Search Results - (( simulation optimization window algorithm ) OR ( binary classification tree algorithm ))

Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…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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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…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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Study Of EMG Feature Selection For Hand Motions Classification by Abdullah, Abdul Rahim, Mohd Saad, Norhashimah, Too, Jing Wei

“…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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Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang by Pee, Chih Yang

“…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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An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks by Al-Kharasani, Ameen Mohammed Abdulkarem, Othman, Mohamed, Abdullah, Azizol, Kweh, Yeah Lun

“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator by Mahmed, Ali Nader, Mohd Nizam, Mohmad Kahar

“…Taking both aspects, optimization and dynamic utilization, we propose a simulation for dynamic patient scheduling based on multi-objective optimization, window, and coordinator. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…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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Simulation and Visualization of TSP Using Ant Colony Optimization by Tri Basuki, Kurniawan, Misinem, ., Astried, ., Joan Angelina, Widians

“…The Travelling Salesman Problem (TSP) is a well-known algorithmic problem its main objective is optimization. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems: article / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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Simulation of identifying shortest path walkway in library by using ant colony optimization by Chui Teng, Chan

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Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection by Jia, Liu

“…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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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

“…These problems were extensively studied within the scope of classification (binary and multi-class) and regression (linear and survival). …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers by Ahmed I.T., Hammad B.T., Jamil N.

An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Hui, Bian, Chiew, Kang Leng

“…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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Pixel-based feature for android malware family classification using machine learning algorithms by Mohd Zamri, Osman, Rahiwan Nazar, Romli, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan

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QTCP: an optimized and improved congestion control algorithm of high-speed TCP networks by Qureshi, Barkatullah, Othman, Mohamed, K. Subramaniam, Shamala, Abdul Hamid, Nor Asilah Wati

“…To overcome these problems Quick Transport Control Protocol (QTCP) algorithm based on optimizations of HS-TCP slow start algorithm and Additive Increase and Multiplicative Decrease (AIMD) algorithm have been proposed. …”
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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study by Mujtaba, Ghulam, Shuib, Liyana, Raj, Ram Gopal, Rajandram, Retnagowri, Shaikh, Khairunisa

“…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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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…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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