Search Results - (( java implementation mining algorithm ) OR ( using partial bees algorithm ))
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1
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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3
Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. …”
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4
Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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6
Application of Bee Colony Optimization (BCO) in NP-Hard Problems
Published 2011“…This report presents the first stage of an ongoing research which is the problem solving of highly complex tasks using Bee-Inspired algorithms. Bee-Inspired algorithms are partially referring to the nature of bee swarm behaviour. …”
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7
Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…This study explores the application of an artificial bee colony (ABC) to locate partial discharge (PD) in a test tank based on acoustic emission (AE) approach. …”
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8
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing
Published 2018“…Recently, the artificial bee colony (ABC) algorithm was used in the solution process where it was considered as a very useful, effective and well-known algorithm. …”
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10
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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11
Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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13
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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14
Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Published 2024“…Then, data from different analysis months were used as source and target datasets. Next, joint distri bution adaptation based partial least square (JDA-PLS) and transfer component analysis based PLS (TCA-PLS) were implemented to establish NIRS predictive models of moisture, hydroxymethylfurfural (HMF), and glucose quality. …”
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