Search Results - time estimation ((mining algorithm) OR (means algorithm))

Refine Results
  1. 1

    A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Wendy Ling, Shinyie, Tan Lit, Ken

    Published 2022
    “…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), Hartigan- Wong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Zun, Liang Chuan, Wan Yusof, Wan Nur Syahidah, Senawi, Azlyna, Mohd Akramin, Mohd Romlay, Soo, Fen Fam, Wendy, Ling Shinyie, Tan, Lit Ken

    Published 2022
    “…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Shinyie, Wendy Ling, Ken, Tan Lit

    Published 2022
    “…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Zun, Liang Chuan, Fam, Soo Fen, Wan Yusof, Wan Nur Syahidah, Senawi, Azlyna, Mohd Akramin, Mohd Romlay, Wendy, Ling Shinyie, Tan, Lit Ken

    Published 2022
    “…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), Hartigan-Wong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5
  6. 6

    Estimating 1-MCP application for Kampuchea guava with data mining technology by Ding, Phebe, Khor, Kor Chin

    Published 2018
    “…In this preliminary study, data mining (DM) technology was utilized to achieve fast estimation of 1-MCP application based on different qualities of 'Kampuchea' Guava. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…The BayesNet ML-ADR classifier model performance evaluation with the highest kappa statistic value of 0.991, the lowest mean absolute error value of 0.0009, weighted average precision values of 99.2 %, ROC area coverage of 100 %, the most down trip decision time of 10 ms better than the existing 20 ms for conventional ADR. …”
    Get full text
    Get full text
    Thesis
  8. 8
  9. 9

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
    Get full text
    Get full text
    UMK Etheses
  10. 10
  11. 11

    Severity Estimation of Plant Leaf Diseases Using Segmentation Method by Chyntia Jaby, Entuni, Tengku Mohd Afendi, Zulcaffle, Kuryati, Kipli, Fatih, Kurugollu

    Published 2020
    “…The best severity estimation algorithm and color space used to estimate the diseases severity of plant leaf is the combination of Fuzzy C-Means and YCbCr color space. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    On time-domain OFDM channel estimation: Use of pilots correlation for digital video broadcasting (DVB) cable receiver by Khan, A.M., Jeoti, V.

    Published 2015
    “…In this paper, an improved OFDM time domain channel estimation algorithm is proposed for (DVB) Cable receivers. …”
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
    Get full text
    Get full text
    Article
  15. 15

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…In the first sub-algorithm, the state mean propagation removes the Gaussian white noise to obtain the expected solution. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
    Get full text
    Get full text
    Article
  17. 17

    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

    Published 2018
    “…Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the ordinary least squares (LS) estimator in terms of mean squared error (MSE). …”
    Get full text
    Get full text
    Book Section
  18. 18

    Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system by Abdolee, Reza

    Published 2006
    “…At the next stage of the project, the effect of channel estimation algorithm on performance of MIMO-OFDM system was investigated. …”
    Get full text
    Get full text
    Thesis
  19. 19
  20. 20

    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

    Published 2012
    “…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
    Get full text
    Get full text
    Article