Search Results - property distribution ((((using algorithm) OR (learning algorithm))) OR (clustering algorithm))

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  1. 1
    Comparison between clustering algorithm for rainfall analysis in Kelantan / Wan Nurshazelin Wan Shahidan and Siti Nurasikin Abdullah

    Comparison between clustering algorithm for rainfall analysis in Kelantan / Wan Nurshazelin Wan Shahidan and Siti Nurasikin Abdullah by Wan Shahidan, Wan Nurshazelin, Abdullah, Siti Nurasikin

    Published 2017
    “…So, in this study clustering algorithm on rainfall distribution dataset is done using WEKA 3.8 software. …”
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  2. 2
    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering

    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering by Hengda, Wang, Mohamad Mohsin, Mohamad Farhan, Mohd Pozi, Muhammad Syafiq

    Published 2024
    “…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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  3. 3
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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  4. 4
    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation

    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…Next, samples are generated from Normal Distribution. To test the effectiveness of the proposed algorithm, the real and generated samples is added to training phase to build a prediction model using M5 Model Tree. …”
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  5. 5
    A cluster-based hybrid replica control protocol for high availability in data grid

    A cluster-based hybrid replica control protocol for high availability in data grid by Mabni, Zulaile

    Published 2019
    “…Another proposed algorithm is replica placement algorithm which selects and places only one replica in each cluster. …”
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  6. 6
    Short term load forecasting using a hybrid neural network

    Short term load forecasting using a hybrid neural network by Yap K.S., Abidin I.Z., Lim C.P., Shah M.S.

    Published 2023
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    Conference paper
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  7. 7
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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  8. 8
    Exploring The Synergy Of Template And Machine Learning Methods To Improve Photometric Redshifts

    Exploring The Synergy Of Template And Machine Learning Methods To Improve Photometric Redshifts by Khalfan, Alshuaili Ishaq Yahya

    Published 2024
    “…The second method uses machine learning algorithms to learn the relationship between a galaxy’s photometric properties and its redshift, based on a training set of spectroscopic redshift measurements. …”
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  9. 9
    Instance matching framework for heterogeneous semantic web content over linked data environment

    Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

    Published 2021
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  10. 10
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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  11. 11
    Ab-initio calculations of the structural, electronic and optical properties of (CdSe)2 clusters

    Ab-initio calculations of the structural, electronic and optical properties of (CdSe)2 clusters by Alselawe, A.I.A., Jumali, MHH, Gopir, G., M.M. Anas

    Published 2020
    “…First, geometry optimization calculations of the possible geometric isomers were carried out using the BroydenFletcher-Goldfarb-Shanno minimization (BFGS) algorithm. …”
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  12. 12
    CFD modeling on coal properties towards the burnout efficiency

    CFD modeling on coal properties towards the burnout efficiency by Nabil Asyraf Abd Halim

    Published 2024
    text::Final Year Project
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  13. 13
    Random sampling method of large-scale graph data classification

    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…Finally, we classified the graphs of data blocks using the SVM algorithm. In experimental evaluation, our proposed method outperformed state-of-the-art graph kernels on graph classification datasets in terms of accuracy.…”
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  14. 14
    Predicting the popularity of tweets using the theory of point processes.

    Predicting the popularity of tweets using the theory of point processes. by Tan, Wai Hong

    Published 2019
    “…The intensity process of the model is interpretable as a cluster Poisson process, which implies that the model can be simulated using the cascading algorithm similar to that used for the efficient simulation of Hawkes processes, and the prediction can be done properly by exploiting the probabilistic properties of the model. …”
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    UMK Etheses
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  15. 15
    Ab-initio Calculations of the Structural, Electronic and Optical Properties of (CdSe)2 Clusters

    Ab-initio Calculations of the Structural, Electronic and Optical Properties of (CdSe)2 Clusters by Alselawe A.I.A., Jumali M.H.H., Gopir G., Anas M.M.

    Published 2024
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    journal::journal article
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  16. 16
    A New Robust Weak Supervision Deep Learning Approach for Reservoir Properties Prediction in Malaysian Basin Field

    A New Robust Weak Supervision Deep Learning Approach for Reservoir Properties Prediction in Malaysian Basin Field by Ahmad Fuad, M.I., Hermana, M., Jaya, M.S., Ishak, M.A.

    Published 2023
    “…In this work, we develop a robust approach to deep learning-based seismic inversion to predict elastic properties from seismic data. …”
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  17. 17
    The implementation of forward chaining algorithm in calculating inheritance property based on faraid law / Nur Ain Syafiqah Mohammad Marzuki

    The implementation of forward chaining algorithm in calculating inheritance property based on faraid law / Nur Ain Syafiqah Mohammad Marzuki by Mohammad Marzuki, Nur Ain Syafiqah

    Published 2021
    “…The distribution of properties is solved using Python Programming Language and also will verify using Inheritance Calculator Mobile Application. …”
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    Student Project
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  18. 18
    Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems

    Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems by Ravari, Arastoo Rostami

    Published 2005
    “…Low-complexity spectral-based estimators are used for the estimation of direction and spatial spread of the distributed source by employing the proposed channel model for simulation. …”
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  19. 19
    Optimized techniques for landslide detection and characteristics using LiDAR data

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…This information is used to examine and manage slope failures and distributions effectively. …”
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  20. 20
    Predictive Framework for Imbalance Dataset

    Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

    Published 2012
    “…Properties of the proposed framework include; developing an approach to correlate materials defects, developing an approach to represent data attributes features, analyzing various ratio and types of data re-sampling, analyzing the impact of data dimension reduction for various data size, and partitioning data size and algorithmic schemes against the prediction performance. …”
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