-term energy storage with low cost. However, there is 'trade-off' between the global optimality and computational burden to schedule massive distributed vehicles. Additionally, the concern on battery degradation has become a critical obstacle for electric vehicle (EV) owners to participate in the vehicle-grid integration services, which is often ignored in existing scheduling methods. therefore, a hierarchical framework is proposed in this work, using global optimization to allocate the energy consumption and supply boundaries at the upper level, and 'self-organization' by peer-to-peer energy trading among prosumers with blockchain to execute instant transactions at the regional lower level. the evolutionary game and double auction are applied for iteration. the characteristics of EV charging and travel are generated with real-world statistics, and the battery degradation is included in the social welfare function. the simulation example has verified the effectiveness of the proposed method, achieving 13.8% and 15.7% increase of the overall utility compared with the method without blockchain and disregarding battery degradation, respectively. © 2023 ieee.

关键词： Global optimization

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Data Cleaning Optimization for Grain Big Data Processing using Task Merging 6

Data Cleaning Optimization for Grain Big Data Processing usi...

引用

6th international conference on Information Science and control engineering (ICISCE)

作者： Ju, Xingang Lian, Feiyu Zhang, Yuan Henan Finance Univ Collaborat Innovat Ctr Henan Grain CropsKey Disc Key Lab Grain Photoelect Detect & ControlMinist Henan Prov Key Lab Grain Informat Proc & Control Zhengzhou Peoples R China Minist Educ Henan Prov Key Lab Grain Informat Proc & Control Key Lab Grain Photoelect Detect & Control Zhengzhou Peoples R China Minist Educ Collaborat Innovat Ctr Henan Grain Crops Key Lab Grain Photoelect Detect & Control Henan P Key Lab Grain Informat Proc & Control Zhengzhou Peoples R China

ISBN: (纸本)9781728157122

Data quality has exerted important influence over the application of grain big data, so data cleaning is necessary and important work. In MapReduce frame, we can use parallel technique to execute data cleaning in high scalability mode, but due to the lack of effective design there are amounts of computing redundancy in the process of data cleaning, which results in lower performance. In this research, we found some tasks often are carried out multiple times on same input files, or require same operation results in the process of data cleaning. For this problem, we proposed a new optimization technique that is based on task merge. By merging simple or redundancy: computations on same input files, the number of the tool computation in MapReduce can be reduced greatly. thy experiment shows, by this means, the overall system runtime is significantly reduced, which proves that the process of data cleaning is optimized. In this paper, we optimized several modules of data cleaning such as entity: identification, inconsistent data restoration, and missing value filling. Experimental results show that the proposed method in this paper can increase efficiency for grain bid data cleaning.

关键词： grain big data data cleaning task merging hadoop mapReduce

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A method to prevent cascading trip in power network based on nodal power 13th

A method to prevent cascading trip in power network based on...

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13th international conference on Genetic and Evolutionary computing, ICGEC 2019

作者： Deng, Hui-Qiong Wu, Peng-Peng Lin, Xing-Ying Lin, Qin-Bin Li, Chao-Gang School of Information Science and Engineering Fujian University of Technology Fujian350118 China Fujian Provincial University Engineering Research Center of Smart Grid Simulation Analysis and Integrated Control Fujian350118 China

ISBN: (纸本)9789811533075

this paper proposes a method to prevent cascading trip based on the action of relay protection and the output of generator as the optimization variable for aiming at the cascading trip in power grid. Firstly, the critical state of cascading trip is discussed, and the safety index of cascading trip in power grid is analyzed based on the analysis of the performance of cascading trip and the action of relay protection. On the basis of this index, a kind of optimized model of cascading trip prevention is given while considering the various constraints of power grid synthetically. this paper presents a complete algorithm flow for solving the optimized model combined with particle swarm optimization algorithm aiming at the proposed optimized model. Finally, on a ieee39 system, an example is analyzed by the MATLAB program, which verifies the rationality of the proposed method. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Particle swarm optimization (PSO)

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Deep Reinforcement Learning for Distribution Power system Cyber-Resilience via Distributed Energy Resource control 14

Deep Reinforcement Learning for Distribution Power System Cy...

引用

14th ieee international conference on Communications, control, and computing Technologies for Smart Grids, SmartGridComm 2023

作者： Corrado, Nicholas E. Livesay, Michael Bailey, Tyson Johnson, Jay Levin, Drew University of Wisconsin Department of Computer Sciences Madison United States Sandia National Laboratories United States

ISBN: (纸本)9781665455541

Interoperable, internet-connected distributed energy resource (DER) devices in power systems create a new attack vector for malicious cyber-actors. Modern control systems primarily focus on transmission and sub-transmission operations and rarely incorporate DER or other distribution-connected equipment. While recent advances have expanded grid operator visibility and control functionality to the distribution level, these control systems struggle to scale with thousands of networked devices. thus, to defend against potential attacks on DER devices, we must develop new real-time control algorithms to ensure grid stability. In this work, we present a new approach to power distribution control based on deep reinforcement learning (RL) algorithms which can learn optimal control policies through experience. We evaluate four RL algorithms in novel voltage stabilization tasks based on the ieee 13-bus and EPRI Ckt5 power distribution models. We demonstrate that RL can successfully perform voltage regulation and outperform a greedy algorithm. Our results coupled with the established capability of RL to scale in high-dimensional settings opens a path towards real-time cyber defense of power systems with RL agents. © 2023 ieee.

关键词： Reinforcement learning

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Edge computing Resource Management Based on Genetic Algorithm

Edge Computing Resource Management Based on Genetic Algorith...

引用

international conference on Electronics Information and Emergency Communication

作者： Lei Cai Kangning Yao Wenbin Xian Chao Gong The 4th System Department North China Institute of Computing Technology Beijing China Computer and Communication Engineering University of Science and Technology Beijing Beijing China

Resource management in edge computing has always been a hot research topic. In the scenario of multiple edge servers and multiple tasks, this paper proposes a task offloading model that optimizes the total cost by weighting energy consumption and latency to reduce energy consumption and latency. Based on the proposed task offloading model, an improved genetic algorithm is proposed to solve the optimal task offloading strategy. Simulation experiments have shown that applying improved genetic algorithms to task offloading models can accelerate convergence speed, find the optimal computing offloading strategy, and improve system performance.

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Robust mobile computing-a case study in architecture performance evaluation

Robust mobile computing-a case study in architecture perform...

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Annual ieee international ASIC/SOC conference

作者： R. Kress S. Schulz Advanced Design Methods Infineon Technologies Munich Germany Department of Electrical and Computer Engineering University of Arizona Tucson Tucson AZ USA

Architecture performance evaluation is a key part in system design. It can be seen as the backbone of architecture analysis and design space exploration. In this paper we present a comparison of system modeling and cycle true simulation. Our work is based on the evaluation of a system model of a design example from the agricultural domain next to the results of an instruction set simulation.

关键词： Robustness Mobile computing Computer aided software engineering Computer architecture Microcontrollers Hardware Modems Computer networks Robust control Circuits

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