Search Results - (( data application based algorithm ) OR ( parameter estimation utilizing algorithm ))

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  1. 1
    Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs

    Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz

    Published 2015
    “…The next stage is to estimate the parameters of the model and finally, the mathematical model is validated. …”
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  2. 2
    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method

    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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  3. 3
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. Under certain assumptions, the OLS estimates are the best linear unbiased estimates. …”
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  4. 4
    Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters

    Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters by Yousri D., Thanikanti S.B., Allam D., Ramachandaramurthy V.K., Eteiba M.B.

    Published 2023
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  5. 5
    Expectation maximization clustering algorithm for user modeling in web usage mining system

    Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

    Published 2009
    “…The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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  6. 6
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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  7. 7
    Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission

    Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission by Ahmad Suki, Che Mohamed Arif

    Published 2011
    “…The new algorithm is capable of producing a high data rate and at the same time a better quantization parameter (QP) stability video sequence. …”
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  8. 8
    A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf.

    A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf. by Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Kabiri, Keivan, Samim-Namin, Kaveh

    Published 2013
    “…Since the aforementioned algorithm has been developed for other types of sensors, an approach using weighted mean value of parameters for SeaWiFS, MERIS, VIIRS, and OCTS sensors were employed to estimate parameter values for QuickBird image. …”
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  9. 9
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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  10. 10
    Properties of selected garma models and their estimation procedures

    Properties of selected garma models and their estimation procedures by Ramiah Pillai, Thulasyammal

    Published 2012
    “…The focus of this study is to investigate the properties specically the variance and autocovariance of the GARMA (p; q; ±1; ±2) models. We also study the estimation of the parameters of these models. Evaluation of the performance of two estimators based on the Hannan-Rissanen Algorithm Estimator (HRA) and the Whittle's Estimator (WE) through a series of simulation studies have been conducted in this thesis. …”
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  11. 11
    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…The Expectation Maximization (EM) was considered to obtain the estimate of the parameters. These estimates were then compared to the Newton-Raphson iteration method. …”
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  12. 12
    Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network

    Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network by Dayang Suhaila, Awang Suhaili

    Published 2006
    “…The back propagation algorithm was adopted for this study. The optimal model for predicting missing data found in this study is the network with the combination of learning rate and the number of neurons in the hidden layer of 0.2 and 60. …”
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  13. 13
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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  14. 14
    Use of AR Block Processing for Estimating the State Variables of Power System

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
    “…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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  15. 15
    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…In addition, the structural parameters of a system can be accurately estimated through the proposed system identification methods for both cases of linear and nonlinear conditions. …”
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  16. 16
    Predicting the popularity of tweets using the theory of point processes.

    Predicting the popularity of tweets using the theory of point processes. by Tan, Wai Hong

    Published 2019
    “…We further propose an inhomogeneous Poisson process model and an estimation method which utilizes internal and external knowledge, based on the times of historical retweets up to the censoring time, and the complete retweet sequences in the training data set respectively. …”
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    UMK Etheses
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  17. 17
    Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian

    Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian by Tey, Siew Kian

    Published 2009
    “…By using real time measurements and historical data base, power system state estimator detects errors in measurements and the data base; and calculates an optimal estimate of the system state vector of the bus voltage magnitudes and angles. …”
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  18. 18
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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  19. 19
    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…To consistently estimate relevant thresholds from the threshold set obtained by the group LASSO, the backward elimination algorithm (BEA) is utilized. …”
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  20. 20
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    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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