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  1. 1
    Improved intrusion detection algorithm based on TLBO and GA algorithms

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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  2. 2
    Three phase fault algorithm in distribution system by using database approach and impedance based method

    Three phase fault algorithm in distribution system by using database approach and impedance based method by Shamsudin, N.H., Latiff, A.A., Abas, N., Mokhlis, Hazlie, Awalin, L.J.

    Published 2012
    “…A three phase fault location algorithm using database and impedance based method is utilized in distribution system to locate fault which may occur in any possible fault sections and to optimize the switching operations to reduce the outage time affected by fault. …”
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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
    Comparative Study of Weighted Product–Dijkstra’s Algorithm and All Possible Path Approach Based on Multiple Criteria and Multi-Dimensions

    Comparative Study of Weighted Product–Dijkstra’s Algorithm and All Possible Path Approach Based on Multiple Criteria and Multi-Dimensions by Ting Kien Hua, Noraini Abdullah

    Published 2020
    “…The focus of this paper was the decision making in choosing the best path within a network based on multiple criteria. Therefore, Weighted ProductDijkstra’s Algorithm (WPDA) was introduced in this paper for optimal path identification with involvement of multiple criteria. …”
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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., 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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  6. 6
    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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  7. 7
    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Mohd Sharif, Zakaria, Mohammad Fadhil, Abas, Fatimah, Dg Jamil, Norhafidzah, Mohd Saad, Addie, Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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  8. 8
    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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  9. 9
    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Zakaria, Mohd Sharif, Abas, Mohammad Fadhil, Dg Jamil, Fatimah, Mohd Saad, Norhafidzah, Hashim, Addie Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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  10. 10
    Assessment of ANN-based auto-reclosing scheme developed on single machine-infinite bus model with IEEE 14-bus system model data

    Assessment of ANN-based auto-reclosing scheme developed on single machine-infinite bus model with IEEE 14-bus system model data by Fitiwi, D. Z., K., S. Rama Rao.

    Published 2009
    “…Consequently, improper reclosing of the line onto a fault is avoided. The fault identification prior to reclosing is based on optimized artificial neural network associated with three different training algorithms. …”
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  11. 11
    Fuzzy modelling using firefly algorithm for phishing detection

    Fuzzy modelling using firefly algorithm for phishing detection by Noor Syahirah, Nordin, Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Shahreen, Kasim, Mohd Saberi, Mohamad, Ashraf Osman, Ibrahim

    Published 2019
    “…To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods provides the Firefly Algorithm (FA). …”
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  12. 12
    Rule Prioritisation Heuristic in Shift Design of Airline Ground Crew

    Rule Prioritisation Heuristic in Shift Design of Airline Ground Crew by Kong Weng, Lee

    Published 2024
    “…Shifts are assigned based on this minimum, employing heuristic and genetic algorithms. …”
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  13. 13
    Modeling the powder compaction process using the finite element method and inverse optimization

    Modeling the powder compaction process using the finite element method and inverse optimization by Hrairi, Meftah, Chtourou, Hedi, Gakwaya, Augustin, Guillot, Michel

    Published 2011
    “…Minimization of the objective function with respect to the material parameters was performed using an in-house optimization software shell built on a modified Levenberg–Marquardt method. …”
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  14. 14
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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  15. 15
    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.

    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models. by Kwad, Ayad Mahmood

    Published 2022
    “…This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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  16. 16
    Direct Adaptive Predictive Control For Wastewater Treatment Plant

    Direct Adaptive Predictive Control For Wastewater Treatment Plant by Shair, Ezreen Farina, Abu Bakar, Norazhar, Mohd Nor, Arfah Syahida, Mohd Azam, Sazuan Nazrah, Mohd Sobran, Nur Maisarah, Zainal Abidin, Amar Faiz

    Published 2012
    “…The adaptive control structure is based on the linear model of the process and combined with numerical algorithm for subspace state space system identification (N4SID). …”
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  17. 17
    Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm

    Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Mohamed Sultan, Mohamed Ali, Mohd Anwar, Zawawi, Mohd Falfazli, Mat Jusof

    Published 2021
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  18. 18
    LSR-YOLO: a lightweight and fast model for retail products detection

    LSR-YOLO: a lightweight and fast model for retail products detection by Zhao, Yawen, Solihin, Mahmud Iwan, Yang, Defu, Cai, Bingyu, Chow, Li Sze, Handayani, Dini Oktarina Dwi, Prabuwono, Anton Satria

    Published 2025
    “…To address the high computational cost and slow detection speed of existing methods, this study proposes LSR-YOLO, a lightweight object detection framework based on YOLOv8n, designed for deployment in robots and intelligent devices. …”
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  19. 19
    Register Transfer Level Implementation Of Pooling - Based Feature Extraction For Finger Vein Identification

    Register Transfer Level Implementation Of Pooling - Based Feature Extraction For Finger Vein Identification by Mohamed Ali, Mohamed Hassan

    Published 2017
    “…The proposed algorithm extracted the local feature information of the finger vein pattern (patches), and used these patches to improve the robustness of the identification. …”
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  20. 20
    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali

    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali by Mohd Razali, Ainaa Farhanah

    Published 2022
    “…In this case, the algorithm of the DIS operator is embedded with the Marker-based Watershed segmentation as the assistance of Marker-based Watershed Segmentation is effective in extracting the individual significant edges features produced by DIS operator. …”
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