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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
    On damping parameters of Levenberg-Marquardt algorithm for nonlinear least square problems

    On damping parameters of Levenberg-Marquardt algorithm for nonlinear least square problems by Sulaiman, I.M, Zamri, N., Mamat, M., Umar, A.O., Waziri, M.Y.

    Published 2021
    “…The Levenberg-Marquardt (LM) algorithm is a widely used method for solving problems related to nonlinear least squares. …”
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  8. 8
    Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique

    Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique by Al-Ewiwi, Mahmoud

    Published 2006
    “…Scheduling of a multiple distributed servers is considered as a complex problem.considered as NP-complete problem,where no single efficient algorithm guaranteed to produce optimal results.This thesis investigates on how to find optimal solution for distribute system,by implementing market based scheduling Algorithm(MBSA).On implementing the MBSA, a new auction technique which is the least suitable sealed bid auction will be introduced.it is found that least suitable sealed bid technique will give the close-to-optimum solution.In the implementation, cooperative agents were used as a middleware between web servers and stand-alone schedulers. …”
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  9. 9
    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. …”
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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
    A hybrid local search algorithm for minimum dominating set problems

    A hybrid local search algorithm for minimum dominating set problems by Abed, S.A., Rais, H.M., Watada, J., Sabar, N.R.

    Published 2022
    “…In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. …”
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  12. 12
    A hybrid local search algorithm for minimum dominating set problems

    A hybrid local search algorithm for minimum dominating set problems by Abed, S.A., Rais, H.M., Watada, J., Sabar, N.R.

    Published 2022
    “…In the first stage, we propose an adaptive information content-based local search algorithm as an exploratory procedure. This algorithm focuses on generating promising solutions in different areas of the solution space using the problem search history. …”
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  13. 13
    Least congested channel recommendation for uncoordinated WiFi access point / Ag Ibrahim Ag Daud

    Least congested channel recommendation for uncoordinated WiFi access point / Ag Ibrahim Ag Daud by Ag Daud, Ag Ibrahim

    Published 2017
    “…This study has design channel scoring algorithm using Link Score Method, whereby the channel with the highest score were selected as least congested channel (LCC). …”
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  14. 14
    Application of least square method and conjugate gradient method for solving second order differential equation / Nur Fatonah Kamsani

    Application of least square method and conjugate gradient method for solving second order differential equation / Nur Fatonah Kamsani by Kamsani, Nur Fatonah

    Published 2018
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  15. 15
    Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nurulhuda Zainuddin and Khairiyah Md Shahid

    Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur... by Saman, Fadhlina Izzah, Zainuddin, Nurulhuda, Md Shahid, Khairiyah

    Published 2012
    “…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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    Research Reports
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  16. 16
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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  17. 17
    Optimization of drilling path using the bees algorithm

    Optimization of drilling path using the bees algorithm by Kamaruddin, Shafie, Rosdi, Mohamad Naqiuddin, Sukindar, Nor Aiman

    Published 2021
    “…Optimization is the process of finding the best possible solutions to a problem. It has been widely used in various areas especially in engineering problems. …”
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  18. 18
    Travelling salesman problem using genetic algorithm / Muhammad Faiz Wafiq Mohd Zaini, Nurin Hannani Mohd Bakhary and Nur Aishah Zakaria

    Travelling salesman problem using genetic algorithm / Muhammad Faiz Wafiq Mohd Zaini, Nurin Hannani Mohd Bakhary and Nur Aishah Zakaria by Mohd Zaini, Muhammad Faiz Wafiq, Mohd Bakhary, Nurin Hannani, Zakaria, Nur Aishah

    Published 2022
    “…Travelling Salesmen Problem is a well-known algorithm problem in the fields of computer science and operation research. …”
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  19. 19
    An enhanced distance vector-hop algorithm using new weighted location method for wireless sensor networks

    An enhanced distance vector-hop algorithm using new weighted location method for wireless sensor networks by Han, Fengrong, Izzeldin Ibrahim, Mohamed Abdelaziz, Liu, Xinni, Kamarul Hawari, Ghazali

    Published 2020
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  20. 20
    Robust multivariate least angle regression

    Robust multivariate least angle regression by Uraibi, Hassan Sami, Midi, Habshah, Rana, Sohel

    Published 2017
    “…The least angle regression selection (LARS) algorithms that use the classical sample means, variances, and correlations between the original variables are very sensitive to the presence of outliers and other contamination. …”
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