Search Results - (( using optimization model algorithm ) OR ( features extraction method algorithm ))*

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  1. 1

    Optimised content-social based features for fake news detection in social media using text clustering approach by Yahya, Adnan Hussein Ali

    Published 2025
    “…The accuracy of fake news detection models relies mainly on the quality of the extracted features and the method used in detection. …”
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    Thesis
  2. 2

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…The proposed CGWO and OBCGWO are then applied to select the relevant features from the original feature set. Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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  5. 5

    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. …”
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  6. 6

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  7. 7

    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

    Published 2019
    “…In addition, to prove the superiority of the proposed hybrid forecasting method the simulation results obtained using ANN and ANFIS models optimized by other well-known optimization methods have been compared with that of proposed method. © 2019 IEEE.…”
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  8. 8

    Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

    Published 2012
    “…As a result,it will first introduce the theories about the feature extraction and the basic principles on how feature points can act as locating resynchronization between watermark insertion and extraction discussed in detail.Subsequently,it will present several content-based watermark embedding and extraction methods which can be directly implemented based on the synchronization scheme.Further detailed watermarking schemes which combine feature regions extraction with counter propagation neural network-based watermarks synapses memorization are then presented.The performance of watermarking schemes based on framework of feature point shows the following advantages:a)Good imperceptibility. …”
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  10. 10

    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 algorithms are developed using MATLABTM software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsTM, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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  11. 11

    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 algorithms are developed using MATLAB software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytems, and the spectra of the fault data are analyzed using fast Fourier transform to extract features of each type of fault. …”
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  12. 12

    Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

    Published 2020
    “…In this research, a hybrid electricity price forecasting methodology is proposed using two-stage feature selection method and optimization using adaptive neuro-fuzzy inference system (ANFIS) technique as a forecasting engine. …”
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  13. 13

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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  14. 14

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…The third proposed segmentation algorithm involves two pipelines for feature extraction: split & merge methods and Contextual Encoding Network (EncNet) with an attention mechanism. …”
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  15. 15

    GA Based Feature Recognition of Step File for CAD/CAM Integration by Syafnil, Alfais Admiral

    Published 2009
    “…A GA model is proposed for optimizing the coordinates which is used for feature recognition. …”
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  16. 16

    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

    Published 2022
    “…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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  17. 17

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The second stage (i.e. feature extraction stage) extracts the features based on ROI using the grey-level co- occurrence matrix (GLCM). …”
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  18. 18

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…The method employs the intelligence of deep CNN (DenseNet Model) to extract the features after training the model on a wide range of food categories and images. …”
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  19. 19

    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 algorithms are developed using MATLABâ„¢ software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsâ„¢, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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    Conference or Workshop Item
  20. 20

    Noise eliminated ensemble empirical mode decomposition scalogram analysis for rotating machinery fault diagnosis by Atik, Faysal

    Published 2022
    “…Artificial intelligence can be applied in fault feature extraction and classification. It is crucial to use an effective feature extraction method to obtain most of the fault information and a robust classifier to classify those features. …”
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