Search Results - (( set selection search algorithm ) OR ( java simulation optimization algorithm ))
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Optimization of attribute selection model using bio-inspired algorithms
Published 2019“…This is achieved in two stages; 1) create attribute selection models by combining search method and feature selection algorithms, and 2) determine an optimized attribute set by employing bio-inspired algorithms.Classification performance of the produced attribute set is analyzed based on accuracy and number of selected attributes. …”
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Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm
Published 2017“…The purpose of this study is to assist potential developers in selecting the most suitable cuckoo search variant, provide proper guidance in future modifications and ease the selection of the optimal cuckoo search parameters. …”
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Enhanced feature selections of Adaboost training for face detection using genetic algorithm (GABoost)
Published 2007“…The GA carries out an evolutionary search over possible features search space which results in a higher number of feature types and sets selected in lesser time. …”
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Enhanced feature selections of Adaboost training for face detection using genetic algorithm
Published 2007“…The GA carries out an evolutionary search to select features which results in a higher number of feature types and sets selected in less time. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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A hybrid local search algorithm for minimum dominating set problems
Published 2022“…To solve these problems, we propose a two-stage hybrid local search algorithm. In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. …”
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A hybrid local search algorithm for minimum dominating set problems
Published 2022“…To solve these problems, we propose a two-stage hybrid local search algorithm. In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
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Book Section -
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Thesis -
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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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Monograph -
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A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem
Published 2016“…The AVNS consists of two stages: a learning phase and a multi-level VNS with guided local search. The adaptive aspect is integrated in the local search where a set of highly successful local searches is selected based on the intelligent selection mechanism. …”
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A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem
Published 2020“…As such, the adoption of parameter free meta-heuristic algorithms is often straightforward. On the negative note, exploration (i.e. roaming the search space thoroughly) and exploitation (i.e. manipulating the current known best neighbor) are pre-set. …”
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Conference or Workshop Item -
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A new ant based rule extraction algorithm for web classification
Published 2011“…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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Monograph -
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…In this research, the empirical experiments have been conducted for the five selected algorithms in the engineering optimization discipline, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS). …”
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A New And Fast Rival Genetic Algorithm For Feature Selection
Published 2021“…Presently, many metaheuristic optimization algorithms were successfully applied for feature selection. …”
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Genetic Algorithm for Web Data Mining
Published 2001“…This study used a prototype program based on genetic algorithm to manipulate the initial set of data. Three sets of inputs were used to generate new populations based on the individual fitness. …”
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Project Paper Report -
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Experimental study of variation local search mechanism for bee algorithm feature selection
Published 2017“…This situation creates unwanted suboptimum solution(s) leading to the lack of accuracy and longer processing time. A set of different local neighborhood search extension and their combination approaches have been proposed, including Simple-swap, 2-Opt, 3-Opt, and 4-Opt. …”
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