Search Results - (( parameter estimation methods algorithm ) OR ( changes adaptation method algorithm ))

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  1. 1

    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 second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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    Thesis
  2. 2

    Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm by Natsheh, Essam Fathi

    Published 2006
    “…In this thesis, we use a fuzzy reasoning algorithm (FRA) as a highly adaptive algorithm to achieve that goal. …”
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    Thesis
  3. 3

    Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

    Published 2008
    “…Both experimental and simulation results obtained from the HMRASC and the position angle estimation algorithms showed superior results compared to other methods presented in the literature.…”
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    Thesis
  4. 4

    Advanced online battery states coestimation using Kalman filter for electric vehicle Applications / Prashant Shrivastava by Prashant , Shrivastava

    Published 2021
    “…In addition to co-estimation of SOC and SOE in the first method, the SOP estimation is performed by using identified Rint battery model parameters using the forgetting factor recursive least square (FFRLS) algorithm. …”
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    Thesis
  5. 5

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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    Thesis
  6. 6

    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 performances of both estimation and control algorithms are illustrated by simulation results. …”
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    Conference or Workshop Item
  7. 7

    Self-tuning control of an electro-hydraulic actuator system by Ghazali, Rozaimi, Md Sam, Yahaya, Rahmat, Mohd Fua'ad, Jusoff, Kamaruzaman, Zulfatman, Mohd Hashim, Abd Wahab Ishari

    Published 2011
    “…The results show the proposed control algorithm can adapt the changes occur in model parameters compared with the fixed controller. …”
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    Article
  8. 8

    Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

    Published 2013
    “…Nevertheless, these methods require huge batch of data for tuning its parameters. …”
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    Thesis
  9. 9

    Optimization of ANFIS with GA and PSO estimating α ratio in driven piles by Moayedi, Hossein, Raftari, Mehdi, Sharifi, Abolhasan, Wan Jusoh, Wan Amizah, A. Rashid, Ahmad Safuan

    Published 2020
    “…This study aimed to optimize Adaptive Neuro-Fuzzy Inferences System (ANFIS) with two optimization algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for the calculation friction capacity ratio (α) in driven shafts. …”
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    Article
  10. 10

    Neural network based adaptive pid controller for shell-and-tube heat exchanger by Othman, Mohamad Hakimi

    Published 2019
    “…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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    Student Project
  11. 11

    Neural network based adaptive pid controller for shell-and-tube heat exchanger: article by Othman, Mohamad Hakimi

    Published 2019
    “…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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    Article
  12. 12

    REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC by ABDELRAHMAN ELAMIN, ABDELRAHMAN ELAMIN

    Published 2011
    “…The feedback channel (FC) has the role to adapt the bit rate to the changing ' statistics between the side infonmation and the frame to be encoded. …”
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    Thesis
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    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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    Thesis
  16. 16

    Pemodelan data indeks komposit Kuala Lumpur menggunakan neurofuzzy by Mohd. Yunos, Zuriahati

    Published 2006
    “…The pre-process methodology includes splitting, scaling, normalization, feature selection, and follows by the Ten-Fold Cross Validation method as a benchmark for estimating the predictive accuracy and effectiveness of splitting and selecting the input data. …”
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    Thesis
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    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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    Article
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    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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    Article