Search Results - (( using selection problem algorithm ) OR ( basic optimization means algorithm ))
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1
Basic firefly algorithm for document clustering
Published 2015“…Results demonstrate that the Basic FA generates a more robust and compact clusters than the ones produced by K-means and Particle Swarm Optimization (PSO).…”
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2
Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim
Published 2007“…It makes use of three basic operations in order to optimize this problem. …”
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3
Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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Cycle time minimization in production line using robust hybrid optimization algorithm
Published 2021“…As example, memetic algorithm, EGSJAABC3 is applied for economic environmental dispatch (EED) optimization, Hybrid Pareto Grey Wolf Optimization to minimize emission of noise and carbon in U-shaped robotic assembly line and Polar Bear Optimization to optimize heat production. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…The proposed algorithm has been better than basic ABC in all tested problems with average of 0.570%.…”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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System identification using Extended Kalman Filter
Published 2017“…The EKF algorithm performance was compared with Recursive Least Square (RLS) estimation algorithm as a comparison algorithm performance. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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Fuzzy C means imputation of missing values with ant colony optimization
Published 2020“…This paper proposes a improved method of imputation by employing a new version of Fuzzy c Means (FCM) which hybridized with Evolutionary Algorithm to handle missing values problem. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…Some popular intelligent techniques like Genetic Algorithm, Fuzzy Logic and Artificial Neural Network are often used by reasearcher to perform classifcation problems. …”
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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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Earth observation micro-satellite design optimization using satellite simulator / Robertus Heru Triharjanto … [et al.]
Published 2016“…Therefore, the objective of the research is to develop method for optimizing satellite design. The satellite design phase concerned in the research is in detail design, which mean that the choices for basic configurations of the satellite has been determined. …”
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A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization
Published 2018“…Numerous studies in optimization problems often lead to tailoring a specific algorithm to adapt to the problem instances, especially in expensive optimization problems. …”
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Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri
Published 2017“…This study aims to implement the classification algorithm using the Improved Clonal Selection Algorithm (ICLONALG) to classify the eyesight’s problems. …”
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16
Static and self-scalable filter range selection algorithms for peer-to-peer networks
Published 2011“…The research works were implemented by simulation in which it was used to identify the selection problem, implementation of the proposed algorithms and the measurement of the results. …”
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17
Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…In this research, we showed how evolutionary multi-objective algorithms can be used to solve the view selection problem and its advantage over classical optimization problems were described. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…The proposed algorithm has been evaluated using 24 benchmark functions. …”
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Metaheuristic algorithms for feature selection (2014–2024)
Published 2025“…Metaheuristic algorithms are suited to provide solutions to feature selection problems because these problems are combinatorial and require an effective and efficient search through large solution spaces. …”
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