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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
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    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
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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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
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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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
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  8. 8
    Real time nonlinear filtered-x lms algorithm for active noise control

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…However, unlike the other algorithms, NLFXLMS cannot be implemented in real time. …”
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  9. 9
    High Rise Building Evacuation Route Model Using DIJKSTRA'S Algorithm

    High Rise Building Evacuation Route Model Using DIJKSTRA'S Algorithm by Mohd Sabri, Nor Amalina

    Published 2015
    “…The information then is used to generate a directed graph in order to obtain the shortest path results through the implementation of shortest path algorithm. The main algorithms involve is Dijkstra’s algorithm and then an Ant Colony Optimization algorithm is used as hybrid versions of Dijkstra’s algorithm. …”
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  10. 10
    Hub Angle Control for A Single Link Flexible Manipulator Based on Cuckoo Search Algorithm

    Hub Angle Control for A Single Link Flexible Manipulator Based on Cuckoo Search Algorithm by aiman Azrael, Shaiful Nahar Sukri, Siti Sarah Zahidah, Nazri, Muhamad Sukri, Hadi, Annisa, Jamali, Hanim, Mohd Yatim, Intan Zaurah, Mat Darus

    Published 2021
    “…System identification was implemented via swarm intelligence algorithm known as cuckoo search algorithms based on auto regressive with exogenous model structure. …”
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  11. 11
    Development of lung cancer prediction system using meta-heuristic optimized deep learning model

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…The algorithm detects the affected region depending on pixel similarity computation process. …”
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  12. 12
    Enhancing indoor positioning service for location based internet of things (IoT): a source selecting approach with error compensation

    Enhancing indoor positioning service for location based internet of things (IoT): a source selecting approach with error compensation by Chui, Yew Leong, Perumal, Thinagaran, Yaakob, Razali, Kwan, Wei Peng

    Published 2017
    “…This proposed model includes implementation of enhanced RSSI technique with error compensation algorithm to determine the position of users or targeted objects with correct reference points to improve the positioning result.…”
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  13. 13
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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  14. 14
    Web Algorithm search engine based network modelling of Malaria Transmission

    Web Algorithm search engine based network modelling of Malaria Transmission by Eze, Monday Okpoto

    Published 2013
    “…The Hypertext Induced Topical Search (HITS) web search algorithm was adapted to implement a search engine, which uses the bipartite contact network as the input. …”
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  15. 15
    Development of dynamic programming algorithm for maintenance scheduling problem

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…The dynamic programming model developed for this research reflected the flow of the maintenance activity of the company and implemented the model by Lieberman and Hillier (2010). …”
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  16. 16
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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  17. 17
    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

    Published 2021
    “…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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  18. 18
    Cyberbullying detection: a machine learning approach

    Cyberbullying detection: a machine learning approach by Yeong, Su Yen

    Published 2022
    “…Machine learning is a hot topic and it is widely implemented in software, web application and more. Those algorithms are used in the classification or regression model to predict an input. …”
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  19. 19
    Model predictive control of air-conditioning system for electric vehicles.

    Model predictive control of air-conditioning system for electric vehicles. by Ang, Wei Hang

    Published 2022
    “…After defining the prediction model, the model will be implemented to the MPC by using MATLAB. …”
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  20. 20
    Analysis of LMS and NLMS noise cancellations of speech signal using Matlab Simulink / Roziahtushahila Hashim

    Analysis of LMS and NLMS noise cancellations of speech signal using Matlab Simulink / Roziahtushahila Hashim by Hashim, Roziahtushahila

    Published 2014
    “…It is found that the NLMS is a variant of the LMS algorithm which is more robust when implemented in finite-precision hardware and well understood convergence behaviour compare to the other adaptive algorithm.…”
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