Search Results - (( using vectorization means algorithm ) OR ( data visualisation using algorithm ))

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  1. 1

    Multi-dimensional Data Visualisation using Mobile Augmented Reality by Rehman Ullah, Khan, Yin, Bee Oon, Ahmad Sofian, Shminan, Lee, Jun Choi, Chen, Jacqueline How Ting

    Published 2020
    “…Therefore, this algorithm uses AR to provide a multi-display solution for improved data visualisation after processing, summarising and classifying data. …”
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    Article
  2. 2

    Effectiveness of silhouette rendering algorithms in terrain visualisation by Che Mat, Ruzinoor, Visvalingam, Mahes

    Published 2002
    “…Silhouette Rendering Algorithms have been successfully used in various applications such as communicating shape and cartoon rendering.This paper explores how effective silhouette rendering algorithms could be used in terrain visualisation. …”
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    Conference or Workshop Item
  3. 3

    Urban green space spatio-temporal change influences on land surface temperature in Kuala Lumpur, Malaysia by Abu Kasim, Junainah

    Published 2020
    “…Accordingly, this study aims to monitor the UGS changes and LST pattern in Kuala Lumpur (KL) for the past six years and to develop an automated prediction model of these scenario for the year 2025 via temporal and spatial variation, using high-resolution aerial imagery data supported by the use of advanced technology mapping. …”
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    Thesis
  4. 4

    Visualisation System of COVID-19 Data in Malaysia by Rehman Ullah, Khan, NOR SYAZA, SYAMIMI, CLADIA SIMBUT, MAMBANG, IVY, THOMAS, TZI NI, WEE

    Published 2021
    “…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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    Article
  5. 5

    3D terrain visualisation for GIS: A comparison of different techniques by Ruzinoor, Che Mat, Mohamed Shariff, Abdul Rashid, Mahmud, Ahmad Rodzi, Pradhan, Biswajeet

    Published 2011
    “…The results of this paper will be of help to the users in identifying the best technique of terrain visualisation suitable for GIS data.…”
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    Book Section
  6. 6

    Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms by Afzal, Asif, Alshahrani, Saad, Alrobaian, Abdulrahman, Buradi, Abdulrajak, Khan, Sher Afghan

    Published 2021
    “…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
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    Article
  7. 7

    Visualisation System of COVID-19 Data in Malaysia by Rehman Ullah, Khan, NOR SYAZA, SYAMIMI, CLADIA SIMBUT, MAMBANG, IVY, THOMAS, NI WEE, TZI

    Published 2021
    “…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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    Article
  8. 8
  9. 9

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
  10. 10

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
  11. 11

    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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    Thesis
  12. 12

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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    Thesis
  13. 13

    A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES by Ling, Chien

    Published 2020
    “…Clustering is used to identify the intrinsic grouping of a set of unlabelled data. …”
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    Final Year Project Report / IMRAD
  14. 14

    Short term forecasting based on hybrid least squares support vector machines by Zuriani, Mustaffa, M. H., Sulaiman, Ernawan, Ferda, Noorhuzaimi, Mohd Noor

    Published 2018
    “…In this study, hybrid Least Squares Support Vector Machines (LSSVM) with four meta-heuristic algorithms viz. …”
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    Article
  15. 15

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

    Published 2013
    “…MATLAB was used to implement the model system. The output shows the public places which habour the infected malaria vectors, and their corresponding vector densities. …”
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    Thesis
  16. 16

    Ontology-based indexing of annotated images using semantic DNA and vector space model by Engku Fadzli Hasan, Syed Abdullah, Setchi, Rossitza

    Published 2014
    “…The proposed approach is evaluated by comparing the indexing achieved using the proposed semantic algorithm with results obtained using a traditional TF-based indexing in vector space model (VSM) with singular value decomposition (SVD) technique. …”
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    Conference or Workshop Item
  17. 17

    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

    Published 2017
    “…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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    Thesis
  18. 18

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
    Article
  19. 19

    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

    Published 2020
    “…Five evaluation metrics were utilized; mean average percent error (MAPE), accuracy, symmetric mean absolute percent error (SMAPE), root mean square percent error (RMSPE) and fitness value. …”
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    Article
  20. 20

    Ontology-based indexing of annotated images using semantic DNA and vector space model by Engku Fadzli Hasan, Syed Abdullah, Setchi, Rossitza

    Published 2011
    “…The proposed approach is evaluated by comparing the indexing achieved using the proposed semantic algorithm with results obtained using a traditional TF-based indexing in vector space model (VSM) with singular value decomposition (SVD) technique. …”
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    Conference or Workshop Item