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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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    Final Year Project / Dissertation / Thesis
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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
    Local Stereo Matching Algorithm Using Modified Dynamic Cost Computation

    Local Stereo Matching Algorithm Using Modified Dynamic Cost Computation by Kadmin, Ahmad Fauzan, Hamzah, Rostam Affendi, Abd Manap, Nurulfajar, Hamid, Mohd Saad, Tg. Wook, Tg Mohd Faizal

    Published 2021
    “…A modified census transform with dynamic histogram is used to provide the cost in the cost computation. …”
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  8. 8
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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  9. 9
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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  10. 10
    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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  11. 11
    Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks

    Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks by Mahzan, Shahruddin, J. Staszewski, Wieslaw, Worden, Keith

    Published 2010
    “…This paper compares two advanced signal processing methods for impact location in composite aircraft structures. The first method is based on a modified triangulation procedure and Genetic Algorithms whereas the second technique applies Artificial Neural Networks. …”
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  12. 12
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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  13. 13
    An experimental study of modified black hole algorithms

    An experimental study of modified black hole algorithms by Mohammed, Suad Khairi

    Published 2018
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  14. 14
    A modified strength capacity for composite slab using reliability approach

    A modified strength capacity for composite slab using reliability approach by Mohammed, Kachalla

    Published 2016
    “…Hence, variable deection, _defl and shear resistance, _prop factors are introduced to modify the existing limit state. Similarly, a procedural algorithm lead to the development of pro_led composite slab strength determination function for both longitudinal shear estimation methods by considering section slenderness and deck characteristics. …”
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  15. 15
    Improved stereo matching algorithm based on census transform and dynamic histogram cost computation

    Improved stereo matching algorithm based on census transform and dynamic histogram cost computation by Kadmin, Ahmad Fauzan, Hamzah, Rostam Affendi, Abd Manap, Nurulfajar, Hamid, Mohd Saad, Abd Gani, Shamsul Fakhar

    Published 2021
    “…A modified Census Transform with dynamic histogram is used to provide the cost volume. …”
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  16. 16
    Predicting the rutting parameters of nanosilica/waste denim fiber composite asphalt binders using the response surface methodology and machine learning methods

    Predicting the rutting parameters of nanosilica/waste denim fiber composite asphalt binders using the response surface methodology and machine learning methods by Al-Sabaeei, Abdulnaser M., Alhussian, Hitham, Abdulkadir, Said Jadid, Giustozzi, Filippo, Mohd Jakarni, Fauzan, Md Yusoff, Nur Izzi

    Published 2023
    “…The study conducts an extensive investigation using ML algorithms to accurately predict the multiple stress creep recovery (MSCR) rutting parameters for the base and modified asphalt binders. …”
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  17. 17
    Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives

    Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives by Jegatheesan N., Ibrahim M.R., Ahmed A.N., Koting S., El-Shafie A., Katman H.Y.B.

    Published 2025
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  18. 18
    Structural assessment of damaged and CFRP repaired reinforced concrete beams from experimental modal analysis / Moatasem Mohammed Fayyadh

    Structural assessment of damaged and CFRP repaired reinforced concrete beams from experimental modal analysis / Moatasem Mohammed Fayyadh by Moatasem, Mohammed Fayyadh

    Published 2012
    “…Previous studies have used modal parameters for damage detection and the assessment of repair work, and showed that existing algorithms used for damage detection sometimes produced inaccuracies and anomalies. …”
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  19. 19
    A modified linear programming model for cost minimisation of Pangasius hypophthalmus feed formulation / Zuraida Alwadood, Anis Syahirah Rosli and Norlenda Mohd Noor

    A modified linear programming model for cost minimisation of Pangasius hypophthalmus feed formulation / Zuraida Alwadood, Anis Syahirah Rosli and Norlenda Mohd Noor by Alwadood, Zuraida, Rosli, Anis Syahirah, Mohd Noor, Norlenda

    Published 2022
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  20. 20
    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

    Published 2024
    “…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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