Search Results - (( variable optimization svm algorithm ) OR ( using optimization path algorithm ))
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…The first two algorithms, ACOR-SVM and IACOR-SVM, tune the SVM parameters while the second two algorithms, ACOMV-R-SVM and IACOMV-R-SVM, tune the SVM parameters and select the feature subset simultaneously. …”
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Thesis -
2
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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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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Mixed variable ant colony optimization technique for feature subset selection and model selection
Published 2013“…This paper presents the integration of Mixed Variable Ant Colony Optimization and Support Vector Machine (SVM) to enhance the performance of SVM through simultaneously tuning its parameters and selecting a small number of features.The process of selecting a suitable feature subset and optimizing SVM parameters must occur simultaneously,because these processes affect each ot her which in turn will affect the SVM performance.Thus producing unacceptable classification accuracy.Five datasets from UCI were used to evaluate the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with the small size of features subset.…”
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Conference or Workshop Item -
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Solving SVM model selection problem using ACOR and IACOR
Published 2013“…In applying ACO for optimizing SVM parameters which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretize process would result in loss of some information and hence affect the classification accuracy.In order to enhance SVM performance and solving the discretization problem, this study proposes two algorithms to optimize SVM parameters using Continuous ACO (ACOR) and Incremental Continuous Ant Colony Optimization (IACOR) without the need to discretize continuous value for SVM parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed integrated 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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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Integrated ACOR/IACOMV-R-SVM Algorithm
Published 2017“…The first algorithm, ACOR-SVM, will tune SVM parameters, while the second IACOMV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. …”
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Optimization of multi-holes drilling path using particle swarm optimization
Published 2018“…PSO is also compared with another algorithm like Whale Optimization Algorithm, Ant Lion Optimizer, Dragonfly Algorithm, Grasshopper Optimization Algorithm, Moth-flame Optimization and Sine Cosine Algorithm. …”
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Book Chapter -
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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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Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system
Published 2021“…This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. …”
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Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization
Published 2018“…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
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Research Report -
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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Thesis -
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MULTIPLE DRONES PATH OPTIMIZATION ALGORITHM FOR 3D SPACE PERFORMANCE USING CENTRALIZED VISUALIZATION PLATFORM
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Final Year Project Report / IMRAD -
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Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…Each algorithm was tested to compute the shortest path, with results indicating that while all algorithms arrive at the same optimal route, their efficiency differs. …”
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Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…The euler's path it using pseudo input and Heuristic algorithm to find the minimum interlace. …”
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Thesis -
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Optimizing optimal path trace back for Smith-Waterman algorithm using structural modelling technique
Published 2012“…The optimizing of optimal path trace back system for Smith-Waterman algorithm using structural modelling techniques are presented in this paper. …”
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Student Project -
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Optimization of drilling path using the bees algorithm
Published 2021“…This study uses the Bees Algorithm to find the best sequence of drilling holes (minimum total path length) and the results found are compared with the result of other algorithms. …”
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New algorithm for autonomous dynamic path planning in real-time intelligent robot car
Published 2017“…Different algorithms have been used to address this problem by considering the optimal path with minimum cost; however, these algorithms did not consider the execution time to find such path. …”
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