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linear algorithms for Radioelectric Spectrum Forecast

algorithms 2016年第4期9卷 82-82页

作者： Pedraza, Luis F. Hernandez, Cesar A. Paez, Ingrid P. Ortiz, Jorge E. Rodriguez-Colina, E. Univ Dist Francisco Jose de Caldas Fac Technol Bogota 110231 Colombia Univ Nacl Colombia Fac Engn Dept Ind & Syst Engn Bogota 111321 Colombia Univ Autonoma Metropolitana Iztapalapa Dept Elect Engn Mexico City 09340 DF Mexico

This paper presents the development and evaluation of two linear algorithms for forecasting reception power for different channels at an assigned spectrum band of global systems for mobile communications (GSM), in order to analyze the spatial opportunity for reuse of frequencies by secondary users (SUs) in a cognitive radio (CR) network. The algorithms employed correspond to seasonal autoregressive integrated moving average (SARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH), which allow for a forecast of channel occupancy status. Results are evaluated using the following criteria: availability and occupancy time for channels, different types of mean absolute error, and observation time. The contributions of this work include a more integral forecast as the algorithm not only forecasts reception power but also the occupancy and availability time of a channel to determine its precision percentage during the use by primary users (PUs) and SUs within a CR system. Algorithm analyses demonstrate a better performance for SARIMA over GARCH algorithm in most of the evaluated variables.

关键词： cognitive radio time series linear algorithms

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On sets of linear forms of maximal complexity

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COMPUTATIONAL COMPLEXITY 2023年第1期32卷 1-26页

作者： Kaminski, Michael Shparlinski, Igor E. Waldschmidt, Michel Technion Israel Inst Technol Dept Comp Sci IL-3200003 Haifa Israel Univ New South Wales Sch Math & Stat Sydney NSW 2052 Australia Sorbonne Univ CNRS IMJ PRG F-75005 Paris France Univ Paris CNRS IMJ PRG F-75005 Paris France

We present a uniform description of sets of m linear forms in n variables over the field of rational numbers whose computation requires m(n - 1) additions.

关键词： linear algorithms additive complexity effective Perron theorem common nonzeros of polynomials

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Machine learning-based prediction of hydrogen-assisted fatigue crack growth rate in Cr-Mo steel

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 122卷 1-11页

作者： Hu, Jiangchuan Ma, Kai Zhang, Zhenquan Zhang, Ruiming Zheng, Jinyang Zhejiang Univ Inst Adv Equipment Hangzhou 310027 Zhejiang Peoples R China MOE Engn Res Ctr High Pressure Proc Equipment & Safety Beijing Peoples R China Zhejiang Univ Key Lab Hydrogen Storage & Transportat Technol Zhe Hangzhou 310027 Zhejiang Peoples R China

In this study, linear and tree-based algorithms were utilized to train the hydrogen-assisted fatigue crack growth test data. Through accuracy verification, it was found that the Gradient Boosting Regression (GB) belonging to tree-based algorithms had the best predictive performance. For the model trained by the GB algorithm, SHapley Additive exPlanations (SHAP) values were employed to evaluate the impact of stress intensity factor range, hydrogen pressure, ultimate tensile strength, stress ratio, frequency and chemical compositions on the hydrogenassisted fatigue crack growth. The results show that material properties, experimental conditions and environment all have an effect on the crack growth rate. Besides, the feature influence patterns derived from machine learning models are consistent with the literature, demonstrating that the model has the potential to accurately predict the hydrogen-assisted fatigue crack growth rate of Cr-Mo steel.

关键词： Machine learning linear algorithms Tree-based algorithms Cr-Mo steel Hydrogen-assisted fatigue crack growth rate Prediction model

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Completeness Criteria for a linear Model of Classification algorithms with Respect to Families of Decision Rules

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DOKLADY MATHEMATICS 2020年第1期101卷 57-59页

作者： D'yakonov, A. G. Golovina, A. M. Lomonosov Moscow State Univ Fac Computat Math & Cybernet Moscow 119991 Russia Natl Res Univ Bauman Moscow State Tech Univ Moscow 105005 Russia

In the framework of Zhuravlev's algebraic approach to classification problems, a linear model of algorithms is investigated (estimates of class membership are generated by linear regressions). The possibility of weakening the completeness requirement (obtaining an arbitrary estimation matrix) in order to obtain any classification of a fixed set of objects by using special decision rules is investigated.

关键词： classification linear algorithms algebraic approach correctness completeness

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Sets of linear Forms Which Are Hard to Compute 46

Sets of Linear Forms Which Are Hard to Compute

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46th International Symposium on Mathematical Foundations of Computer Science, MFCS 2021

作者： Kaminski, Michael Shparlinski, Igor E. Department of Computer Science Technion - Israel Institute of Technology Haifa Israel School of Mathematics and Statistics University of New South Wales Sydney Australia

ISBN: (纸本)9783959772013

We present a uniform description of sets of m linear forms in n variables over the field of rational numbers whose computation requires m(n1) additions. Our result is based on bounds on the height of the annihilating polynomials in the Perron theorem and an effective form of the Lindemann-Weierstrass theorem which is due to Sert (1999). © Michael Kaminski and Igor E. Shparlinski;licensed under Creative Commons License CC-BY 4.0 46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021).

关键词： Additive complexity Effective lindemann-weierstrass theorem Effective perron theorem linear algorithms

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Distributed non-linear robust consensus-based sensor calibration for networked control systems

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IET CONTROL THEORY AND APPLICATIONS 2020年第9期14卷 1200-1208页

作者： Stankovic, Maja S. Antic, Dragan S. Univ Nis Fac Elect Nish Serbia Telekom Srbija Belgrade Serbia

In this study a new algorithm is proposed for distributed blind sensor macro-calibration in networked control systems robust to noise. The proposed distributed algorithm for estimation of gain and offset correction parameters is of stochastic approximation type, with local non-linear transformations of residuals. Convergence of the algorithm in mean-square and with probability one to consensus is proved for a large class of non-linear transformations, network properties and communication and measurement noise characteristics. The choice of the introduced non-linear transformations in accordance with the theory of robust statistics leads to the proposal of new calibration algorithms robustified w.r.t. noise. It is demonstrated by Monte Carlo simulation that the proposed algorithms are very efficient in the presence of large outliers from the point of view of both achievement of high convergence rate and adequate values of convergence points, outperforming the existing linear algorithms.

关键词： calibration networked control systems robust control measurement errors Monte Carlo methods estimation theory stochastic processes distributed algorithms probability mean square error methods distributed control nonlinear control systems distributed nonlinear robust consensus-based sensor calibration networked control systems distributed blind sensor macro-calibration stochastic approximation type measurement noise characteristics robust statistics linear algorithms distributed algorithm local nonlinear transformations Monte Carlo simulation

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Recognizing generalized Petersen graphs in linear time

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DISCRETE APPLIED MATHEMATICS 2020年 283卷 756-761页

作者： Krnc, Matjaz Wilson, Robin J. Univ Salzburg Dept Comp Sci Salzburg Austria Univ Primorska FAMNIT Koper Slovenia Open Univ Milton Keynes Bucks England London Sch Econ London England

By identifying a local property which structurally classifies any edge, we show that the family of generalized Petersen graphs can be recognized in linear time. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Graph recognition Generalized Petersen graphs linear algorithms

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Combination of LEDs and cognitive modeling to quantify sheep cheese whey in watercourses

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TALANTA 2019年 203卷 290-296页

作者： Lastra-Mejias, Miguel Villa-Martinez, Alberto Izquierdo, Manuel Aroca-Santos, Regina Cancilla, John C. Torrecilla, Jose S. Univ Complutense Madrid Dept Ingn Quim & Mat E-28040 Madrid Spain Scintillon Inst San Diego CA USA

The concentration of sheep cheese whey (CW) in water obtained from two Spanish reservoirs, two Spanish rivers, and distilled water has been estimated by combining spectroscopic measurements, obtained with light-emitting diodes (LEDs), and linear or non-linear algorithms. The concentration range of CW that has been studied covers from 0 to 25% in weight. Every sample was measured by six different types of LEDs possessing different emission wavelengths (blue, orange, green, pink, white, and UV). 1,800 fluorescence measurements were carried out and used to design different types of models to estimate the concentration of CW in water. The fluorescence spectra provided by the pink LED originated the most accurate mathematical models, with mean square errors lower than 3.3% and 2.5% for the linear and non-linear approaches, respectively. The pink LED combined with the non-linear model, which was an artificial neural network, was further validated through a k-fold cross-validation and an internal validation. It should be noted that the sensor used here has been designed and produced by a 3D printer and has the potential of being implemented in situ for real-time and cost-effective analysis of natural watercourses.

关键词： Artificial neural network Fluorescence Sheep cheese whey linear algorithms Water quality

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Flexible image processing in Embedded Systems using Multi-agents Systems

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IFAC-PapersOnLine 2016年第25期49卷 164-169页

作者： Inguère, Tifaine Carlier, Florent Renault, Valérie CREN University of Maine Le Mans France STMicroelectronics Le Mans France

Efficient Image processing can lead to complex algorithms. In Embedded context resources are limited and the approach of linear algorithm does not allow to decrease complexity regarding the variations of these resources availability. Agents are autonomous entities brought together into systems. They interact between them and with their environment to perform tasks. Their interactions allow them to share knowledge and capacities in order to adapt themselves to a changing context. In this paper we propose to use Multi-agents systems algorithms to perform flexible Image processing in an Embedded context. We will introduce our hardware context and the architecture choices made to adapt Multi-agents systems to the Embedded field. We will then present an experiment focusing on pixel interpolation process to study the flexibility of our solution. © 2016

关键词： Embedded systems Autonomous agents Image processing Lead compounds Multi agent systems Resource allocation Autonomous entities Complex algorithms Decrease complexity Embedded fields linear algorithms Management systems Multi agents systems Share knowledge

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Performance Comparison of Cloudlet Scheduling Policies 1

Performance Comparison of Cloudlet Scheduling Policies

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1st International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS)

作者： Geetha, V. Devi, R. Aruna Ilavenil, T. Begum, S. Marjana Revathi, S. Pondicherry Engn Coll Dept Informat Technol Pondicherry India

ISBN: (纸本)9781467367257

Cloud computing is widely accepted as the best computing and storage model for low cost and high resource utilization. User requests from public can be run in data centers of large datacenters whey they are idle. This brings in high profit for cloud providers and low cost for cloud users. The profit and response time can be improved by an optimal scheduling policy. This paper does a survey on various classes of existing cloudlet scheduling algorithms. Researchers have proposed linear algorithms, genetic algorithms and swarm intelligence algorithms. The merits and demerits of these classes of algorithms are analyzed in this paper.

关键词： Cloud Virtual Machine Cloudlet cloudlet Scheduling policies Swarm intelligence algorithms linear algorithms Genetic algorithms

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