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检索条件"任意字段=Joint International Conference on Measurement and Modeling of Computer Systems"

共 7880 条记录，以下是391-400 订阅

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Methodology for Metrological Analysis of a Measuring Situation Allowing Consideration of Functional Relationships between Measured Quantities and Examples of its Application

Methodology for Metrological Analysis of a Measuring Situati...

引用

international conference on Soft Computing and measurements (SCM)

作者： Vladimir A. Garanin Higher School of Computer Technologies and Information Systems Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (数字)9798350363708

ISBN: (纸本)9798350363715

The work is devoted to the metrological analysis of situations of joint measurement of the values of several desired quantities, for which such dependencies between them exist and are known a priori that, for at least one of the quantities to be measured, we can obtain one or more independent estimates with their help from the values of other measured quantities. To calculate the limits of possible error in the results of processing such joint measurements, taking into account the mentioned a priori information, a universal technique is proposed that considers the uncertainties of the results of measurements performed and the parameters of the equations describing known relationships. The methodology is developed for cases when the relationships between measurands are expressed as one or more equations. The paper presents examples of its use for performing metrological analysis of typical measuring situations).

关键词： Uncertainty measurement uncertainty Mathematical models Reliability

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Machine and deep learning approaches for modeling global horizontal irradiation dynamics: A case study 4

Machine and deep learning approaches for modeling global hor...

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4th international conference on Applied Automation and Industrial Diagnostics, ICAAID 2022

作者： Boubaker, Sahbi University of Jeddah College of Computer Science and Engineering Department of Computer and Network Engineering Jeddah21959 Saudi Arabia

ISBN: (纸本)9781728189390

Global Horizontal Irradiation (GHI) is the most critical parameter in the design of solar energy plants. More than being relatively expensive, GHI measurement stations require frequent maintenance and their accuracies are still questionable. Thus, one of the frequent practices to cope with such difficulties is the dynamic prediction of GHI. Several techniques have been already utilized for forecasting GHI including time-series, swarm intelligence and many empirical equations. In the last few years, machine learning (ML) has emerged as a strong tool for modeling complex dynamic systems. Due to the non-Availability of accurate meteorological data known to affect the GHI, this paper aims to investigate machine/deep learning algorithms for predicting GHI dynamics. The proposed models used previous lags of the GHI itself as unique explanatory variables. Based on the King Abdullah Center for Atomic and Renewable Energy (KACARE) records collected from Hail, Saudi Arabia, and statistical performance indicators, several dynamic models are investigated, tested and compared. The obtained results have shown the superiority of deep-learning artificial neural networks (DL-ANNs) with small numbers of neurons in 5-hidden layers structure trained using resilient-propagation fast algorithm. The best performances obtained for the testing dataset were a MAPE of 5.3219%, an R2 of 0.7993 and an RMSE of 5.8418 wh/m2/day. © 2022 IEEE.

关键词： Irradiation

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Research on key technologies of four-rotor UAV flight control system based on STM32 microcontroller

Research on key technologies of four-rotor UAV flight contro...

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international conference on Information systems and computer Aided Education (ICISCAE)

作者： Zhiwei Ren Zucai Tang Ranran Wang School of Geophysics and Information Technology China University of Geosciences (Beijing) Beijing China School of Automation Shenyang Aerospace University Shenyang China Leicester International Institute Dalian University of Technology Panjin China

In order to realize the self-stabilization control of the four-rotor UAV, the dynamic modeling and control of the four-rotor UAV are carried out. In the modeling, the dynamic simulation model of the four-rotor aircraft is established by using the combination of mechanism modeling and experimental measurement. The inverse kinematics algorithm is used to decompose the attitude model into three independent subsystems, which control the roll, pitch and yaw motion of the body respectively. The sliding mode controller based on the stability theorem is designed for the decomposed subsystems through the distributed control strategy, and the whole system is simulated on the Matlab platform. The simulation results show that the dynamic model and PID controller can effectively realize the self-stabilization control of the aircraft, which lays a foundation for the subsequent control research of the four-rotor aircraft.

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Analog modeling of agricultural soil included in a simple temperature control scheme 16

Analog modeling of agricultural soil included in a simple te...

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16th international conference on Engineering of Modern Electric systems (EMES)

作者： Monica, Sas Diana Rodica, Varban Helga, Silaghi Fac Elect Engn & Informat Technol Dept Control Syst Engn & Management Oradea Romania Univ Agr Sci & Vet Med Dept Crops Sci Cluj Napoca Romania

ISBN: (纸本)9781665449953

This paper presents a primary theoretical research for a simplified version of analog modeling of an agricultural soil, both isolated and included in a simple temperature control scheme. Also, are exposed some specific details for interpretation of processed signals evolution, being emphasized the application aspects for such a system.

关键词： Agricultural soil simplified analog model approximate solutions for second order partial differential equations with two variables exponential functions computer analog modeling

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A Robust Broad Learning System for Classification Problems in Label Noise Environments

A Robust Broad Learning System for Classification Problems i...

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Machine Learning and computer Application (ICMLCA), international conference on

作者： Jiale Wang Civil Aviation University of China Institute of Electronics and Information Tianjin China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

In response to the problem of reduced performance of classification models due to label noise in real-world scenarios, this paper proposes a robust broad learning system that suppresses noise effectively and has parameter adaptive capabilities. The system is built within a broad learning framework characterized by fast learning ability and universal approximation ability. To enhance the model's ability to handle noise, a loss function is constructed using the kernel risk-sensitive mean p-power (KRP) criterion to train the output weights, which suppresses the influence of noisy samples in the loss function. The proposed model is theoretically proven to be robust. Experimental results on nine classification datasets demonstrate that the proposed model exhibits good generalization ability and robustness.

关键词： Learning systems Adaptation models Adaptive systems Computational modeling Noise Machine learning computer applications Robustness Noise measurement Kernel

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Performance and Power: Systematic Evaluation of AI Workloads on Accelerators with CARAML

Performance and Power: Systematic Evaluation of AI Workloads...

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High Performance Computing, Networking, Storage and Analysis, SC-W: Workshops of the international conference for

作者： Chelsea Maria John Stepan Nassyr Carolin Penke Andreas Herten Jülich Supercomputing Centre Forschungszentrum Jülich Jülich Germany

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

The rapid advancement of machine learning (ML) technologies has driven the development of specialized hardware accelerators designed to facilitate more efficient model training. This paper introduces the CARAML benchmark suite, which is employed to assess performance and energy consumption during the training of transformer-based large language models and computer vision models on a range of hardware accelerators, including systems from NVIDIA, AMD, and Graphcore. CARAML provides a compact, automated, extensible, and reproducible framework for assessing the performance and energy of ML workloads across various novel hardware architectures. The design and implementation of CARAML, along with a custom power measurement tool called jpwr, are discussed in detail.

关键词： Training Energy consumption computer vision Computational modeling Energy measurement computer architecture Benchmark testing Energy efficiency Usability Hardware acceleration

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modeling of Photovoltaic-Wind Hybrid systems 3

Modeling of Photovoltaic-Wind Hybrid Systems

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3rd international conference on Communications, Information, Electronic and Energy systems, CIEES 2022

作者： Isaied, Mohammad Tarabsheh, Anas Al Abu Dhabi University Dept. of Computer And Biomedical Engineering Abu Dhabi United Arab Emirates Abu Dhabi University Dept. Electrical Computer And Biomedical Engineering Abu Dhabi United Arab Emirates The Hashemite University Dept. Faculty of Engineering Electrical Engineering Zarqa Jordan

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

This article proposes a model for photovoltaic-wind hybrid systems. The system under investigation comprises five PV modules attached to the blades of a vertical-axis wind turbine. The solar irradiation readings at each PV module are monitored at three different tilt angles: 90°(default), 50°, and 10°. These measurements are taken on many selected days at random times around noon. This paper calculates the solar irradiation received at each PV module and estimates the optimum tilt angle of the system. A simple clear sky model is used for the calculation, the input data of the model is the solar geometry, including location latitude, solar azimuth angle and solar elevation angle, no aerosol or atmospheric data is necessary. A comparison between measurement and calculated data is conducted, and the result shows that the optimum tilt angle is 50°. The mean absolute percentage error is computed between the measured and calculated values and shows that it ranges between 11% and 17% at a 90° tilt angle, and between 5% and 17.4% at a 50° tilt angle. © 2022 IEEE.

关键词： Wind power

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modeling of Weight Perception Based on Subjectivity by Considering Individual Differences

Modeling of Weight Perception Based on Subjectivity by Consi...

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international Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Daisuke Kushida Kei Nakajima Dept. Electrical Engineering and Computer Science Faculty of Engineering Tottori University Tottori Japan Dept. Engineering Graduate School of Sustainability Science Tottori University Tottori Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

The minimum amount of perception that humans can perceive is called the stimulus threshold. This study aims to clarify the stimulus threshold of weight perception for the biceps brachii muscle based on a method of constant stimuli. In general, the stimulus threshold depends on the individual. The authors consider that physical characteristics are related to individual differences, construct a model of the relationship between physical characteristics and stimulus thresholds, and attempt to estimate stimulus thresholds from physical characteristics. The constructed model is evaluated via cross-validation and found to be able to estimate stimulus thresholds from physical characteristics with an 85% accuracy.

关键词： Accuracy Predictive models Muscles Load modeling

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Application of an ANN and LSTM-Based Ensemble Model for Stock Market Prediction

Application of an ANN and LSTM-Based Ensemble Model for Stoc...

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international conference on Information systems and computer Aided Education (ICISCAE)

作者： Fang Liu Shaobo Guo Qianwen Xing Xinye Sha Ying Chen Yuhui Jin Qi Zheng Chang Yu

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

Stock trading has always been a key economic indicator in modern society and a primary source of profit for financial giants such as investment banks, quantitative trading firms, and hedge funds. Discovering the underlying patterns within the seemingly volatile yet intrinsically structured economic activities has become a central focus of research for many companies. Our study leverages widely-used modern financial forecasting algorithms, including LSTM, ANN, CNN, and BiLSTM. We begin by comparing the predictive performance of these well-known algorithms on our stock market data, utilizing metrics such as R2, MAE, MSE, RMSE for detailed evaluation. Based on the performance of these models, we then aim to combine their strengths while mitigating their weaknesses, striving to construct a powerful hybrid model that overcomes the performance limitations of individual models. Through rigorous experimentation and exploration, we ultimately developed an LSTM+ANN model that breaks through prior performance bottlenecks, achieving promising and exciting results.

关键词： measurement Solid modeling Biological system modeling Computational modeling Stacking Predictive models Prediction algorithms Stock markets Protection Investment

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Multipactor in a Coaxial Geometry with Non-Sinusoidal RF Fields

Multipactor in a Coaxial Geometry with Non-Sinusoidal RF Fie...

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international conference on Vacuum Electronics

作者： Asif Iqbal Patrick Wong Sandhiya Suresh Peng Zhang De-Qi Wen Shu Lin John Verboncoeur Deparment of Electrical and Computer Engineering Michigan State University East Lansing MI USA Albuquerque NM USA Department of Computational Mathematics Science and Engineering Michigan State University East Lansing MI USA Key Laboratory for Physical Electronics and Devices of the Ministry of Education Xi'an Jiaotong University Xi'an China

ISBN: (数字)9798350348705

ISBN: (纸本)9798350348712

We investigate multipactor in a coaxial geometry with non-sinusoidal Gaussian-type RF fields by employing 3D electromagnetic particle-in-cell (PIC) simulations, ID analytical calculations, and statistical modeling. For different aspect ratios of a coaxial geometry, we analyze the effects of the RF amplitude and the full width at half maximum (and/or half minimum) (FWHM) on multipactor susceptibility and the time dependent physics. We find that with Gaussian-type RF operation, the threshold peak RF voltage as well as the threshold time averaged RF power per unit area for multipactor increases compared to that with sinusoidal RF operation. The effects of the Gaussian-type RF operation on the deposited power densities by multipacting particles on the inner and outer conductors are also analyzed.

关键词： Radio frequency Geometry Solid modeling Power system measurements Three-dimensional displays Density measurement Computational modeling Color Conductors Bars

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