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检索条件"任意字段=3rd IEEE International Conference on Distributed Computing in Sensor Systems"

共 5118 条记录，以下是61-70 订阅

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A Hybrid PSO and K-Means Clustering Approach for Enhanced sensor Localization in WSNs 3

A Hybrid PSO and K-Means Clustering Approach for Enhanced Se...

引用

3rd international conference on Intelligent systems, Advanced computing, and Communication, ISACC 2025

作者： Singh, Ningombam Hemarjit Manna, Prithwish Majumder, Sudipta Bose, Rajesh Dibrugarh University Dept. of CSE Dibrugarh India JIS University Dept. of CSE West Bengal India

ISBN: (纸本)9798331523893

In Wireless sensor Networks (WSNs), correct sensor location is crucial for optimal data collection and transmission. This work introduces an improved methodology for sensor placement that integrates Particle Swarm Optimisation (PSO) with K-Means clustering to boost the efficacy of RSSI-based localisation. To measure the distance between sensors, researchers commonly employ the Received Signal Strength Indicator (RSSI);nevertheless, errors may be introduced by outside variables including interference and signal attenuation. To tackle these problems, we present a hybrid approach whereby Particle Swarm Optimisation (PSO) is employed for the global optimisation of sensor placements, while K-Means clustering enhances the sensor aggregation based on proximity and Received Signal Strength Indicator (RSSI) signal intensity. The suggested technique reduces localisation errors by optimising sensor placement and classifying nodes into suitable clusters. Experimental findings indicate that the hybrid PSO-K-Means method markedly improves positioning accuracy relative to conventional localisation strategies. The results indicate that combining PSO with K-Means clustering is an efficient approach for enhancing sensor localisation for the considered performance criteria. © 2025 ieee.

关键词： sensor nodes

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Research on optimal scheduling of distributed flexible resources based on regional energy autonomous balancing architecture 3

Research on optimal scheduling of distributed flexible resou...

引用

3rd ieee international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Yuntong, Lv Peng, Tao Zhitao, Wang Hongbo, Li Wei, Huo Xin, Xin State Grid Hebei Electric Power Co. Ltd. Marketing Service Center Hebei Province Shijiazhuang050022 China

ISBN: (纸本)9798350380989

In order to solve the problem of optimizing distributed flexible resources, a distributed flexible resource optimization scheduling model based on regional energy self-balancing architecture is proposed. The regional energy autonomous architecture is analyzed, focusing on the role of edge computing in the architecture, and explaining the basic principles of autonomous scheduling. The basic connotation of flexible resources is analyzed and the basic characteristics of flexible resources are explained. A multi-objective optimization model based on cloud-side distributed power capacity optimization, side-side model cost optimization, and end-side model revenue optimization is proposed, and is solved using the augmented Lagrangian function. Finally, simulation analysis was conducted based on the 39-node model to demonstrate the effectiveness of the model proposed in this article. © 2024 ieee.

关键词： distributed flexible resources optimal dispatch regional energy autonomy renewable energy

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distributed Adaptive Test Monitoring Data Classification Technique Based on Data Fields 3

Distributed Adaptive Test Monitoring Data Classification Tec...

引用

3rd international conference on Innovations and Development of Information Technologies and Robotics, IDITR 2024

作者： Wei, Jinyi Zhang, Shiyong North China Institute of Computing Technology Department of Experimental Training Beijing China

ISBN: (纸本)9798350385694

Aiming at the problem that monitoring data in cross-domain tests face a large amount of data and cross categories, we establish a test monitoring data classification system, study the distributed adaptive data classification technology based on data fields, cut and assign the classification task to nodes at different levels by using a distributed data processing scheme to make the classification modular and low-coupling, and realize fast and accurate classification of cross-domain test monitoring data to achieve the purpose of improving the monitoring efficiency of test data by different test personnel and fast access to key data. © 2024 ieee.

关键词： Classification (of information)

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Protection Coordination Impact on Reliability of Distribution systems with distributed Energy Resources 3

Protection Coordination Impact on Reliability of Distributio...

引用

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

作者： Kumari, Rani Naick, Bhukya K. Dept. of Electrical Engineering Dhanbad India

ISBN: (纸本)9798350349207

The effectiveness and reliability of a power distribution system hinge on the establishment and maintenance of efficient coordination between protective relays. Alongside the prevention of unwarranted overloads, inadequate coordination among relays may lead to an increased likelihood of revealing concealed failures within crucial components of the protection system, like Circuit Breakers. To assess the potential degradation of system reliability due to protection system malfunctions, this study proposes the utilization of a Markov model (MM) in combination with a Monte Carlo simulation (MCS) algorithm. Furthermore, the study also addresses the impact of the protective equipment mis-coordination on the concealed failure of protection systems. Subsequently, using a modified Canadian benchmark distribution system, the study computes the reliability indices of System Average Interruption Duration Index (SAIDI) and Expected Energy Not Supplied (EENS) for three distinct scenarios characterized by varying relay settings and protection coordination. The findings are subsequently presented to demonstrate how miscoordination of protection systems within the distribution network can affect the overall system reliability. © 2024 ieee.

关键词： Electric circuit breakers

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High Capacity Multiresonant Chipless RFID sensor Tag For IoT Applications 3

High Capacity Multiresonant Chipless RFID Sensor Tag For IoT...

引用

3rd international conference on Communication, computing and Digital systems, C-CODE 2023

作者： Jabeen, Iqra Amin, Yasar Tenhunen, Hannu University of Engg and Technology Dept.of Telecommunication Engg Taxila Pakistan University of Turku Dept.of Information Technology Turku Finland

ISBN: (纸本)9798350332391

A novel, high-density, miniature and compact chip- less RFID sensor tag is presented in this article. The proposed work comprises fourteen nested quatrefoil-shaped slot resonators for ID coding with the additional feature of printability and sensitivity. The geometrical configuration consists of several quatrefoil slots of various sizes distributed in a concentric *** unique feature of the presented tag is exhibiting a humidity sensing feature with the deployment of silver nano-ink particle as a radiator by keeping the high code density of 21.8 bits/cm2 in comparison with existing reported works. A bit coding sequence is observed in the frequency spectra from 5 GHz-24 GHz while maintaining a compact size of 8 mm× 8 mm. Further, the performance of the proposed tag is evaluated for numerous substrates, including Rogers RT/Duroid/5880, Taconic (TLX-8), F4BM and Kapton HN, allowing it to be employed in a variety of environments. Additionally, the realized tag structure possesses angular stability at various polarization angles up to 900. This particular tag is deemed to be a suitable choice for future product identification and Internet of Things (IoT) systems. © 2023 ieee.

关键词： Internet of things

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IoT based Target Tracking System using WSN in Smart City Surveillance 3

IoT based Target Tracking System using WSN in Smart City Sur...

引用

3rd ieee international conference on Blockchain and distributed systems Security, ICBDS 2024

作者： Zade, Nilima Iyer, Kamatchi R. Deshpande, Shubhada Vora, Deepali Henry, Rabinder Pakhmode, Sonali Lohbare Maharashtra Pune India Universal SkillTech University Maharashtra Mumbai India Raak Group of Institutions Pondicherry India Vppcoe Sion Mumbai India University of Mumbai Mumbai India

ISBN: (纸本)9798350354348

Safety and security are the main objectives to be achieved in unpopulated and unguarded open areas within the smart city mission that has been started recently in India. Tracking non-cooperative moving targets such as humans or animals in an outdoor environment is a challenging task. This is due to inherent hardware constraints and limitations associated with respect to wireless sensor networks and the Internet of Things (IoT) required for implementing object detection, observation, and monitoring. The simulation and validation of the motion models and development of an IoT-based electronics system for approximate localization of the non-cooperative target in an open secluded area is a part of this work. In the work passive infrared sensor network has been utilized for target tracking. The developed prototype has been tested with the tracking algorithm. A comparative analysis of the prototype and the simulated results are presented. The results indicate that an approximate localization of the target has been achieved. © 2024 ieee.

关键词： Wireless sensor networks

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A Scratchpad Spiking Neural Network Accelerator 3

A Scratchpad Spiking Neural Network Accelerator

引用

3rd international conference on computing and Machine Intelligence (ICMI)

作者： Karakchi, Rasha Univ South Carolina Dept Comp Sci & Engn Columbia SC 29208 USA

ISBN: (纸本)9798350372977;9798350372984

Spiking Neural Networks (SNNs) have recently been used as a computational model for applications such as deep learning, image recognition and machine learning. Similar to the biological brain, SNN neurons depend on the membrane level to fire an output. If the level exceeds a specified threshold, the neuron sends an output to activate next neurons. This leads to an unbalanced workload among the neurons. The dynamically-changing membrane level is stored inside a neuron. In hardware, this storage can be implemented as a register or on-chip memory, which determines the amount of consumed resources and, in turns, affects the network scalability. SNN accelerators have recently been implemented on UltraScale FPGAs devices for high-performance purposes. On-chip memories on these devices are classified as distributed memory, Block RAMs (BRAMs) and Ultra RAMs (URAMs). In this paper, we explored the impact of using different on-chip memories to store the membrane level of SNN neurons. We implemented a parameterizable SpIking Neural networK (SINK) accelerator where the network capacity and weight width are parameters. SINK has the ability to run in four different modes based on the memory type. We ran SINK on UltraScale Zync104 FPGA device and measure the utilization of the hardware resources (LUTs), registers, memory, power consumption and performance. The results show that URAM can be the best fit to store the membrane level, since it used 30%, 11% and 2% less LUTs, Regs, and power 2% respectively comparing with BRAM and distributed memory

关键词： Spiking Neural Network FPGA Onchip Memory URAM BRAM distributed Memory

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Bitcoin price prediction based on financial data, technical indicators, and news headlines sentiment analysis using CNN and GRU deep learning algorithms 3

Bitcoin price prediction based on financial data, technical ...

引用

3rd international conference on distributed computing and High Performance computing, DCHPC 2024

作者： Arjmand, Masoud Kazeminia, Saman Sajedi, Hedieh University of Tehran Kish International Campus Department of Computer Engineering Kish Iran NHL Stenden University of Applied Science Department of Computer Vision and Data Science Leeuwarden Netherlands University of Tehran Department of Mathematics Statistics and Computer Science Tehran Iran

ISBN: (纸本)9798350381580

Bitcoin is the leading cryptocurrency with the highest market value among digital currencies. Therefore, predicting the value of Bitcoin can help to understand the entire cryptocurrency market. However, Bitcoin has had a lot of price fluctuations since its inception. In this paper, we are going to forecast the price of Bitcoin using news headline analysis, technical analysis indicators, and historical financial data. The news headlines used in this article are scraped from the Cointelegraph news website, which contains 3988 news headlines related to Bitcoin between 2/7/2020 and 3/8/2021. A transformer pre-trained model on cryptocurrency-related texts called CryptoBERT, which is a BERT-based sentiment analysis model, has been used to analyze the textual data. Also, a novel hybrid 2DCNN-GRU deep learning model has been used to predict the price. To adjust the parameters of this model, a parameter tuning method based on orthogonal arrays called the Taguchi method has been employed. Finally, to examine the proposed model's efficiency, the obtained results have been compared with other deep learning models from the literature review that used text data to predict bitcoin prices. The results show that this model outperformed other models in terms of MAE criterion, while in the other three criteria, namely MSE, RMSE and MAPE, it still demonstrated good results. © 2024 ieee.

关键词： Forecasting

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SRS: Scalable and Robust Snapshot Algorithm for Wireless sensor Networks 3

SRS: Scalable and Robust Snapshot Algorithm for Wireless Sen...

引用

3rd ieee international conference on Intelligent Technologies, CONIT 2023

作者： Mishra, Raghvendra Sharma, Teek Parval National Institute of Technology Department of Computer Science HP Hamirpur India

ISBN: (纸本)9798350338607

Global state determination of distributed systems gives information that is useful in applications of checkpointing, distributed garbage collection, deadlock detection, distributed algorithm termination detection, event boundary detection, distributed debugging, etc. Determination of the global state in a wireless sensor network needs a different approach than of traditional distributed networks due to unique properties of WSN like a constraint on resources, energy constraints, remote hazardous environments where sensors are deployed, network topology that is dynamic in nature, etc. In this paper, we propose a distributed snapshot algorithm that is scalable, robust, and provides efficient communication among WSN nodes which is based on tree architecture. We designed an algorithm in such a way that it can easily be scaled to any number of nodes without affecting the performance of the underlying system and it can effectively handle packet loss so that the communication cost of the whole system is maintained as minimal. We performed simulations in OMNET++ and did the analysis of results based on the number of messages exchanged, response time, and performance in packet loss situations. © 2023 ieee.

关键词： Fault tolerance

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Fault Localization of Distribution Network Based on Conservative Q-Learning Algorithm 3

Fault Localization of Distribution Network Based on Conserva...

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3rd international conference on Energy and Electrical Power systems (ICEEPS)

作者： Wu, Hongwen Yi, Chenying Zhou, Yangjun Zhang, Yuxuan Huang, Jinfeng Luo, Wei Tian, Junyang He, Renjun Wei, Renqiong Wang, Jing Guangxi Power Grid Co Ltd Wuzhou Power Supply Bur Wuzhou Peoples R China Guangxi Power Grid Co Ltd Guangxi Key Lab Intelligent Control & Maintenance Elect Power Res Inst Nanning Peoples R China Guangxi Power Grid Co LTD Power Dispatch Control Ctr Nanning Peoples R China

ISBN: (纸本)9798350375145;9798350375138

With the large-scale integration of distributed generation, the characteristics of the distribution network have changed significantly, resulting in a notable decline in the accuracy of traditional fault localization methods. To address this issue, this paper proposes a fault location method based on a conservative Q-learning (CQL) algorithm. Specifically, to tackle the problem of potential misjudgment, an objective function/fitness value correction method for bidirectional power flow induced by distributed generation is introduced. To overcome the challenges of slow convergence speed and poor robustness in existing models, a CQL algorithm is employed to enhance the efficiency and stability of the algorithm. The ieee-33 distribution network is used as a case study to demonstrate the accuracy and efficiency of the proposed fault localization method.

关键词： fault localization distributed generation bidirectional power flow conservative Q-learning algorithm

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