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SARSA-Based Voltage Regulation of PV-Buck Converter System Under Multi-Nature Load Conditions

SARSA-Based Voltage Regulation of PV-Buck Converter System U...

引用

international conference on communication systems and Network Technologies (CSNT)

作者： Rinki Maurya Ankit Srivastava Dashrath Nishad Ashutosh Kumar Singh Electronics & Communication Department IIIT Allahabad India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

DC microgrids are experiencing rapid evolution due to increasing renewable energy integration and diverse load requirements, necessitating advanced control strategies for stable operation. this paper presents a novel voltage regulation approach utilizing policy gradient reinforcement learning with SARSA algorithm for a PV-fed buck converter system. the proposed methodology addresses the complex dynamics of multiple load types through a hierarchical control framework that combines actor-critic networks for continuous control actions. the control strategy employs a comprehensive seven-parameter state space encompassing voltage error, current measurement, solar irradiance, duty cycle history, voltage dynamics, error integration, and average voltage deviation. the experimental validation employs a buck converter maintaining 48V DC output from a 100V PV source, tested under challenging scenarios including 100W constant power load, 50W pulsed power load, and variable linear load conditions. the results demonstrate significant advantages over traditional PI control: 83% reduction in steady-state error, 75% improvement in voltage stability, and 73% faster load transition response. the controller successfully maintains voltage variations within +-1V across diverse load combinations, effectively addressing the destabilizing effects of constant power loads and sudden pulsed load changes. the integration of policy-based learning with on-policy SARSA implementation enables real-time adaptation without prior system modeling requirements. this approach showcases exceptional performance in both steady-state maintenance and transient response, particularly in scenarios involving mixed load characteristics. the framework provides a robust solution for modern DC microgrid applications requiring stable voltage regulation under complex load dynamics.

关键词： Voltage measurement Buck converters Microgrids Reinforcement learning systems modeling Real-time systems Stability analysis Regulation Steady-state Voltage control

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A Lightweight Broad Learning System for Wireless Traffic Prediction

A Lightweight Broad Learning System for Wireless Traffic Pre...

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international conference on Wireless communications and Signal Processing (WCSP)

作者： Xinyu Li Yajun Chen Mengwen Diao Hengfa Liu Xiao Liu Xin Wei School of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China Anhui Province Key Laboratory of Intelligent Building and Building Energy Saving Anhui Jianzhu University Hefei China

ISBN: (纸本)9781665450867

Currently, traffic trends to grow explosively under the scenarios of advanced wireless communication networks and diversified services. How to design suitable model to accurately and efficiently predict wireless traffic has become a significant technical challenge. To get over this dilemma, this paper proposes a lightweight broad learning system (LBLS) for wireless traffic prediction. Specifically, the LBLS firstly adopts restricted Boltzmann machine (RBM) to perform feature extraction. then, gated recurrent unit (G RU) is introduced into enhancement layer to describe temporal relations of multivariate time series. Finally, elastic-net considering both $L$ 1-norm and $L_{2}$ -norm regularization is used to realize connection weight estimation. Experimental results on two typical traffic datasets show that the proposed LBLS can not only reduce the complexity of existing BLS and its variants, but also has strong modeling and prediction ability for wireless traffic prediction.

关键词： Wireless communication Learning systems Time series analysis Estimation Predictive models Signal processing Logic gates

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three-dimensional Reconstruction of Retinal Blood Vessels based on Binocular Vision

Three-dimensional Reconstruction of Retinal Blood Vessels ba...

引用

international conference on Computational Intelligence and communication networks (CICN)

作者： Chao-liang Wu Zhi-jin Lv Hua-zhu Liu Xiao-fang Zhao ZHIXING College Of DGUT Dongguan University of Technology Dongguan China School of Computer Science and Technology Dongguan University of Technology Dongguan China International School of Microelectronics Dongguan University of Technology Dongguan China

ISBN: (纸本)9781665487726

Due to the limited perception ability of the naked eye, it is difficult to accurately locate the micro scale retinal vessels, which is easy to cause organ damage in the process of surgery. therefore, the retinal vascular reconstruction method based on binocular stereo vision is studied. Firstly, build a binocular vision detection system and then calibrate and correct the system. Secondly, filter and segment the collected 3D printed eyeball blood vessel model image, and calculate the parallax and depth map by constructing the error energy function. After that, the high-precision 3D point cloud model can be obtained. Finally, the error analysis of three-dimensional point cloud is carried out by binocular parallax principle. the experimental results show that this method can control the error within 0.5 mm and meet the requirements of retinal vascular surgery.

关键词： Point cloud compression Solid modeling Image segmentation three-dimensional displays Machine vision Surgery Blood vessels

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Time Efficient End-State Prediction through Hybrid Trace Decomposition Using Process Mining

Time Efficient End-State Prediction Through Hybrid Trace Dec...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Zeeshan Tariq Darryl Charles Sally McClean Ian McChesney Paul Taylor School of Computing Ulster University Belfast UK School of Com Eng & Int. Sys Ulster University Magee UK Applied Reseach BT Ipswich UK

ISBN: (纸本)9781665487726

In a real-world environment, business processes are complex and challenging to monitor for potential irregularities. Service-oriented organisations rely primarily on the effectiveness of their processes to maintain the quality of their offered services and prefer to be notified in advance if an ongoing business process is not executing as expected. Process mining techniques analyse business processes, but heterogeneity & variability in the real-world event logs make it challenging and time-consuming to mine using standard methods. Trace clustering divides event logs into sub-logs with similar properties based on the case and event attributes. However, given the size of the event logs collected from heterogeneous information systems, it is difficult to identify meaningful clusters in actual business process logs. this paper proposes a hybrid technique to decompose large event logs into several smaller sub-logs, making it easier and more time efficient to analyse. Each sub-log is independently investigated to gain valuable insights into the process's underlying behaviour. Non-traditional process mining techniques are applied to identify possible behavioural correlations and discrepancies between simulated and observed process execution by extracting features from the log segment. We used a real-world case study to depict our framework's usefulness in prediction accuracy and timeliness. Furthermore, we compared our findings to those of previously proposed methodologies from the literature. We demonstrated that the framework improved the fitness quality of the resultant business process models.

关键词： Fault diagnosis Correlation Feature extraction Data mining communication networks Monitoring Standards

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A New Low-Complexity WMMSE Algorithm for Downlink Massive MIMO systems

A New Low-Complexity WMMSE Algorithm for Downlink Massive MI...

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international conference on Wireless communications and Signal Processing (WCSP)

作者： Ningxin Zhou Zheng Wang Lanxin He Yang Huang School of Information Science and Engineering Southeast University Nanjing China College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9781665450867

Precoding is one of the most important technologies for downlink massive multiple-input multiple-output (MIMO) systems. Although the popular weighted minimum mean-square error (WMMSE) algorithm is guaranteed to converge to at least a local optimum of the weighted sum rate (WSR) maximization problem, its computational complexity is still too high due to the complicated matrix inversion. To this end, an iterative method based WMMSE algorithm (IM-WMMSE) is proposed in this paper. By adopting the traditional iterative methods to bypass the matrix inversion, the complexity of IM-WMMSE is significantly less than WMMSE with negligible performance loss. Meanwhile, inspired by deep learning, a deep neural network named as IM-WMMSE-Net is also designed for further complexity reduction. Simulation results demonstrate that IM-WMMSE is able to effectively reduce the computational complexity while the designed IM-WMMSE-Net achieves high performance with low computational complexity.

关键词： Deep learning Wireless communication Simulation Precoding Neural networks Signal processing algorithms Signal processing

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5G Virtual Private Network Planning Methodology Analysis

5G Virtual Private Network Planning Methodology Analysis

引用

international conference on Wireless communications and Signal Processing (WCSP)

作者： Tangbai Cheng Fang Zhou School of Communication and Information Engineering Shanghai Technical Institute of Electronics & Information City of Shanghai P.R.China School of Electrical and Information Engineering Anhui University of Technology City of Ma'anshan P.R.China

ISBN: (纸本)9781665450867

this paper analyses 5G virtual private network challenges and proposes corresponding innovative solutions. Firstly 5G virtual private network planning process is summarized, and services minimum design principles and hybrid services capacity planning methodology are proposed. Meanwhile coverage planning standard and new propagation model are introduced. these new planning solutions are important to 5G virtual network SLA guarantee.

关键词： Wireless communication Analytical models 5G mobile communication Design methodology Signal processing Planning Virtual private networks

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A Low Complexity Algorithm of Beamforming Optimization for IRS-Assisted MIMO systems

A Low Complexity Algorithm of Beamforming Optimization for I...

引用

international conference on Signal Processing systems, ICSPS

作者： Chuangqi Shi Yajun Wang Shuang Liu Shanjie Cai Ocean College Jiangsu University of Science and Technology Zhenjiang China

In order to provide secure, efficiency and high- quality mobile wireless communication with limited wireless resources and improve network spectral efficiency. In this paper, we consider an intelligent reflecting surface (IRS) assisted point- to-point multi-input multi-output (MIMO) communication system. According to the sum-path-gain maximization criteria, under the single-mode constraints of the phase shift vector and the maximum transmitting power constraints of the transmitting side, the spectral efficiency of the system is maximized. the linear alternating direction multiplier (LADMM) algorithm is used to optimize the phase shift of the IRS and the precoding matrix of the transmitter. By Taylor expansion of the objective function, the inverse operation of matrix in iterations is avoided. the results show that this method reduces the computational complexity, higher spectral efficiency can be achieved, the spectral efficiency and performance of the system have been further improved.

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Oil Spill Identification using Deep Convolutional Neural networks

Oil Spill Identification using Deep Convolutional Neural Net...

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international conference on Computational Intelligence and communication networks (CICN)

作者： David M. Feinauer Ghazanfar Latif Abeer M. Alenazy Nizar Tayem Jaafar Alghazo Loay Alzubaidi Department of Electrical and Computer Engineering Virginia Military Institute Lexington VA USA Computer Science Department Prince Mohammad Bin Fahd University Khobar Saudi Arabia Department of Engineering and Technology Texas A&M University Commerce USA Faculty of Computer Information Systems Higher Colleges of Technology United Arab Emirates

ISBN: (纸本)9781665487726

Oil spill detection is an extremely important topic in which Machine Learning (ML) can be utilized because oil spills that go undetected can cause huge environmental negative impacts. the science of how an oil spill can cause devastation to wildlife has been widely viewed with sorrow and the early detection of oil spills can greatly reduce the negative impact oil spills have on the environment. If an optimal solution is found for oil spill detection, continuous monitoring can be achieved either through satellite images or images obtained from unmanned aerial vehicles such as drones. In this paper, we develop a dataset for oil spill detection collected from images from the Internet and other online resources. the dataset consists of 783 images of Oil Spills and 783 normal images. Since these are real-world images, research done on this dataset will produce a more realistic and practical solution. In this paper, we also propose an enhanced CNN model based on GoogleNet and VGG16 combined with transfer learning for the detection and classification of oil spills. the GoogleNet Transfer Learning model achieved better results of training accuracy of 97.5%, training loss of 0.0894, and validation accuracy of 95.6%. Since this is a new dataset, the results cannot be compared to anything in the extant literature.

关键词： Training Satellites Oils Transfer learning Wildlife Internet Convolutional neural networks

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Channel Modeling Based On Quantum Generative Adversarial Network

Channel Modeling Based On Quantum Generative Adversarial Net...

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international conference on Wireless communications and Signal Processing (WCSP)

作者： Zhairui Gong Xinling He Zhifan Wan Zetong Li Xianchao Zhang Xutao Yu School of Information Science and Engineering Southeast University Nanjing China Agricultural Bank of China Data Center Shanghai China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing China

ISBN: (纸本)9781665450867

Channel modeling is indispensable in a communication system. In this paper, a novel scheme for channel modeling using quantum generative adversarial model was proposed. A quantum generative adversarial network is a generative adversarial model with a quantum circuit as the generative module and a deep neural network as the discriminant module, thereby exploiting the privilege of quantum algorithms in simulating probability distributions to stochastic channel models. Experiments were conducted on IBM QX quantum computing platform. the gradient descent of the cost function and Kullback-Leibler divergence were analyzed. Results verify the feasibility and superiority of the quantum generative adversarial network for channel modeling.

关键词： Wireless communication Quantum algorithm Computational modeling Neural networks Stochastic processes Signal processing Generative adversarial networks

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Isolation Enhancement in Closely Packed Wideband Antennas Using Metasurface 14

Isolation Enhancement in Closely Packed Wideband Antennas Us...

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14th international conference on Microwave and Millimeter Wave Technology (ICMMT)

作者： Qiu, Wenlu Li, Jinxin Xiao, Pei Liu, Zhu Dong, Jun Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Hunan Peoples R China Nanjing Univ Posts & Telecommun Natl & Local Joint Engn Lab RF Integrat & Microas Nanjing 210023 Peoples R China Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hunan Normal Univ Sch Phys & Elect Changsha 410081 Hunan Peoples R China Hunan Normal Univ Coll Informat Sci & Engn Changsha 410081 Hunan Peoples R China

ISBN: (纸本)9781665467520

A planar anisotropic metasurface superstrate structure for isolation enhancement of two closely packed antennas is proposed in this paper. the spacing of the initial antennas is only 0.12 lambda(0) at 3.55 GHz (lambda(0) is the wavelength at the center frequency). the metasurface structure is consists of periodic rectangular-loop unit resonators, which are printed on the one side of 1.5 mm thick FR-4 substrate in E -plane. By placing the decoupling structure beside the initial antennas instead of putting it in the middle of the antennas, it can reject coupling wave propagation and improve isolation of two ports of the antenna further. the simulated results show that the proposed metasurface structure is able to achieve port isolation improvement at least 19.7dB and at most 31.9dB with in the operation band from 3.3 to 3.8 GHz. More importantly, the antenna still keeps good performance with S< -10 dB and has tendency to broaden bandwidth, while the metasurface superstrate structure is loaded.

关键词： Mutual coupling reduction multiple-input-multiple-output (MIMO) metasurface isolation enhancement 5G communication system

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