Search Results - (( java implementation mining algorithm ) OR ( quality solution machine algorithm ))

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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    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. 2
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    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. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    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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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    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. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources

    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

    Published 2023
    “…However, the number of resources available is limited, and this makes the problem difficult to solve for a good quality solution. Genetic algorithm shows promising results in solving UPMR. …”
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  7. 7
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  8. 8
    A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time

    A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time by Nazif, Habibeh, Lee, Lai Soon

    Published 2009
    “…The computational results indicate the effectiveness of the proposed algorithm in generating better quality solutions compared to other algorithms. …”
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  9. 9
    Solving single machine scheduling problem with maximum lateness using a genetic algorithm

    Solving single machine scheduling problem with maximum lateness using a genetic algorithm by Nazif, Habibeh, Lee, Lai Soon

    Published 2010
    “…The results showed that the proposed algorithm is generating better quality solutions compared to other variants of genetic algorithms…”
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  10. 10
    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem

    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

    Published 2009
    “…While these assumptions simplify the problem, they adversely affect the solution quality for many applications which require explicit treatment of setup. …”
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  11. 11
    Damping power system oscillation using elitist differential search algorithm in multi machine power system

    Damping power system oscillation using elitist differential search algorithm in multi machine power system by Niamul Islam N., Hannan M.A., Mohamed A., Hussain S.

    Published 2023
    “…The findings show the presented Elitist-DSA technique is far superior as compared to BFOA and PSO in terms of quality solution of multi-machine PSSs optimization. …”
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  12. 12
    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network

    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
    “…Machine Learning (ML) is seen as a promising application that offers autonomous learning and provides optimized solutions to complex problems. …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    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. 14
    Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems

    Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems by Ariafar, Shahram

    Published 2012
    “…Comparison of the results with an adapted algorithm from the literature, in terms of the quality of solutions (material handling cost) shows that the proposed algorithm produces better solutions with a maximum of 0.08% error compared to 0.12% error in the benchmarked algorithm. …”
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  15. 15
    Genetic algorithms for single machine family scheduling problems with maximum lateness and completion time

    Genetic algorithms for single machine family scheduling problems with maximum lateness and completion time by Lee, Lai Soon, Habibeh, Nazif

    Published 2010
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  16. 16
    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals

    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

    Published 2015
    “…The proposed approach provides high quality solution with respect to efficiency as well as shop floor stability. …”
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  17. 17
    Estimation of optimal machining control parameters using artificial bee colony

    Estimation of optimal machining control parameters using artificial bee colony by Norfadzlan, Yusup, Arezoo, Sarkheyli, Azlan, Mohd Zain, Siti Zaiton, Mohd Hashim, Norafida, Ithnin

    Published 2013
    “…Optimizing the machining control parameters are essential in order to provide a better quality and economics machining. …”
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  18. 18
    Fuzzy expert system modeling of laser processing

    Fuzzy expert system modeling of laser processing by Subramonian, Sivarao, Ahmad, Kamely, Md Palil, Md Dan

    Published 2009
    “…Hence, this micro quality starts from the control of many parameters on the machine itself. …”
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  19. 19
    Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications

    Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

    Published 2025
    “…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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  20. 20
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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