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检索条件"主题词=software algorithms"

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Development of an Iteration Based Design Algorithm for High Frequency Transformer Incorporated in Solid State Transformer

Development of an Iteration Based Design Algorithm for High ...

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Trends in Engineering Systems and Technologies (ICTEST), International Conference on

作者： Sherin Joseph Shajimon K John Department of Electrical and Electronics Engineering Saintgits College of Engineering Kottayam APJ Abdul Kalam Technological University Thiruvananthapuram Kerala India Department of Electrical Engineering College of Engineering Chengannur Department of Electronics and Communication Muthoot Institute of Technology and Science Ernakulam APJ Abdul Kalam Technological University Thiruvananthapuram Kerala India

ISBN: (数字)9798350307795

ISBN: (纸本)9798350307801

Solid State Transformer(SST) is a key element in evolving smart-grid system due to its control and communication capability along with the conventional power transfer operation. The control of power flow is achieved by the incorporation power electronic converters at either sides of the transformer. The transformers used in SST is of high frequency type to reduce the size, weight and volume. This transformer which is incorporated in SST is known as High Frequency Transformer (HFT). For the optimum design of SST, of a specific power and voltage rating, the power electronic switches used are of specific ratings, so the optimum design of HFT determines the optimum design of SST. This paper details the optimum design of a high frequency transformer for the design of solid state transformer. The objective function considered for the optimization of HFT is minimization of Total Owning Cost (TOC). The optimum design is generated from an iterative algorithm, which is developed using Brute Force Technique. A case study is performed in a 1000kVA, 11kV/415V SST by varying different parameters such as magnetic materials, AC test voltage, load factor etc. The validation of the optimum design developed is done in Ansys Maxwell software and the results are comparable with the optimum design developed from the iterative algorithm.

关键词： Costs software algorithms Force Transformer cores Mathematical models Power electronics software

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Reinforcement Learning-driven automatic calibration for color segmentation-based robot detection

Reinforcement Learning-driven automatic calibration for colo...

引用

IEEE Latin American Robotics Symposium, LARS

作者： Clara Acruchi Geovany Icaro L. Nunes Thiago José A. Souza Breno Cavalcanti Adiel Teixeira de A. Filho Mateus G. Machado Edna N. Barros Centro de Informática Universidade Federal de Pernambuco Recife Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

The systems designed to accomplish the color segmentation task are based on machine-learning-based color classifiers or deterministic algorithms, which usually rely on manual parameter calibration to perform well. Robot soccer competitions such as IEEE VSSS and RoboCup SSL rely on the latter type of vision software and thus suffer from manual calibration, which can be time-consuming and highly depend on operator proficiency and lighting conditions. As a challenge of IEEE VSSS, the teams must develop their robot detection software. Therefore, the present work proposes automatic calibration for color segmentation and robot detection systems as a black-box optimization problem. Then, applying the formulation of the IEEE VSSS robot detection software used in LARC 2023, it compares different methods to solve the problem with multi-armed bandit reinforcement learning algorithms. The analysis includes a detailed evaluation of the performance and efficiency of these methods in enhancing the precision and reliability of robot detection.

关键词： software algorithms Lighting Color Reinforcement learning Manuals Calibration software reliability Robots Optimization Sports

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Impact of Model Selection on Pulmonary Effusion Diagnosis Using Prediction Analysis algorithms

Impact of Model Selection on Pulmonary Effusion Diagnosis Us...

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Communication, Computer Sciences and Engineering (IC3SE), International Conference on

作者： Chandra Mani Divya Pachauri Richa Gupta Neeraj Varshney Manika Manwal Computer Science & Engineering Raj Kumar Goel Institute of Technology Ghaziabad UP India Department of CSE-AIML NITRA Technical Campus Ghaziabad UP India Computer Science & Engineering Graphic Era Hill University Dehradun Uttarakhand India Department of Computer Engineering and Applications GLA University Mathura UP India Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Model selection is of utmost significance for accurate analysis and treatment of pulmonary effusion. With the increasing complexity of scientific statistics and the advancement of prediction analysis algorithms in the clinical field, model selection has emerge as a critical step in a hit prediction evaluation. In this text, we have a look at the effect of version choice on pulmonary effusion prognosis the use of a hard and fast of prediction evaluation algorithms. We compare the overall performance of different algorithms in phrases of accuracy, kind-I and sort-II errors, and interpretability. We demonstrate that version selection can have an effect on the accuracy and interpretability of the diagnosis and for this reason the remedy plan installed for the patient. We in addition talk the consequences for practitioners, clinicians, and researchers, who have to don't forget the deserves of model choice whilst the use of prediction analysis algorithms for the analysis of pulmonary effusion. Version choice is a crucial a part of the predictive evaluation pipeline, as the selection of version for given software may have a large effect on accuracy and performance. In the context of pulmonary effusion (PE) analysis, an appropriate choice of a predictive evaluation set of rules can enhance the detection of PE abnormalities and facilitate scientific decision making. Numerous algorithms were carried out to broaden models for PE prognosis, which includes synthetic neural networks, help vector machines, logistic regression, and decision trees.

关键词： Analytical models Accuracy Computational modeling Biological system modeling software algorithms Lung Vegetation

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Performance Enhancement of Photovoltaic Systems Using Parrot Optimization Algorithm-Based Optimal Control Scheme

Performance Enhancement of Photovoltaic Systems Using Parrot...

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Smart Power & Internet Energy Systems (SPIES), International Conference on

作者： Ayedh H. Alqahtani Hany M. Hasanien Electrical Engineering Department College of Technological Studies Public Authority for Applied Education and Training Kuwait Electrical Power and Machines Department Faculty of Engineering Ain Shams University Cairo Egypt

ISBN: (数字)9798350368864

ISBN: (纸本)9798350368871

This paper presents an optimized control strategy for enhancing the low-voltage-ride-through (LVRT) capability of photovoltaic (PV) systems. The proposed method employs a proportional-integral (PI) controller, which is designed using the Parrot Optimization Algorithm (POA). The PV system is connected to the grid via a DC boost chopper and a grid-side inverter. The incremental conductance method is applied to track the maximum power of the PV system. A cascaded control strategy is implemented to control the grid-side inverter. The effectiveness of the POA-PI controller is tested under various symmetrical and asymmetrical fault conditions, demonstrating significant performance improvements. The results are compared with those obtained from a genetic algorithm-PI control system. Numerical simulations are carried out using PSCAD/EMTDC software, illustrating the robustness of the proposed approach.

关键词： Photovoltaic systems Renewable energy sources Simulation Power system dynamics software algorithms Choppers (circuits) Inverters software Smart grids Optimization

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Applying Machine Learning to Enhance Intrusion Detection Systems

Applying Machine Learning to Enhance Intrusion Detection Sys...

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Contemporary Computing and Communications (InC4), IEEE International Conference on

作者： Amit Garg Ramya N Rishi Gupta J. Logeshwaran Department of CSE Manipal University Jaipur Jaipur INDIA Department of ECE M Kumarasamy College of Engineering Karur INDIA Department of ECE Sri Eshwar College of Engineering Coimbatore INDIA

ISBN: (数字)9798350383652

ISBN: (纸本)9798350383669

Gadget up to date has shown its effectiveness in several packages, identifying styles and detecting anomalies. One such software enhances intrusion detection structures (IDS), which are essential for shielding up-to-date networks from malicious attacks. However, as the complexity and quantity of network information updated, traditional IDS strategies are becoming much less efficient and accurate. This technical summary focuses on the software of system learning techniques up to date enhance IDS. Specially, we explore how supervised, unsupervised, and deep learning algorithms can be used come across and respond up-to-date anomalies in network those algorithms can analyze and adapt up to date new assault styles, making them extra powerful at detecting and up-to-date cyber-attacks. Furthermore, they can manage massive amounts of records without compromising accuracy, making them appropriate for actual-time intrusion detection.

关键词： Deep learning Accuracy Machine learning algorithms software algorithms Intrusion detection software Complexity theory

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Research on the Application of Artificial Intelligence Technology in ADS-B Data Anomaly Detection

Research on the Application of Artificial Intelligence Techn...

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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Xianyu Lu Haitao Chen Guangzhou Civil Aviation College Guangzhou China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Automatic Dependent Surveillance Broadcast (ADS-B) system is widely used in the field of aerial surveillance because of its accuracy and high efficiency. However, ADS-B system is easy to be spoofed and interfered because it broadcasts signals in plaintext format and lacks data encryption and message authentication mechanism. This article conducts research on this issue. Firstly, it analyzes the structure of the ADS-B system and discusses its data anomaly problems. It summarizes that researchers at home and abroad generally approach the solution to data anomaly problems from three directions: encrypting the data link, improving the ADS-B hardware and software, and analyzing from the perspective of the ADS-B data fields. Then, it particularly points out that artificial intelligence algorithms also build models from the perspective of the ADS-B data fields to complete ADS-B track data anomaly detection, including algorithms based on clustering, data reconstruction, and data temporal correlation. Finally, this paper compares the detection precision, recall rate, and F1 score of several deep learning algorithm models based on data time-related, and finds that they all have excellent ADS-B data anomaly detection effects, with detection precision all above 92.2%, recall rate all above 84.9%, and F1 score all above 86.8%.

关键词： Surveillance Heuristic algorithms software algorithms Clustering algorithms Predictive models Prediction algorithms Data models software Anomaly detection Message authentication

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Optimization and Dynamic Analysis of a Natural Gas Assisted LCPV/T Triple-generation System

Optimization and Dynamic Analysis of a Natural Gas Assisted ...

引用

Power Energy Systems and Applications (ICoPESA), International Conference on

作者： Zhen Yao Huixia Sheng Yang Liu National Institute of Metrology Beijing China SPIC Zhengzhou Gas Power Generation CO.LTD China

ISBN: (数字)9798350351668

ISBN: (纸本)9798350351675

This paper presents an optimization analysis method of the natural gas assisted low-concentrating photovoltaic/thermal (LCPV/T) triple-generation system. The main energy sources of this triple-generation system are solar energy and nature gas, to achieve the purpose of year-round supply of cooling, heating and electricity to the building. The system comprises of a low-concentrating photovoltaic/thermal system, heat pump, absorption chiller, water tanks, and capillary network. The core of the whole system is the low-concentrating photovoltaic/thermal system, used for space heating, electrical production, space cooling and domestic hot water preheating. In particular, an operation strategy and integrated optimization model are established in order to reduce the life cycle costs. Furthermore, a penalty function is implemented in order to balance lab room comfort with operating costs of the triple-generation system. The construction of the whole system, the realization of the operation strategy and the optimization calculation are all realized by TRNSYS software.

关键词： Photovoltaic systems Costs Heuristic algorithms software algorithms Water heating Space cooling Optimization Natural gas Space heating Resistance heating

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Comparison of Doppler Estimation Methods in Mobile Underwater Acoustic Communication

Comparison of Doppler Estimation Methods in Mobile Underwate...

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OCEANS

作者： Patrick J. Donnelly Kerem Enhos Emrecan Demirors Deniz Unal Tommaso Melodia Hydronet Inc. Burlington MA USA Institute for The Wireless Internet of Things Northeastern University Boston MA USA

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

Underwater acoustic (UWA) communication and networking have been of great interest in recent years and find utility in various commercial and military applications, including underwater surveillance, environmental monitoring, data-driven intelligent aquaculture, and unmanned underwater vehicles. However, due to the relatively low propagation ve-locity of sound through water, even modest velocities between transmitter and receiver translate into extreme Doppler shifts, marring transmission quality. The Doppler effect is amplified for high-frequency transmission, further complicating Doppler estimation and compensation. In this paper, we present three distinct Doppler estimation techniques based on linear frequency-modulated signals: displacement estimation, using preamble and postamble correlation; slope estimation, using the Fractional Fourier Transform (FrFT); and dilation estimation, using a novel matched filtering technique. We compare the efficacy of these three methods across three different scenarios: first, in simulation using a simplified channel model, and then in real-world UWA channels, employing both stationary and mobile node setups with software-defined Hydronet Modems.

关键词： Transmitters Heuristic algorithms software algorithms Estimation Channel estimation Modems Mobile nodes Doppler effect Underwater acoustics Vehicle dynamics

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A Framework for Reproducible Benchmarking and Performance Diagnosis of SLAM Systems

A Framework for Reproducible Benchmarking and Performance Di...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Nikola Radulov Yuhao Zhang Mihai Bujanca Ruiqi Ye Mikel Luján Department of Computer Science University of Manchester UK Qualcomm Technologies XR Labs Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We propose SLAMFuse, an open-source SLAM benchmarking framework that provides consistent cross-platform environments for evaluating multi-modal SLAM algorithms, along with tools for data fuzzing, failure detection, and diagnosis across different datasets. Our framework introduces a fuzzing mechanism to test the resilience of SLAM algorithms against dataset perturbations. This enables the assessment of pose estimation accuracy under varying conditions and identifies critical perturbation thresholds. SLAMFuse improves diagnostics with failure detection and analysis tools, examining algorithm behaviour against dataset characteristics. SLAMFuse uses Docker to ensure reproducible testing conditions across diverse datasets and systems by streamlining dependency management. Emphasizing the importance of reproducibility and introducing advanced tools for algorithm evaluation and performance diagnosis, our work sets a new precedent for reliable benchmarking of SLAM systems. We provide ready-to-use docker compatible versions of the algorithms and datasets used in the experiments, together with guidelines for integrating and benchmarking new algorithms. Code is available at https://***/nikolaradulov/slamfuse

关键词： software maintenance Simultaneous localization and mapping Perturbation methods software algorithms Benchmark testing Fuzzing Reproducibility of results Reliability Stress Resilience

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Implementation of Mental Medical Registration Algorithm Based on Psychopathology Model

Implementation of Mental Medical Registration Algorithm Base...

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software Engineering, Social Network Analysis and Intelligent Computing (SSAIC), Asia-Pacific Conference on

作者： Zhuoxin He Shantou University Medical College Shantou Guangdong China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

Psychopathology also refers to psychopathology, which is a scientific study of various psychological disorders. Strictly speaking, the research fields it involves include psychologists, psychiatrists, neuroscientists, endocrinologists and pharmacologists, which are different from the medical practice of clinical psychologists and psychiatrists who treat psychological disorders. In this paper, we propose a mental medical registration algorithm based on psychopathology model, which sets the search direction as the initial orthogonal search direction again after every complete update of the search direction. The experiment shows that the registration algorithm in this paper only needs about 150 iterations to reach the optimal solution, while the genetic algorithm needs 210 times. The experimental data fully show that the registration algorithm has a good global search ability, and has achieved good results. The registration technology is used to fuse the image information obtained under different conditions, integrate the advantages of various imaging devices, and express the patient’s mental information as much as possible in psychopathology, becoming a strong backing for clinical medical observation, diagnosis and treatment of boils in psychiatry.

关键词： Social networking (online) Computational modeling software algorithms Psychology Medical treatment Medical diagnostic imaging Optimization

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