Search Results - adoption using different ((extraction algorithm) OR (selection algorithm))*
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Proceeding Paper -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Thesis -
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. …”
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Article -
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…To extract the maximum power from the PV system, the proposed BCM algorithm selects a suitable set of battery cells to charge for a particular time by referring to the forecasted PV output power. …”
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Thesis -
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images
Published 2015“…Those features that are kept in all three truncated feature sets are chosen as final selected features which are 10 features. Chernoff bound decreases again from 50.2 to 46.3 by using the rank based feature selection algorithm. …”
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A Bayesian probability model for Android malware detection
Published 2021“…The experiment was then conducted using two algorithms for feature selection: information gain and chi-square. …”
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Article -
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Development of deep learning based user-friendly interface for fruit quality detection
Published 2024“…These image datasets encompass diverse information which requires extensive data extraction. To overcome this issue, a deep learning approach using convolutional neural network was used to evaluate the fruit quality. …”
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A New Bit-Plane Extraction Approach for Fingerprint Recognition Using Phase-Only Correlation Function
Published 2016“…POC based recognition method is adopted because of its simplicity and ability to achieve high accuracy compared to other recognition algorithms, especially for low quality fingerprint image. …”
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A Bayesian probability model for Android malware detection
Published 2022“…The experiment was then conducted using two algorithms for feature selection: information gain and chi-square. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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Thesis -
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…When the Gaussian mixture distribution algorithm is adopted, none of the criteria can consistently select features with the least number. …”
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Book Chapter -
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Monitoring and assessment of weld penetration condition during pulse mode laser welding using air-borne acoustic signal
Published 2021“…Signal features, such as mean absolute deviation (MAD), standard deviation (SD), kurtosis (K), L-scale (LS), L-kurtosis (LK), bandpower (BP), and sum of synchrosqueezed wavelet coefficient (CSqWCsum) were extracted from the acquired sound. To develop the signal processing algorithm, multi-lag phase space (MLPS) method was adopted in which some modifications on its original algorithm were made by introducing the localized crest factor (CF) thresholding method to reduce the influence of noise. …”
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Thesis -
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Feature extraction from natural language to aid requirements reuse in software product lines engineering / Noor Hasrina Bakar
Published 2016“…Then, linguistic tagging is applied to extract software features followed by applying simple clustering algorithms to form groups of common features. …”
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Thesis -
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Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-way Testing
Published 2022“…However, not all metaheuristics are effectively adopted in combinatorial t-way testing, some proved to be effective and thus have been popular tools selected for optimization whilst others are not adopted. …”
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Article -
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Zebra optimization algorithm for feature selection
Published 2026“…In this paper, we proposed the use of Zebra Optimization Algorithm (ZOA) for handling task regarding feature selection. …”
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Conference or Workshop Item -
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