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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The proposed system utilizes Biased ARTMAP for pattern learning and classification. …”
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Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems
Published 2012“…The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. …”
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Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions
Published 2013“…The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. …”
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A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega)
Published 2009“…However, it is impractical to solve MOOP by using classical methods due to its complexity. Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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Final Year Project Report / IMRAD -
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A Test Vector Minimization Algorithm Based On Delta Debugging For Post-Silicon Validation Of Pcie Rootport
Published 2017“…To solve the problem, a test vector minimizer algorithm is proposed to eliminate redundant test vectors that do not contribute to reproduction of a test failure, hence, improving the debug throughput. …”
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Analysis on target detection and classification in LTE based passive forward scattering radar
Published 2016“…The experimental results confirm the passive FSR system’s capability for ground target detection and classification. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Improving performance of mobile ad hoc networks using efficient Tactical On Demand Distance Vector (TAODV) routing algorithm
Published 2012“…The proposed TAODV algorithm performs better for solving routing problems in Mobile Ad Hoc networks. …”
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Convergence and Diversity Evaluation for Vector Evaluated Particle Swarm Optimization
Published 2013“…An extended PSO algorithm called Vector Evaluated Particle Swarm Optimization (VEPSO) has been introduced to solve multi-objective optimization problems. …”
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Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization
Published 2013“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation
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Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain
Published 2020“…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
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An Improved VEPSO Algorithm for Multi-objective Optimisation Problems
Published 2015“…The vector evaluated particle swarm optimisation algorithm is widely used for such purpose, where this algorithm optimised one objective using one swarm of particles by the guidance from the best solution found by another swarm. …”
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