Search Results - (( data optimization method algorithm ) OR ( data transformation based algorithm ))

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  1. 1

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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    Thesis
  2. 2

    Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid by Zahid, Zuhaili

    Published 2008
    “…Thus, this project will introduce a genetic-algorithms-based technique to overcome the rounding error problem. …”
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    Thesis
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    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…The major contribution of this research is to introduce a Taylor-Bird Swarm optimization-based Deep Belief Network (Taylor-BSA-based DBN) for medical data classification. …”
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    Thesis
  5. 5

    Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines by K.S.R., Rao, Z.F., Desta

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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    Conference or Workshop Item
  6. 6

    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

    Published 2003
    “…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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    Proceeding Paper
  7. 7

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…Clustering, an unsupervised method of grouping sets of data, is used as a solution technique in various fields to divide and restructure data to become more significant and transform them into more useful information. …”
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    Article
  8. 8

    Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm by Salami, Momoh Jimoh Emiyoka, Najeeb, Athaur Rahman

    Published 2012
    “…The proposed model coefficients determination in conjunction with various methods of optimal model order determination were then applied on MRI data using both Transient Error Reconstruction Algorithm (TERA) and modified Transient Error Reconstruction Algorithm to obtain images with improved resolution. …”
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    Monograph
  9. 9

    Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

    Published 2014
    “…This thesis also presents the study of a method to improve the descriptive accuracy of DARA algorithm by generating multi-instances of summarized data. …”
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    Thesis
  10. 10

    Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform by Abdul Rashid, Abdul Hadi

    Published 2014
    “…Later, an algorithm combining both Genetic Algorithm and Discrete Cosine Transform was proposed, which shows the step-by-step sequence of both methods. …”
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    Final Year Project
  11. 11

    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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    Conference or Workshop Item
  12. 12

    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

    Published 2009
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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    Conference or Workshop Item
  13. 13

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…The hybrid method, IDBA-AFW, aims to enhance the original IDBA by incorporating the Adaptive Floyd-Warshall algorithm for graph transformation and optimization. …”
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    Thesis
  14. 14

    Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks by K.S.R, Rao, F. D., Zahlay

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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    Conference or Workshop Item
  15. 15

    Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

    Published 2018
    “…Since there are many methods involved in each task of the multilayered ensemble, genetic algorithm is added to optimize the overall framework in order to select the optimal combinations of methods in each layer that can produce satisfactory results. …”
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    Thesis
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    Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes by Reem Mustafa , Mah’d Al Debes

    Published 2025
    “…The research leverages Artificial Intelligence (AI)-based Genetic Algorithms (GA) and game theory to address critical challenges in resource allocation. …”
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    Thesis
  20. 20

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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    Monograph