Search Results - (( model mitigation means algorithm ) OR ( style classification based algorithm ))
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Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda
Published 2006“…Based on UPSR Essay Assessment Schema, there are three main assessment components consists of language, discourse element and style. …”
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2
Hybrid genetic random forest algorithm for the identification of ISI-indexed articles / Mohammadreza Moohebat
Published 2017“…After ensuring that the classification technique was able to accomplish this work, Hybrid Genetic Random Forests (HGRF) was introduced as a new ensemble classifier based on a Random Forest algorithm, but altered slightly with some innovations. …”
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3
Converged Classification Network For Matching Cost Computation
Published 2020“…Overall quantitative results for the proposed work performed competitively compared to other established stereo matching algorithm based on the Middlebury standard benchmark online system.…”
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GEOSPATIAL TEMPORAL FRAMEWORK ON LANDSLIDES MITIGATION STRATEGIES FOR PIPELINES
Published 2023“…AUC values of 0.879 were obtained for the susceptibility models developed from the SVM algorithms, indicating outstanding predictive performance.…”
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Discovering student learning styles in engineering mathematic at Politeknik Merlimau using neural network techniques
Published 2015“…If questionnaires are too long, students tend to choose both answers arbitrarily instead of thinking about the result of the student’s learning style observed through analysis. This research identified the classification of students learning styles based on the Felder Silverman Learning dimension. …”
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7
Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity
Published 2016“…The dominant saturation nonlinearity is in the transducers, which can be represented by a Wiener model. An effective solution to mitigate such nonlinear distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. …”
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Semantic shot classification in soccer videos via playfield ratio and object size considerations.
Published 2013“…This paper presents a semantic shot classification algorithm for soccer videos. Generally, each shot within a match video is assigned either a far or close up-view class label. …”
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Feature recognition and classification of shanxi cave dwellings based on deep learning
Published 2023“…Through detailed investigation and research on specific examples in Shanxi, the results are as follows: (1) We identify and classify the architectural features of Shanxi cave dwellings based on deep learning algorithm so that we can better understand and explore Shanxi cave dwellings. (2) By analyzing the present situation of examples, it is concluded that most villagers affirm the living comfort and regional adaptability of cave buildings, and the identification and classification of cave building features in Shanxi based on deep learning can provide effective reference, in order to better complete the renovation and development of cave buildings in Shanxi.…”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. …”
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Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…The dominant saturation nonlinearity in the transducers is the loudspeaker which can be represented by a Wiener model. An effective solution to mitigate such nonlinearly distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. …”
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12
A stylometry approach for blind linguistic steganalysis model against translation-based steganography
Published 2023“…The proposed stylometry-based blind steganalysis model consists of two stages, which are stylometric feature selection and classification. …”
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13
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…The objective of this study is to identify groups of drivers based on their driving styles using the collected OBD-II data. …”
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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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16
Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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Classification of SNPs for obesity analysis using FARNeM modelling
Published 2013“…However, the overall analysis showed that, it is encouraging to include feature selection process before the learning algorithms.…”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Mean Squared Error (MSE) shows that the Random Forest model makes more accurate predictions than the others. …”
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Simulation on Emotion Recognition for Autism Therapy
Published 2017“…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. …”
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Final Year Project -
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Modelling of river flow using particle swarm optimized cascade-forward neural networks: A case study of kelantan river in malaysia
Published 2023“…Additionally, the developed nonlinear multivariable regression model using CFNNPSO produced acceptable prediction accuracy during model testing with the regression coefficient (R2), root mean square error (RMSE), and mean of percentage error (MPE) of 0.88, 191.1 cms and 0.09%, respectively. …”
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