Search Results - (( java implementation clustering algorithm ) OR ( basic implementation learning algorithm ))

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  1. 1

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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    Thesis
  2. 2

    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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    Thesis
  3. 3

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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    Final Year Project
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  5. 5

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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    Final Year Project / Dissertation / Thesis
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    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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    Conference or Workshop Item
  8. 8

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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  9. 9

    Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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    Thesis
  10. 10
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    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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    Thesis
  12. 12

    IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE by ABDUL RAZAK, NUSRAH

    Published 2017
    “…Selected basic behaviour-based algorithms such as wallfollower, obstacle avoidance, escape route and target detection are to be combined and its efficiency is measured. …”
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    Final Year Project
  13. 13

    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system by M.H., Ali, Mohamad, Fadlizolkipi, Ahmad Firdaus, Zainal Abidin, Nik Zulkarnaen, Khidzir

    Published 2018
    “…This work proposes the extreme learning machine (ELM) is one of the poplar machine learning algorithms which, easy to implement with excellent learning performance characteristics. …”
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    Conference or Workshop Item
  14. 14

    Comparative study on job scheduling using priority rule and machine learning by Murad, Saydul Akbar, Zafril Rizal, M Azmi, Abu Jafar, Md Muzahid, Al-Imran, Md.

    Published 2021
    “…We’ve achieved better for SJF and a decent machine learning algorithm outcome as well.…”
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    Conference or Workshop Item
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    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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    Thesis
  17. 17

    Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

    Published 2018
    “…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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    Article
  18. 18

    Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

    Published 2018
    “…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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    Article
  19. 19

    Assessing the outcome of Competencies Level from Knowledge-Based Project by Sungsinlert, Anyamanee

    Published 2008
    “…This project is the new idea to implement the Knowledge Management by applying the concept of Knowledge Map and Social Network Map, which are the basic implementation of Knowledge Management, with Artificial Neural Network (ANN) Algorithm ofArtificial Intelligence System. …”
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    Final Year Project
  20. 20

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…This research presents an efficient way to facilitate the hearing loss symptoms diagnosis process by designing a symptoms identification model that efficiently identify hearing loss symptoms based on air and bone conduction pure-tone audiometry data. The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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    Thesis