Search Results - (( parameter estimation a algorithm ) OR ( variable interactive learning algorithm ))

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  1. 1

    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

    Published 2017
    “…A BRT model was developed using hourly ozone data as a response variable and nitric oxide (NO), Nitrogen Dioxide (NO2) and Nitrogen Dioxide (NOx) and meteorological parameters as explanatory variables. …”
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    Article
  2. 2

    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of two hidden layers with six and seven neurons in the first and second layers, respectively for xylitol stearate and xylitol palmitate and also seven and five neurons in the first and second layers for xylitol caprate, with hyperbolic tangent sigmoid transfer function. …”
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    Thesis
  3. 3

    Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar by Jaafar, Jurina

    Published 2015
    “…It is learned that creating an accurate description of the ground surface is a complex problem, which requires at least site study. …”
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    Thesis
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    Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

    Published 2021
    “…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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    Thesis
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    Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

    Published 2007
    “…Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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    Thesis
  9. 9

    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
  10. 10

    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

    Published 2020
    “…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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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
    “…The estimated parameters from the experiment produce a better model by means of obtaining a reasonable good fit of model prediction to the experimental data. …”
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    Article
  13. 13

    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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    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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    Thesis
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    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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    UMK Etheses
  17. 17

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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    Thesis
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    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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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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    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
    “…Therefore, it is crucial to assess the parameter of chaotic systems. To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
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    Conference or Workshop Item