Search Results - (( java application mining algorithm ) OR ( problem implication based 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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    Citation Index Journal
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  7. 7
    Implication of image processing algorithm in remote sensing and GIS applications

    Implication of image processing algorithm in remote sensing and GIS applications by Pathan, Mubeena, Jusoff, Kamaruzaman, Mohd Sood, Alias, Razali, Yaakob, Qureshi, Barkatullah

    Published 2011
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  8. 8
    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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  9. 9
    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud

    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

    Published 2023
    “…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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    Book Section
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  10. 10
    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)

    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE) by Tijani, Ismaila Bayo, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2015
    “…Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. …”
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  11. 11
    Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods

    Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods by Salih, Rawia Tahrir

    Published 2021
    “…Thus, this research aims to standardize and weigh the evaluation criteria of MaOO competitive algorithms base on fuzzy Delphi and new fuzzy-weighted zero-inconsistency (FWZIC) methods. …”
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  12. 12
    Computing the maximum violation of a Bell inequality is an NP-problem

    Computing the maximum violation of a Bell inequality is an NP-problem by Batle, J., Raymond Ooi, C.H., Abdalla, S., Bagdasaryan, A.

    Published 2016
    “…The proof that the optimization of such correlation measure is an NP-problem based on an operational perspective involving a Turing machine, which follows a general algorithm. …”
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  13. 13
    Virtual reality in algorithm programming course: practicality and implications for college students

    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
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  14. 14
    A Method for Mapping XML DTD to Relational Schemas In The Presence Of Functional Dependencies

    A Method for Mapping XML DTD to Relational Schemas In The Presence Of Functional Dependencies by Ahmad, Kamsuriah

    Published 2008
    “…To approach the mapping problem, three different components are explored: the mapping algorithm, functional dependency for XML, and implication process. …”
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  15. 15
    The effectiveness of problem-based serious games on learning and learning motivation in the context of 3D computer graphics / Meisam Moradi

    The effectiveness of problem-based serious games on learning and learning motivation in the context of 3D computer graphics / Meisam Moradi by Meisam , Moradi

    Published 2022
    “…This study and the game design in this study can have pedagogical and practical implications for 3D computer graphics lecturers and those who are interested in designing effective problem-based SGs. …”
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  16. 16
    A fuzzy approach for early human action detection / Ekta Vats

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…Therefore, a new space-time fuzzy implication operator is introduced, by modifying the existing implication operators to accommodate time as an added dimension. …”
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  17. 17
    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines

    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines by Ismail, Napsiah, Musharavati, Farayi, Hamouda, Abdel Magid Salem, Ramli, Abdul Rahman

    Published 2008
    “…Design/methodology/approach: The genetic algorithm methodology implements a genetic algorithm that is augmented by application specific heuristics in order to guide the search for an optimal solution. …”
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  18. 18
    A hybrid deep learning-based unsupervised anomaly detection in high dimensional data

    A hybrid deep learning-based unsupervised anomaly detection in high dimensional data by Muneer, A., Taib, S.M., Fati, S.M., Balogun, A.O., Aziz, I.A.

    Published 2022
    “…Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. Many issues in this field still unsolved, so several modern anomaly detection methods struggle to maintain adequate accuracy due to the highly descriptive nature of big data. …”
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  19. 19
    A balanced partitioning mechanism for multicontroller placement in software-defined wide area networks

    A balanced partitioning mechanism for multicontroller placement in software-defined wide area networks by Saab, Maher Waleed Asaad

    Published 2022
    “…Consequently, the objective of this study is to propose a Balanced Partitioning Mechanism (BPM) based on the notion of a network partition. Moreover, the BPM is designed based on a modified K-means algorithm. …”
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  20. 20
    Evaluation and optimization of frequent, closed and maximal association rule based classification

    Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

    Published 2014
    “…On the other hand maximal itemset based association rules, that are a subset of closed itemset based rules, show to be insufficient in this regard, and typically will have worse recall and generalization power. …”
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