Search Results - (( based constructive method algorithm ) OR ( parameters derivation method algorithm ))
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1
Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…The second part of the study is on the confidence intervals (CI) for the concentration parameter in von Mises distribution. Several methods in constructing the CI for the concentration parameter are proposed including CI based on circular population, CI based on the asymptotic distribution of ˆ , CI based on the distribution of 휃 and 푅 and also CI based on bootstrap-t method. …”
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Thesis -
2
PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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3
Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Moreover, the proposed MSFA based method also can solve the unstable convergence issue in the original smoothed function algorithm (SFA), thus able to provide better convergence accuracy. …”
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Article -
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Comparison of UAV flying height parameter for crack detection applications / Wan Nurdayini Batrisyia Wan Ghazali
Published 2024“…Conventional methods of inspection of constructions are time-consuming, require much labor, and make people stand in hazardous conditions. …”
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Student Project -
5
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…In this study, we propose an alternative method of constructing a confidence interval based from the distribution of the estimated value of error concentration parameter obtained from the Fisher information matrix. …”
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6
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm. …”
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7
Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen
Published 2016“…Parameter estimation with the maximum likelihood estimation via the Expectation-Maximization algorithm is discussed and compared with the conditional least squares method. …”
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8
Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
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Working Paper -
9
Adaptive step size of diagonally implicit block backward differentiation formulas for solving first and second order stiff ordinary differential equations with applications
Published 2020“…In this thesis, new classes of block methods based on backward differentiation formula (BDF) for solving first and second order stiff ordinary differential equations (ODEs) are developed. …”
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10
Modelling and Control of Ankle Foot Orthosis (AFO) for Children Utilising Soft Computing Towards Intelligent Approach
Published 2024“…The PID controllers were tuned automatically by the PSO algorithm based on the same identified models. The performance of both developed controllers was compared and analyzed. …”
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11
An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…Compared to another well-established optimizer, such as particle swarm optimization (PSO), the SKF algorithm is a relatively new optimizer and most importantly, the SKF algorithm has not been applied to parameter tuning of PID controller. …”
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Conference or Workshop Item -
12
An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…The findings suggest that the SKF algorithm has promising potentials to be a good tuning method in PID controller.…”
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Conference or Workshop Item -
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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14
Weighting method for modal parameter based damage detection algorithms
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Article -
15
An Approach to Derive Parametric L-System Using Genetic Algorithm
Published 2009“…The higher level of GA deals with the evolution of symbols and lower level deals with the evolution of numerical parameters. Initial results derived from the approach are very promising, which shows that complicated branching structures can be easily derived by the multilayered architecture of GA. …”
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Book Section -
16
A Hybrid Gini PSO-SVM Feature Selection: An Empirical Study of Population Sizes on Different Classifier
Published 2014“…A performance of anti-spam filter not only depends on the number of features and types of classifier that are used, but it also depends on the other parameter settings. Deriving from previous experiments, we extended our work by investigating the effect of population sizes from our proposed method of feature selection on different learning classifier algorithms using Random Forest, Voting, Decision Tree, Support Vector Machine and Stacking. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…Another problem is estimating the covariance matrix of the parameter estimators, since the existing methods involve derivative of the hazard function of the model’s error terms. …”
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An evolutionary based features construction methods for data summarization approach
Published 2015“…In this work, we empirically compare the predictive accuracies of classification tasks based on the proposed feature construction methods and also the existing feature construction methods. …”
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Research Report -
20
BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Published 2023Article
