Search Results - (( simulation optimization based algorithm ) OR ( features extraction method algorithm ))

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  1. 1
    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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  2. 2
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

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

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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  3. 3
    Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines

    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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  4. 4
    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks

    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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  5. 5
    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks

    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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  6. 6
    Voting algorithms for large scale fault-tolerant systems

    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
    Optimization of neural network using cuckoo search for the classification of diabetes

    Optimization of neural network using cuckoo search for the classification of diabetes by Abubakar, Adamu, Shuib, Liyana, Chiroma, Haruna

    Published 2015
    “…The high dimension of the features in our dataset triggered the study to extract the critical features using principal component analysis. …”
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  8. 8
    Optimal selection of long time acoustic features using GA for the assessment of vocal fold disorders

    Optimal selection of long time acoustic features using GA for the assessment of vocal fold disorders by Sindhu, Ravindran, Neoh, Siew Chin, Dr., Muthusamy, Hariharan, Dr.

    Published 2013
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  9. 9
    Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network

    Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

    Published 2023
    “…This proposed model will be employed in the Improved Reverse Analysis method to extract the relationship between various fields of real-life data sets based on logical representation. …”
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  10. 10
    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system

    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 can provide color and texture information for easy data and feature extraction. Based on literature, stereo algorithm is already being implemented to solve the distance measurement problem. …”
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  11. 11
    Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks

    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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  12. 12
    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin

    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

    Published 2018
    “…The process continues repeatedly to track maximum power depending on the swarmsize of the MPPT algorithm. In order to validate this technique simulation was conducted using MATLAB SIMULINK software in order to observe and identify the output power extracted from the PV panel. …”
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  13. 13
    Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA

    Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA by Javed, E., Faye, I., Malik, A.S., Abdullah, J.M.

    Published 2017
    “…One such problematic artefact is the ballistocardiogram (BCG) artefact. Methods We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. …”
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  14. 14
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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  15. 15
    ECG noise reduction technique using antlion (ALO) algorithm for heart rate monitoring devices

    ECG noise reduction technique using antlion (ALO) algorithm for heart rate monitoring devices by Hii, Kiew Hui

    Published 2020
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  16. 16
    JOINT TORQUEESTIMATION OF sEMG SIGNALS BASED ON INTELLIGENT TECHNIQUES FOR ROBOTIC ASSISTIVE SYSTEM

    JOINT TORQUEESTIMATION OF sEMG SIGNALS BASED ON INTELLIGENT TECHNIQUES FOR ROBOTIC ASSISTIVE SYSTEM by KU ABD RAHIM, KU NURHANIM

    Published 2014
    “…Subsequently, the signal processing that involved processes such as filtering and feature extraction was conducted. Thereafter, the actual joint torque was acquired through dynamic modeling. …”
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  17. 17
    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun

    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

    Published 2021
    “…However, due to some drawbacks, an advanced technique was employed in this study. The proposed method involves using a convolutional neural network (CNN) with a feature extraction ability to learn from the hydrological dataset efficiently. …”
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  18. 18
    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…The wavelet packed decomposition covers the transient and steady state regions of the IM operations with respect to both time and frequency domain. The motor features are extracted through the proposed Discrete Wavelet Transform (DWT) based analysis method, while the wavelet inlet acts as an expert tool to adapt the right controller in accordance with the fault type. …”
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  19. 19
    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model

    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model by Motwake, Abdelwahed, Hassan Abdalla Hashim, Aisha, Obayya, Marwa, Eltahir, Majdy M.

    Published 2023
    “…The ISCSODL-LCC technique utilizes advanced machine learning methods by employing the Squeeze-Excitation ResNet (SE-ResNet) model for feature extraction and the Stacked Gated Recurrent Unit (SGRU) mechanism for land cover classification. …”
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  20. 20
    High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali

    High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali by Mohd Syukri , Ali

    Published 2018
    “…Subsequent algorithm simulation results show that the proposed methods are able to detect and subsequently locate the faults with high accuracies. …”
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