Search Results - (( data visualisation using algorithm ) OR ( evolution classification model algorithm ))

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  1. 1
    Urban green space spatio-temporal change influences on land surface temperature in Kuala Lumpur, Malaysia

    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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  2. 2
    Multi-dimensional Data Visualisation using Mobile Augmented Reality

    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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  3. 3
    Effectiveness of silhouette rendering algorithms in terrain visualisation

    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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  4. 4
    Visualisation System of COVID-19 Data in Malaysia

    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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  5. 5
    3D terrain visualisation for GIS: A comparison of different techniques

    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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  6. 6
    Visualisation System of COVID-19 Data in Malaysia

    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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  7. 7
    A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES

    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
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  8. 8
    Classification of Immunosignature Using Random Forests for Cancer Diagnosis

    Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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  9. 9
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

    Published 2017
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  10. 10
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
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  11. 11
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
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  12. 12
    Deep learning detector for pests and plant disease recognition

    Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

    Published 2020
    “…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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  13. 13
    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network

    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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  14. 14
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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  15. 15
    A case study : 2D Vs 3D parallel differential equation toward tumor cell detection on multi-core parallel computing atmosphere

    A case study : 2D Vs 3D parallel differential equation toward tumor cell detection on multi-core parallel computing atmosphere by Islam, Md. Rajibul, Alias, Norma

    Published 2010
    “…In order to detect tumour cells, 2D and 3D Partial Differential Equations (PDE) are considered and compared by using Multi-Core parallel computing atmosphere with visualisation, communication and data analysis. …”
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  16. 16
    Digital economy tax compliance model in Malaysia using machine learning approach

    Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

    Published 2021
    “…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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  17. 17
    Stock market turning points rule-based prediction / Lersak Photong … [et al.]

    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Feature selection was used to sort out key features for further classification. News classification into factors affecting stock market turning point was done using Naïve Bayes, Deep Learning, Generalized Linear Model (GLM) and Support Vector Machine (SVM). …”
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  18. 18
    Dynamic modeling by usage data for personalization systems

    Dynamic modeling by usage data for personalization systems by Aghabozorgi, S.R., Teh, Y.W.

    Published 2009
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  19. 19
    PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER

    PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER by Tay, Guo Hong

    Published 2019
    “…This is because both Naive Bayes and SVM are baseline algorithm used in text classification. In the end, a visualisation of HFMD Disease Map is presented to visualize the city that suffer HFMD outbreak using geo-located tweet that related with HFMD. …”
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    Final Year Project Report / IMRAD
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  20. 20
    Classification with degree of importance of attributes for stock market data mining

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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