Search Results - (( parameter optimization mead algorithm ) OR ( variable learning module algorithm ))

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  1. 1
    Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia

    Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

    Published 2023
    “…Nelder-Mead outperforms the other optimization algorithm with the least error. …”
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  2. 2
    Single and Multiple variables control using Tree Physiology Optimization

    Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

    Published 2017
    “…In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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  3. 3
    Modelling transmission dynamics of covid-19 during Pre-vaccination period in Malaysia: a predictive guiseird model using streamlit

    Modelling transmission dynamics of covid-19 during Pre-vaccination period in Malaysia: a predictive guiseird model using streamlit by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

    Published 2023
    “…The mathematical model is solved using Scipy odeint function, which uses Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. The time-varying coefficients of SEIRD model that best fit the real data of COVID-19 cases are obtained using the Nelder-Mead optimization algorithm. …”
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  4. 4
    A deep learning approach for facial detection in targeted billboard advertising / Lau Sian En

    A deep learning approach for facial detection in targeted billboard advertising / Lau Sian En by Lau , Sian En

    Published 2025
    “…This system utilises sophisticated deep learning algorithm using Convolutional Neural Network (CNN) to identify and examine human faces, enabling advertisers to customise their content according to demographic variables including age and gender. …”
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  5. 5
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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  6. 6
    Evaluation of arima and ann stream analytics for air quality monitoring system

    Evaluation of arima and ann stream analytics for air quality monitoring system by Nurmadiha, Osman

    Published 2021
    “…It is observed that the data in MySQL are successfully exported to the R query table based on the similar number of variables between those two tables. The data stored in the query table act as input to the analytics algorithm, which runs in R-server as well. …”
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  7. 7
    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller

    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

    Published 2022
    “…The sensorless ANN-IFOC was modelled, simulated, and tested using MATLAB/Simulink for a 20Hp EV motor based on a small Renault Twizy EV model and triggered by the space-vector pulse-width modulation (SVPWM). The results of the ANN-IFOC hybrid estimator were obtained in four cases, which were 1) constant high and low speeds, 2) constant speed against parameter variation, 3) variable speed, and 4) variable load torque disturbances. …”
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  8. 8
    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing

    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

    Published 2014
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  9. 9
    An efficient and lightweight detection method for stranded elastic needle defects in complex industrial environments using VEE-YOLO

    An efficient and lightweight detection method for stranded elastic needle defects in complex industrial environments using VEE-YOLO by Qiaoqiao, Xiong, Qipeng, Chen, Saihong, Tang, Yiting, Li

    Published 2025
    “…The algorithm’s performance was evaluated using a dataset to detect stranded elastic needle defects. …”
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