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The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers
Published 2024“…Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Due to the inherent and uncertain variability of the Harumanis features, fuzzy learning algorithm has been designed to classify these fruits similar to the ability of human experts. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…If the feature extraction process fails to capture the correct information, the performance or accuracy of the classification algorithm will be negatively impacted. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…However, existing RUL prediction approaches have difficulties with variability and nonlinearity that occur during battery degradation, data extraction, feature extraction, hyperparameters optimization, and prediction model uncertainty. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
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Classification of Students' Performance in Computer Programming Course According to Learning Style
Published 2024“…The critical point of this study is the use of classification algorithm to extract patterns which are examined from the cognitive factor specific learning style. …”
Proceedings Paper -
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
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Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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Proceeding Paper -
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Syncope also known as transient loss of consciousness which caused problem to human daily life. Since machine learning is much more advanced, classification of syncope can be done with machine learning. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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ECG-based driving fatigue detection using heart rate variability analysis with mutual information
Published 2023“…For feature extraction, we employ heart rate fragmentation to extract non-linear features to analyze the driver’s cognitive status. …”
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Super resolution imaging using modified lanr based on separable filtering
Published 2019“…The underlying idea is to process and reconstruct information in low and high frequency sub-bands based on separable property of neighbourhood filtering to achieve fast parallel and vectorized operation, while enhancing algorithmic performance by reducing computational burden resulting from computing the weighted function of every pixel for each pixel in an image. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…While machine learning eliminates the requirement for manual feature selection when extracting significant information from predictor fields, considering multiple pivotal factors is essential. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model
Published 2024“…System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. …”
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