Search Results - (( _ generation mining algorithm ) OR ( java simulation optimization algorithm ))
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1
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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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
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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4
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 -
5
Direct approach for mining association rules from structured XML data
Published 2012“…The focus of this study is to propose an enhancement on memory consumption by reducing the number of candidates generated for the existing FLEX algorithm which will reduce the amount of memory needed to execute the algorithm. …”
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6
A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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7
A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…It then divides the compressed database into a set of conditional databases (a special kind of projected database), each associated with one frequent item or pattern fragment, and mines each such database separately.For a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution.In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well.Our algorithm works based on prime factorization, and is called Frequent Pattern- Prime Factorization (FPPF).…”
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8
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The mined frequent patterns are then used in generating association rules. …”
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9
Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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10
A numerical method for frequent pattern mining
Published 2009“…Frequent pattern mining is one of the active research themes in data mining. …”
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11
Evaluation of data mining models for predicting concrete strength
Published 2024“…The Particle Swarm Optimization algorithm is able to generate optimal values for the concrete features that maximizes the strength of concrete. …”
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Final Year Project / Dissertation / Thesis -
12
HYBRID: an efficient unifying process to mine frequent itemsets
Published 2018“…Algorithms to mine frequent itemsets effectively help in finding association rules and also help in many other data mining tasks. …”
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Proceeding Paper -
13
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. …”
Review -
14
Comparative study of apriori-variant algorithms
Published 2016“…One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. …”
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15
A semi-apriori algorithm for discovering the frequent itemsets
Published 2014“…Frequent itemsets generation produce extremely large numbers of generated itemsets that make the algorithms inefficient. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
17
Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…The multiple variants in the R-Eclat algorithm generate varied performances in infrequent mining patterns. …”
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18
RARE: mining colossal closed itemset in high dimensional data
Published 2018“…The task of mining association rules highly relies on the efficiency of the algorithms to extract all frequent itemsets that exist in the database. …”
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19
Propositional satisfiability algorithm to find minimal reducts for data mining
Published 2002“…The experimental result shows that the proposed algorithm has significantly reduced the number of rules generated from the obtained reducts with high percentage of classification accuracy. © 2002 Taylor and Francis Ltd.…”
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20
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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Thesis
