Search Results - (( model estimation means algorithm ) OR ( _ classification using algorithm ))
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1
Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population
Published 2023“…This research concludes that using Google Teachable Machine provide high accuracy and precision for sex estimation but not useful for age classification for sample below 20 years old.…”
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2
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…In conclusion, hybrid DNN with the K-Means Clustering Algorithm is proven to resolve parameter estimations of the chaotic system by developing an accurate prediction model.…”
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3
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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4
Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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5
Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…The Fuzzy c-means clustering improved the accuracy of classification task to 40.53%. …”
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6
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The reweighted fast, consistent and high breakdown (RFCH) estimator is a multivariate procedure used to estimate the robust location and scatter matrix. …”
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7
Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar
Published 2015“…The results of this work show that fault classification using SLFN trained by ELM has high accuracy on estimating fault in transmission line system.…”
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8
Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar
Published 2015“…The results of this work show that fault classification using SLFN trained by ELM has high accuracy on estimating fault in transmission line system.…”
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9
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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10
Assessment of predictive models for chlorophyll-a concentration of a tropical lake.
Published 2011“…Dissolved oxygen, selected through stepwise procedure, was used to develop the MLR model. HEA model used parameters selected using genetic algorithm (GA). …”
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11
Assessment of predictive models for chlorophyll-a concentration of a tropical lake.
Published 2011“…Dissolved oxygen, selected through stepwise procedure, was used to develop the MLR model. HEA model used parameters selected using genetic algorithm (GA). …”
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12
Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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13
Benthic habitat mapping and coral bleaching detection using quickbird imagery and Kd algorithm
Published 2013“…Final results of the applied methodology for depth estimation revealed correlation values equal to ~0.84 and ~0.83 between estimated and measured depth values, while their mean values were ~2.06±1.44 m and ~1.75±1.33 m for 2005 and 2008, respectively. …”
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14
Generating an adaptive and robust walking pattern for prosthetic ankle-foot utilizing a nonlinear autoregressive network with exogenous inputs / Hamza Al Kouzbary
Published 2021“…The trained NARX RNN estimated the foot orientation of all subjects at different walking speeds over a flat terrain with an average root mean square error of 2.1°±1.7°. …”
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15
All-in-1 adverse drug reaction reporting system / Long Chiau Ming … [et al.]
Published 2014“…Values obtained from this algorithm are used in peer reviews to verify the validity of reporter’s conclusion regarding ADRs. …”
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Book Section -
16
Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
Published 2023“…The proposed hybrid DTMF detector scheme is based on power spectrum analysis by means of the Discrete Fourier Transform (DFT). The Goertzel's Algorithm is used to estimate the seven fundamental DTMF carrier frequencies. …”
Conference paper -
17
Spectral features selection and classification of oil palm leaves infected by Basal stem rot (BSR) disease using dielectric spectroscopy
Published 2018“…The selection model comparative feature analysis demonstrated that the best statistical indicators with overall accuracy (88.64%), kappa (0.8480) and low mean absolute error (0.1652) were obtained using significant frequencies produced by SVM-FS model. …”
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Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli
Published 2022“…The Adaptive Moment Estimation (Adam) optimizer and Learning Rate on Plateau are employed to optimize the model's training regime. …”
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19
Model selection approaches of water quality index data
Published 2016“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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20
LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…Furthermore, our CGD algorithms are also capable of estimating the pure GARCH model, unlike any similar algorithm for the same model in the literature. …”
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