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  1. 1
    Sales prediction for Adha Station by using predictive analytics

    Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

    Published 2025
    “…Additionally, pre-processing is conducted using the RapidMiner application prior to mapping the cleaned data with three distinct algorithms for predictive analysis: Decision Tree, Random Forest, and Multiple Linear Regression techniques. …”
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  2. 2
    Optimizing E-commerce inventory management using a machine-learning approach

    Optimizing E-commerce inventory management using a machine-learning approach by Ruonan, Zhao, Wong, Doris Hooi-Ten

    Published 2025
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  3. 3
    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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  4. 4
    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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  5. 5
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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    Thesis
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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, 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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  7. 7
    A near-optimal centroids initialization in K-means algorithm using bees algorithm

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
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  8. 8
    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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    Book Section
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  9. 9
    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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  10. 10
    Data clustering using the bees algorithm

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…K-means clustering involves search and optimization. …”
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  11. 11
    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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  12. 12
    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem

    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

    Published 2021
    “…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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  13. 13
    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction

    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction by Tan, James Yiaw Beng

    Published 2012
    “…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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  14. 14
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…SGD uses random or batch data sets to compute gradient in solving optimization problems. …”
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  15. 15
    Clustering chemical data set using particle swarm optimization based algorithm

    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
    “…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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  16. 16
    An improved data classification framework based on fractional particle swarm optimization

    An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

    Published 2019
    “…The proposed algorithm is tested and verified for optimization performance comparison on ten benchmark functions against six existing established algorithms in terms of Mean of Error and Standard Deviation values. …”
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  17. 17
    Cluster optimization in VANET using MFO algorithm and K-Means clustering

    Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

    Published 2023
    “…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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  18. 18
    Discovering optimal clusters using firefly algorithm

    Discovering optimal clusters using firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
    “…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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  19. 19
    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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  20. 20
    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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