Search Results - (( simulation utilisation data algorithm ) OR ( java application mining algorithm ))

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    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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    Article
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    Smart grid: Bio-inspired algorithms energy distributions for data centers by Woo, Yu Hang

    Published 2025
    “…These algorithms aim to reduce power consumption, improve resource utilisation, and enhance overall data centre efficiency. …”
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    Final Year Project / Dissertation / Thesis
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    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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    Conference or Workshop Item
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    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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    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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    Thesis
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    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

    Published 2018
    “…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

    Published 2023
    “…The simulation results demonstrate that the proposed algorithm outperforms existing heuristic and meta-heuristic algorithms, including the benchmarking algorithm (LACE). …”
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    Thesis
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    Max-average: an extended max-min scheduling algorithm for Grid computing environtment by Maipan-uku, J. Y., Muhammed, Abdullah, Abdullah, Azizol, Hussin, Masnida

    Published 2016
    “…The results from our simulation showed that our proposed algorithm is performing better in producing good quality solutions, particularly in executing tasks fast and in balancing the load (resource utilisation) among the resources more effectively when compared to standard Minimum Execution Time (MET), Minimum Completion Time (MCT), Min-Min, and Max-Min heuristic approaches.…”
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    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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    Thesis
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    Monthly rainfall prediction model of Peninsular Malaysia using clonal selection algorithm by Rodi, N.S.Noor, Malek, M.A, Ismail, Amelia Ritahani

    Published 2018
    “…This study proposed algorithm is utilised to predict future monthly rainfall in Peninsular Malaysia. …”
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    Parametric system identification and active vibration control of vibrational structures using genetic algorithm by Mohammad Sofi @ Aziz, Azfi Zaihan

    Published 2007
    “…The sets of data obtained were utilised to develop ARX model using Least Squares (LS), Recursive Least Squares (RLS) and Genetic Algorithm (GA) methods. …”
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    Predicting energy consumption pattern based on top trending videos YouTube 2021 using machine learning techniques by Ng, Jiun Shen

    Published 2022
    “…In this project, several models will be presented and analysed, with the normal equation in Linear Regression will be the algorithm used to simulate it. Furthermore, the data will be clustered in this project utilising threshold-based approaches. …”
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    Final Year Project / Dissertation / Thesis
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    Monthly rainfall prediction model of Peninsular Malaysia Using Clonal Selection Algorithm by Rodi N.S.N., Malek M.A., Ismail A.R.

    Published 2023
    “…This study proposed algorithm is utilised to predict future monthly rainfall in Peninsular Malaysia. …”
    Article
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    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…Both simulated and real data sets were utilised to measure the performance of the proposed algorithms based on two evaluation indicators, sensitivity and specificity. …”
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