Search Results - (( model estimation method algorithm ) OR ( program implementation using algorithm ))
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Differential equation fault location algorithm with harmonic effects in power system
Published 2023“…In this study, several filters were tested to obtain the lowest fault location error to reduce the effect of harmonic components on the developed fault location algorithm. The network model is simulated using the alternate transients program (ATP)Draw simulation program. …”
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2
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The proposed method uses a rank accuracy estimation model to decide the rank-1 value to be applied for the decomposition. …”
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3
Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…Robust estimators in this case are reliable and efficient in administering outlying data, where they perform credibly enough to sample from popular statistical methods which are not gravely impacted by small departures from assumptions of the model (Rusiecki, 2012). …”
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4
QUANTIFYING CRITICAL PARAMETER IN DISEASE TRANSMISSION
Published 2015“…For numerical method, R programming algorithms were implemented to estimate the parameter faster and easier. …”
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Final Year Project Report / IMRAD -
5
Case driven TLC model checker analysis in energy scenario
Published 2023“…To foster the functional safety of corresponding program-algorithmic solutions, the model checking techniques and related tools are applied to the formal specifications of named solutions. …”
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6
Design And Development Of Gas Argon Purging System
Published 2006“…A method is proposed to estimate the accuracy of the system by implementing PI algorithm. …”
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Monograph -
7
Speed control of separately excited dc motor using artificial intelligent approach
Published 2013“…The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. …”
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Thesis -
8
Using genetic algorithms to optimise land use suitability
Published 2012“…The Erosion Potential Method (EPM) used in erosion estimation and sediment yield of the study. …”
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9
Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection
Published 2019“…The FBTS integrated with automated edge-preserving regularization algorithm is implemented in C++ programming language executed in parallel computing. …”
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10
Deep Reinforcement Learning For Control
Published 2021“…To generate the visual simulation in the simulator, the Python programming language is employed. The improved algorithm will help encourage the real-world implementation of DRL in many autonomous driving applications.…”
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Monograph -
11
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
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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12
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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Enhancing navigation accuracy of Turtlebot3 Burger mobile robot
Published 2024“…To address this challenge, the Kalman Filter algorithm is implemented in this robot, as it is widely used for mobile robot navigation and system integration. …”
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15
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…The proposed framework has been implemented in the hypothetical restructured power market using the IEEE Reliability Test System. …”
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17
Prioritizing CD4 count monitoring in response to ART in resource-constrained settings: a retrospective application of prediction-based classification
Published 2012“…Methods and Findings: Using a prospective cohort of HIV-infected patients (n = 1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. …”
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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Flood damage cost prediction using random forest / Ainul Najwa Azahari and Norlina Mohd Sabri
Published 2024“…This project was implemented using the Python programming language. The data were collected from the annual flood report provided by the JPS Negeri Terengganu. …”
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