Search Results - (( data replication server algorithm ) OR ( parameter classification using algorithm ))
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1
Managing Heterogeneous Database Replication Using Persistence Layer Synchronous Replication (PLSR)
Published 2013“…Proper mechanism is significantly required in order to manage the complex heterogeneous data replication. This paper presents a new algorithm namely the Persistence Layer Synchronous Replication (PLSR) in order to manage the agent handling the replication. …”
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2
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…All the replication servers established its connection through interfaces. …”
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3
Improving response time, availability and reliability through asynchronous replication technique in cluster architecture of web server cluster
Published 2010“…This paper proposes an algorithm of data replication scheme based on asynchronous replication in order to improve web server cluster system reliability. …”
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4
A technique of dispatching algorithms for web-server cluster
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5
Fault Tolerence on Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique
Published 2013“…It also increases the degrees of data availability. This is because the missing data from during the server failure has been reconciled and replicated after that server recovered.…”
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6
Fault Tolerance On Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique
Published 2013“…It also increases the degrees of data availability. This is be cause the missing data from during the server failure has been reconciled and replicated after that server recovered.…”
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7
Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication
Published 2015“…Data replication is one of the mechanisms to manage data since it improves data accessibility and reliability. …”
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Binary vote assignment on grid quorum replication technique with association rule
Published 2018“…However, these techniques have its weaknesses in terms of communication costs that is the total replication servers needed to replicate the data. Furthermore, these techniques also do not consider the correlation between data during the fragmentation process. …”
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9
Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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10
Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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13
Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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14
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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Undergraduates Project Papers -
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…IPJAYA in this study was used to update the C and gamma parameters of the support vector machine (SVM). …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Undergraduate Final Project Report -
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
Published 2018“…This paper presents the gait pattern classification between 3 groups which are control, stroke only and stroke with Peripheral Neuropathy (SPN) using k-Nearest Neighbors (kNN) algorithm. …”
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