Search Results - (( data estimation learning algorithm ) OR ( parallel optimization modified algorithm ))

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    Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem by Uvaraja, Vikneswary, Lai, Soon Lee, Abd Rahmin, Nor Aliza, Hsin, Vonn Seow

    Published 2020
    “…A set covering model was then adopted to minimize the number of buses and drivers simultaneously. A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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    Article
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    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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    Monograph
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    Review of the grey wolf optimization algorithm: variants and applications by Liu, Yunyun, As’arry, Azizan, Hassan, Mohd Khair, Hairuddin, Abdul Aziz

    Published 2023
    “…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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    Article
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    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

    Published 2013
    “…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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    Conference or Workshop Item
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    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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    Thesis
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    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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    Article
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    Review of the grey wolf optimization algorithm: variants and applications by Liu, Yunyun, As’arry, Azizan, Hassan, Mohd Khair, Hairuddin, Abdul Aziz, Mohamad, Hesham

    Published 2024
    “…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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    Article
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    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
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    Conference or Workshop Item
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    Development of a real-time clutch transition strategy for a parallel hybrid electric vehicle by Vu, Trieu Minh

    Published 2011
    “…Model predictive control (MPC) has been used for this model and tested with different control horizons and weighting factors to verify the ability of MPC to control the vehicle speeds for the clutch engagement. Some modified MPC algorithms with softened constraints and with output regions have been also studied to improve the robustness and the ability of this controller. …”
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    Citation Index Journal
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    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…Besides, Extended Kalman Filter (EKF) algorithm was selected in this project as an algorithm for offline estimation data purposes. …”
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    Student Project
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    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…The crucial part about MLP is the learning or training process in which the weights are tuned on the presence of input data to produce a reliable and accurate estimation. …”
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    Thesis
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    Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

    Published 2023
    “…Battery management systems; Charging (batteries); Data handling; Decision trees; Digital storage; Electric vehicles; Learning algorithms; Lithium-ion batteries; Machine learning; Differential search algorithm; Electric vehicle batteries; Lithium ions; Lithiumion battery; Random forest regression; Random forests; Regression algorithms; Search Algorithms; State-of-charge estimation; States of charges; Regression analysis…”
    Conference Paper
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    OPTIMIZATION OF TWO FISH ENCRYPTION ALGORITHM ON FPGA by DORE RAJA, ANAND A RAJA

    Published 2004
    “…For this project, 2 different optimized designs were implemented. The first design (Design I) was implemented with minimum hardware resources usage, using a single F -Function (modified) and was optimized with reasonable latency, throughput and throughput per gate. …”
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    Final Year Project
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