Search Results - (( feature construction patterns algorithm ) OR ( java simulation optimization algorithm ))
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1
Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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2
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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3
Pattern generation through feature values modification and decision tree ensemble construction
Published 2013“…The method modifies feature values of some patterns with the values of other patterns to generate different patterns for different classifiers. …”
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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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5
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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6
Optimized feature construction methods for data summarizations of relational data
Published 2014“…The proposed framework involves the application of genetic algorithm which incorporates several feature scoring measures to optimize the process of feature construction. …”
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7
An extended ID3 decision tree algorithm for spatial data
Published 2011“…One of classification algorithms namely the ID3 algorithm which originally designed for a non-spatial dataset has been improved by other researchers in the previous work to construct a spatial decision tree from a spatial dataset containing polygon features only. …”
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8
Evolutionary-based feature construction with substitution for data summarization using DARA
Published 2012“…This approach allows initial features to be used more than once in constructing newly constructed features. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN
Published 2011“…The second contribution is the extraction pattern construction. Each named entity candidate will be assigned with an extraction pattern constructed from a set of word and syntactical feature. …”
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11
Evaluation of intonation features on emphasized Malay words / Syazwani Nasaruddin
Published 2017“…In this research, all 314 words from 2 different male speakers' speeches are clustered manually based on features of intensity and pitch pattern. The pattern of the features such as intensity and pitch are observed and clustered to find out how many patterns can be identified from all the words. …”
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12
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Initially, several useful features are extracted from the EMG signals to construct the feature set. …”
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13
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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14
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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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion 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 other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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17
Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…In this study, the Deep Belief Network algorithm was optimized and constructed to design an effective NIDS anomaly model. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
Published 2019“…First, the vibration signals of gear with different fault conditions were decomposed by a fourth-level discrete wavelet packet transform, and the statistical features at all constructed nodes were derived. Second, the MFO algorithm was utilised to select the optimal discriminative features. …”
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An improved multiple classifier combination scheme for pattern classification
Published 2015“…The ant system (AS) algorithm is used to partition feature set in developing feature subsets which represent the number of classifiers. …”
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