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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
    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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  8. 8
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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  9. 9
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
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  10. 10
    Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm

    Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm by Golshan, Abolfazl

    Published 2013
    “…With the optimal parameter sets, an operator can select a suitable combination of variables to obtain a better surface finish or lower burr formation. …”
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  11. 11
    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique

    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

    Published 2017
    “…A BRT model was developed using hourly ozone data as a response variable and nitric oxide (NO), Nitrogen Dioxide (NO2) and Nitrogen Dioxide (NOx) and meteorological parameters as explanatory variables. …”
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  12. 12
    Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha

    Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha by Mustapha, Nur Atikah

    Published 2018
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  13. 13
    Design and development of high performance swa cell design for local DNA sequence alignment

    Design and development of high performance swa cell design for local DNA sequence alignment by Syed Abdul Rahman, Syed Abdul Mutalib Al Junid

    Published 2017
    “…Moreover, the minimal size of the two bit data representation characters format used in the design has resulted in minimizing the temporary memory requirement in the cell design up to 75%. …”
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  14. 14
    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods

    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods by Nurshaziana, Mohamad Shamsuri

    Published 2025
    “…The simulation study was conducted under various data conditions; number of variables, sample sizes, percentages of outliers, and data distribution to measure the performance using Cophenetic Correlation Coefficient (CCC). …”
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  15. 15
    A microscopic swarm model simulation and fractal approach towards swarm agent behaviour

    A microscopic swarm model simulation and fractal approach towards swarm agent behaviour by Widyarto, Setyawan, Abd. Latiff, Muhammad Shafie

    Published 2006
    “…The developed model also uses the physical based variables that can be measured. …”
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  16. 16
    Assessment of proposed lateral resistance system used with framed structures

    Assessment of proposed lateral resistance system used with framed structures by Fateh, Amir

    Published 2016
    “…Whereas the, most of the variable stiffness systems are operated using high-tech signal processors, controllers, and external electrical supply.Additionally, the aforesaid systems are highly dependent on controller, energy resources and required repetitive maintenance. …”
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  17. 17
    Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting

    Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting by YAXING, WEI, HUZAIFA, HASHIM, Lai, Sai Hin, CHONG, KAI LUN, HUANG, YUK FENG, ALI NAJAH, AHMED, MOHSEN, SHERIF, AHMED, EL-SHAFIE

    Published 2024
    “…For this dataset, wavelet transformation significantly improves the resolution of lag noise when historical streamflow data are used as lagged input variables, producing a 6% reduction in the root-mean-square error. …”
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  18. 18
    Zero distortion-based steganography for handwritten signature

    Zero distortion-based steganography for handwritten signature by Iranmanesh, Vahab

    Published 2018
    “…Thus, developing a steganographic algorithm to use cover media (c) without raising attention is the most challenging task in data hiding. …”
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  19. 19
    Artificial Intelligence (AI) to predict dental student academic performance based on pre university results

    Artificial Intelligence (AI) to predict dental student academic performance based on pre university results by Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

    Published 2021
    “…Data will be analyzed statistically for each variable, visualized into graphical format, and the correlation coefficients computed. …”
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    Proceeding Paper
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  20. 20
    Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi

    Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi by Hosseiny Fatemi, Mohammad Reza

    Published 2012
    “…For the hardware architecture design, we choose bit-serial structure for implementing our algorithm to benefit from its advantages. Moreover, we use SAD truncation, reusability, source sharing, and power saving techniques in our architecture, which lead to area saving and power consumption reduction. …”
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