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1
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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2
EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization
Published 2019“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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3
Study Of EMG Feature Selection For Hand Motions Classification
Published 2019“…Thus, this paper employs two recent feature selection methods namely competitive binary gray wolf optimizer (CBGWO) and modified binary tree growth algorithm (MBTGA) to evaluate the most informative EMG feature subset for efficient classification. …”
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4
Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang
Published 2013“…Discrete Tchebichef moments are selected as the implementation platform of the proposed algorithms.To evaluate the performance of invariant algorithms, empirical studies have been carried out on large set of binary images which consist of numbers, English letters, symbols, Chinese characters and objects like animals, trees and company logos under noiseless and noisy conditions. …”
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5
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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6
Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
Published 2013“…The optimization of a computationally intensive algorithm such as this on a mobile platform is challenging due to the limited resources available. …”
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7
Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection
Published 2024“…Therefore, this binary tree cannot analyse complex features of mixed attributes and restricts the CART tree's deep-level feature recognition ability. …”
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8
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…Hence, the objective of this research is to propose suitable and optimize algorithm for ANPR system on Android mobile phone. …”
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9
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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10
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…These problems were extensively studied within the scope of classification (binary and multi-class) and regression (linear and survival). …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. …”
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13
Pixel-based feature for android malware family classification using machine learning algorithms
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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15
Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study
Published 2018“…Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. …”
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16
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM.…”
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17
Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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18
Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). The study compares the performance of WOA with various existing strategies, such as Greedy, Density, TVG, Union, ParaOrder, ReqOrder, ITTDG, AURA, Java Algorithm (CTJ), TTSGA, and AFA. …”
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A heuristics approach for classroom scheduling using genetic algorithm technique
Published 2017“…The proposed of heuristics approach will prompt a superior utilization of the accessible classroom space for a given time table of courses at the university. Genetic Algorithm through Java programming languages were used in this study and aims at reducing the conflicts and optimizes the fitness. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
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