Search Results - (( (quantile OR quantify) selection method algorithm ) OR ( java implementation path algorithm ))

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  1. 1
    Elastic net penalized Quantile Regression Model and Empirical Mode Decomposition for Improving the Accuracy of the Model Selection

    Elastic net penalized Quantile Regression Model and Empirical Mode Decomposition for Improving the Accuracy of the Model Selection by Ali S.A. Ambark, Mohd Tahir Ismail, Abdullah S. Al-Jawarneh, Samsul Ariffin Abdul Karim

    Published 2023
    “…Such methods are ridge penalized quantile regression, lasso penalized quantile regression, and elastic net penalized quantile regression which are used for variable selection and regularization and deals with the multicollinearity problem when it exists between the predictor variables. …”
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  2. 2
    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection

    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

    Published 2024
    “…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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  3. 3
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  4. 4
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  5. 5
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  6. 6
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…The selected best quantile population will be brought to the next generation. …”
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  7. 7
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  8. 8
    Development of saliency metric for autonomous landmark selection in cognitive robot navigation / Gao Hanyang

    Development of saliency metric for autonomous landmark selection in cognitive robot navigation / Gao Hanyang by Gao , Hanyang

    Published 2022
    “…This dissertation proposes an algorithm to quantify urban landmarks based on visual salience indicators for cognitive robot navigation. …”
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  9. 9
    Implementation of Color Filtering on FPGA

    Implementation of Color Filtering on FPGA by Mohd Shukor, Mohd Nasir, Lo, H. H., Sebastian, Patrick

    Published 2007
    “…The second is the double band-pass-filter algorithm. Work is currently conducted to quantify the effectiveness of the band-pass filtering algorithm on FPGA before proceeding to test and implement the triple and quadruple band-pass filtering methods.…”
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  10. 10
    OPTIMIZATION OF A CRUDE DISTILLATION UNIT USING PARAMETRIC DESIGN OF TAGUCHI AND RESPONSE SURFACE METHODS

    OPTIMIZATION OF A CRUDE DISTILLATION UNIT USING PARAMETRIC DESIGN OF TAGUCHI AND RESPONSE SURFACE METHODS by ALI, SYED FAIZAN

    Published 2014
    “…Variables with more than 90% contribution factors are selected and validated with the response surface method. …”
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  11. 11
    Load shedding scheme for islanded distribution network with flexible load selection and power changes / Ja’far Saifeddin Abdelhafiz Jallad

    Load shedding scheme for islanded distribution network with flexible load selection and power changes / Ja’far Saifeddin Abdelhafiz Jallad by Ja’far Saifeddin , Abdelhafiz Jallad

    Published 2018
    “…A metaheuristic algorithm in the UFLS scheme can be used to select the best load combination in real time. …”
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  12. 12
    Implementation of color filtering on FPGA

    Implementation of color filtering on FPGA by P., Sebastian, M.N.B.M., Shukor, H.H., Lo

    Published 2007
    “…The second is the double band-pass-filter algorithm. Work is currently conducted to quantify the effectiveness of the band-pass filtering algorithm on FPGA before proceeding to test and implement the triple and quadruple band-pass filtering methods. …”
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  13. 13
    Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning

    Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Daud, Muhamad Aliff Imran, Ahmad Puzi, Asmarani, Sidek, Shahrul Na'im, Zainuddin, Ahmad Anwar, Mohd Khairuddin, Ismail, Abd Mutalib, Mohd Azri

    Published 2024
    “…The test results determined the selection of twenty-five features from a total of forty-eight which be used to train an optimum classifier algorithm for the purpose of quantifying the level of muscle spasticity. …”
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  14. 14
    Tracking using normalized cross correlation and color space

    Tracking using normalized cross correlation and color space by P., Sebastian, V.V., Yap

    Published 2007
    “…In addition to the TDR being used as a metric to determine the accuracy of a tracking method, another metric was formulated to quantify the accuracy of a tracking algorithm. …”
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  15. 15
    Monitoring the drying process of glutinous rice using hyperspectral imaging coupled with multivariate analysis

    Monitoring the drying process of glutinous rice using hyperspectral imaging coupled with multivariate analysis by Jimoh, Kabiru Ayobami, Hashim, Norhashila, Shamsudin, Rosnah, Che Man, Hasfalina, Jahari, Mahirah

    Published 2024
    “…The model prediction performance shows an accuracy (R²P) of 0.9206 with RMSEP of 1.1410. Using CARS algorithm resulted in the selection of 21 optimal wavelengths that are highly associated with the moisture content of glutinous rice during the drying process and the developed PLS model based on the selected wavelength gave an increased model accuracy with R2CV and RMSECV of 0.9176 and 1.0986 respectively. …”
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  16. 16
    Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning

    Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning by Muhamad Aliff Imran, Daud, Asmarani Ahmad Puzi, asmarani@iium.edu.my, Shahrul Na’im, Sidek, Ahmad Anwar, Zainuddin, Ismail, Mohd Khairuddin, Mohd Azri, Abd Mutalib

    Published 2024
    “…The test results determined the selection of twenty-five features from a total of forty-eight which be used to train an optimum classifier algorithm for the purpose of quantifying the level of muscle spasticity. …”
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  17. 17
    FACE CLASSIFICATION FOR AUTHENTICATION APPROACH BY USING WAVELET TRANSFORM AND STATISTICAL FEATURES SELECTION

    FACE CLASSIFICATION FOR AUTHENTICATION APPROACH BY USING WAVELET TRANSFORM AND STATISTICAL FEATURES SELECTION by DAWOUD JADALAH, NADIR NOURAIN

    Published 2011
    “…In the last method, the Modified K-Means Algorithm was used to remove the non-face regions in the input image. …”
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  18. 18
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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  19. 19
    Objective quantification of selective attention in schizophrenia a hybrid TMS – EEG approach

    Objective quantification of selective attention in schizophrenia a hybrid TMS – EEG approach by W Azlan, Wan Amirah

    Published 2017
    “…In conclusion, the combined TMS-EEG approach shows a promising way to study the selective attention in schizophrenia. By successfully quantifying the neural correlates of auditory selective attention reflected in ALRs using the WPS and discriminating the control and patient groups using C4.5 decision tree provides an objective way to diagnose schizophrenia in compliment to the current subjective method.…”
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  20. 20
    Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach

    Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach by Selvarajah, Gayathri Thevi, Bonestroo, Floor A. S., Timmermans Sprang, Elpetra P. M., Kirpensteijn, Jolle, Mol, Jan A.

    Published 2017
    “…BACKGROUND: Quantitative PCR (qPCR) is a common method for quantifying mRNA expression. Given the heterogeneity present in tumor tissues, it is crucial to normalize target mRNA expression data using appropriate reference genes that are stably expressed under a variety of pathological and experimental conditions. …”
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