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modeling algorithm » scheduling algorithm (Expand Search)
case modeling » based modeling (Expand Search)
element » elements (Expand Search)
update » updated (Expand Search)
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101
Loss Model Control for Efficiency Optimization and Advanced Sliding Mode Controllers with Chattering Attenuation for Five-Phase Induction Motor Drive
Published 2024“…<p dir="ltr">This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). …”
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102
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103
Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”
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104
Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers
Published 2024“…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …”
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105
Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”
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106
Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids
Published 2021“…The algorithm has been tested through a case study to demonstrate its performance and effectiveness.…”
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107
Microwave brain imaging system to detect brain tumor using metamaterial loaded stacked antenna array
Published 2022“…The MTM array elements in layers are utilized to enhance the performance concerning antenna’s efficiency, bandwidth, realized gain, radiation directionality in free space and near the head model. …”
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108
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…In addition to the deployment without requiring an explicit model of the plant, the simulation results demonstrate that the proposed solution modifies vehicle dynamics and maneuverability in most cases compared to the model-based conventional controller. …”
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109
Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…Generally, RKPCA reduces the number of samples in the training data set and then builds the KPCA model based on this data set. In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”
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110
An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…The decision tree model provided more accurate results than the other models. …”
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111
A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem
Published 2008“…The use of the finite element method allows the use of variable unstructured meshing and different types of elements within the same model which leads to a reduced size of the problem. …”
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112
Assessment of static pile design methods and non-linear analysis of pile driving
Published 2006“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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113
Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates
Published 2022“…The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. …”
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114
Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements
Published 2020“…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. …”
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115
Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks
Published 2023“…The proposed ANN based algorithm has been used for unswerving petite term forecasting. …”
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116
Corona power loss computation in bundled bipolar conductors
Published 2000“…In this paper, a finite element (FE) based algorithm devoted for the computation of the corona current and hence the corona power loss associated with bundled bipolar high voltage direct current (HVDC) conductors is presented. …”
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117
Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem
Published 2016“…Finally, the research note demonstrates how REBUS detects classes in models with higher order (multidimensional) constructs, which are often the case in tourism research.…”
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118
A feature‐based approach for guiding the selection of Internet of Things cybersecurity standards using text mining
Published 2021“…Third, a text mining algorithm has been implemented. Fourth, the systematic approach has been modeled using business process modeling notation. …”
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119
Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants
Published 2006“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. …”
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120
An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
Published 2019“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. Experiment is performed using Azure Machine Learning (ML) platform to test and assess the most efficient model that would predict the failure of system elements and predict the abnormality of the operation. …”
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