Search Results - (( (variable OR variables) extractions _ algorithm ) OR ( parallel optimization sensor algorithm ))

Refine Results
  1. 1

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…Stereo vision sensor consists of two stereo cameras, mounted parallel in stationary position. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

    Published 2018
    “…The obtained results are compared with the results of four algorithms. These algorithms are Genetic Algorithms (GA), Parallel Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO). …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4
  5. 5
  6. 6

    Strategies of Handling Different Variables Reduction for LDA by Hamid, Hashibah, Mahat, Nor Idayu

    Published 2012
    “…The variables selection technique with local searching algorithm is manipulated. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…A total of 1279 subjects and 9 variables from dataset (1411 subjects and 139 variables) are selected for clustering. t-Distributed Stochastic Neighbour Embedding (t-SNE) for feature extraction and K-means clustering algorithm achieved the highest performance in clustering, which grouping the subjects into Low (13%), Intermediate A (19%), Intermediate B (21%) and High (31%) fall risk group. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  8. 8

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

    Published 2021
    “…In dealing with correlated variables, PCA was embedded in the proposed algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9

    Optimal timber transportation planning in tropical hill forest using bees algorithm by Jamaluddin, Jamhuri

    Published 2022
    “…This study proposed a multi-objective linear programming model with Bees algorithm (BA) to find an optimal cost TTP for extraction, forest road, and landing locations. …”
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

    Published 2015
    “…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
    Get full text
    Get full text
    Thesis
  12. 12

    Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

    Published 2023
    “…A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
    Get full text
    Get full text
    Article
  13. 13

    Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

    Published 2022
    “…Using feature extraction with the t-SNE and the K-means clustering algorithm, subjects were clustered into low, intermediate A, intermediate B and high fall risk groups which corresponded with fall occurrence of 13%, 19%, 21% and 31% respectively. …”
    Get full text
    Get full text
    Article
  14. 14

    Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

    Published 2017
    “…Results: By using the ID3 algorithm, it is possible to consider the relationship among variables and to identify the most informative variables for predicting the classification of the instance. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Characteristics of electronic cigarette and vape users in Malaysia: Lessons from decision tree analysis by Kartiwi, Mira, Nik Mohamed, Mohamad Haniki, Ab Rahman, Jamalludin, Draman, Samsul, Ab Rahman, Norny Syafinaz

    Published 2020
    “…Several predictor variables included in this study were: seven demographics variables (i.e., age, gender, race, residence, marital, occupation and education) and twenty variables on the perception of ECV use. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17
  18. 18

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19

    Analyzing The Potential Of Genetic Algorithm For Maximum Power Point Tracking In Wind Energy Conversion System In Malaysia by Nasrullah Bin Isnin

    Published 2023
    “…A genetic algorithm is used to further optimised the control strategy by finding the optimised variable for the controller. …”
  20. 20

    Linear regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography / Yong Yan Yin by Yong, Yan Ling

    Published 2018
    “…In addition, an inter-observer variability test was performed and has shown that the proposed algorithm has comparable variability against manual luminal area estimations by expert human observers. …”
    Get full text
    Get full text
    Get full text
    Thesis