Search Results - (( parameter extraction method algorithm ) OR ( time estimation learning algorithm ))*
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1
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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2
Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems
Published 2025“…The key attributes that establish the classification learning sessions are the channel parameters extracted from the ray tracing generated multipath signals. …”
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3
Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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4
A comparative study of supervised machine learning approaches for slope failure production
Published 2023“…Generally, slope failure can be estimated based on traditional methods such as limit equilibrium method (LEM) or finite equilibrium method (FEM). …”
Conference Paper -
5
Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
Conference Paper -
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Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home
Published 2024Subjects:Conference Paper -
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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8
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
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10
Hybrid FFT-ADALINE algorithm with fast estimation of harmonics in power system
Published 2016“…In the proposed method, both of the aforementioned algorithms are combined for harmonic estimation where it is able to respond immediately to any change of the measured harmonics and the settling time is reduced to half cycle of the measurement signal. …”
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11
Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…RFR is suitable for real-time SOC estimation due to its robustness to noise, overfitting issues and capacity to work with huge datasets. …”
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Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt-Hall-Hall-Hausman
Published 2022“…Experimental data-oriented parameter extraction helps in giving an accurate assessment to forecast the output current of the photovoltaic cells. …”
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13
Software project estimation with machine learning
Published 2021“…This project involves research about software effort estimation using machine learning algorithms. Software cost and effort estimation are crucial parts of software project development. …”
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14
Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…However, current learning-based methods are computationally expensive and require a significant amount of time to estimate the pose from a video sequence. …”
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15
Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…However, current learning-based methods are computationally expensive and require a significant amount of time to estimate the pose from a video sequence. …”
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16
Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment
Published 2021“…Finally, morphological parameters of the canopy, such as crown height, crown diameter, and crown volume, are extracted using statistical and voxel methods. …”
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A novel theoretical and practical methodology for extracting the parameters of the single and double diode Photovoltaic models
Published 2022“…However, there is no method to date that can guarantee the extracted parameter of the PV model is the most accurate one. …”
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Real time long range (LoRa) based indoor positioning system using Deep Gaussian Process (DGP) algorithm / Ng Tarng Jian
Published 2025“…The study addresses challenges posed by signal fluctuations, non-line-of-sight propagation, and the need for continuous positioning estimation in dynamic environments. Through experimental evaluation and comparison of various machine learning algorithms, including Deep Gaussian Process (DGP) regression, the research demonstrates the effectiveness of DGPs in achieving precise single-point estimation, by keeping the mean absolute error to below 5 meters. …”
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20
Software effort estimation using machine learning technique
Published 2023“…In order to better effectively evaluate predictions, this study recommends various machine learning algorithms for estimating, including k-nearest neighbor regression, support vector regression, and decision trees. …”
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