Search Results - (( programming testing selection algorithm ) OR ( java application mining 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
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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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
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  7. 7
    Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity

    Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2015
    “…This paper propose an optimized regression test case selection and prioritization for object-oriented software based on dependence graph model analysis of the source code and optimized the selected test case using Genetic Algorithm. …”
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  8. 8
    Automated path testing using the negative selection algorithm

    Automated path testing using the negative selection algorithm by Shayma Mustafa Mohi-Aldeen, Radziah Mohamad, Safaai Deris

    Published 2017
    “…Negative selection algorithm (NSA) has been used in this paper to generate test data for path testing automatically. …”
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  9. 9
    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm

    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…The effective and efficient test case selection from the existing test suite becomes very critical issue in regression testing. …”
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  10. 10
    The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases

    The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2015
    “…This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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  11. 11
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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  12. 12
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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  13. 13
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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  14. 14
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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  15. 15
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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  16. 16
    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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  17. 17
    Regression test case selection & prioritization using dependence graph and genetic algorithm

    Regression test case selection & prioritization using dependence graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. …”
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  18. 18
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  19. 19
    Optimizing Ram Testing Method For Test Time Saving Using Automatic Test Equipment

    Optimizing Ram Testing Method For Test Time Saving Using Automatic Test Equipment by Kesavan Prabagaran, Premkumar

    Published 2017
    “…A memory Build-in Self-test (BIST) design with capability of algorithm failing sequence capture have been developed to implement in the Automate Test Equipment (ATE) flow for production screen. 3 selected algorithm have been tested on the 8 detect units in ATE flow to prove the concept of this method. …”
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  20. 20
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…Whereas the results obtained from both selection methods are similar to each other. Tests results show that Genetic Algorithm is a suitable algorithm as it is an optimization technique with, high accuracy, and it avoids local minimum by searching in several regions to arrive to the global optimum solution. …”
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