Search Results - (( based simulation model algorithm ) OR ( time estimation methods algorithm ))

Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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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

“…Hence, based on the aforementioned problems, the optimization algorithm methods played an important role in addressing these problems. …”
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Trajectory planning and simulation for 3d printing process by Ng, Chin Yong

“…However, less accurate of estimating printing time for models that have many layers. …”
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Estimation of Response Transfer Functions of Offshore Structures Using the Time-Varying ARX Model by Yazid, Edwar, Liew, M. S., Parman, Setyamartana, Kurian, V.J.

“…The approach is based on time-varying autoregressive with exogenous input (TVARX) model. …”
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Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

“…The performance of the proposed algorithm in accurately estimating the number of exponential signals and their corresponding exponential consfanis for both simulated and real data is investigated in this paper. …”
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Identification of hammerstain model using stochastic perturbation simultaneous approximation by Nurriyah, Mohd Noor

“…A numerical example is given to illustrate that the SPSA based algorithms can give accurate parameter estimate of the Hammerstein models with high probability through detailed simulation.…”
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Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

“…Besides, algorithm based method has been widely used to forecast future result in various field for example art, biology, marketing including engineering. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm by Lim, Song Wei

“…A Python computational model that uses genetic algorithms will be developed to estimate the optimal tilt angle and orientation angle as well as the solar power received for the solar sites. …”
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A graphical user interface application for continuous-time identification of dynamical system by Rahmat, Mohd. Fua'ad, Omar, Rosli, Jamaluddin, Hishamuddin

“…This paper introduces a Graphical User Interface (GUI) application in system identification and parameter estimation of dynamic systems using Generalized Poisson Moment Functionals (GPMF) method based on Instrumental Variable (IV) algorithm. The GUI based on MATLAB consists of data preprocessing, parameter estimation, model validation and model simulation. …”
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Optimal input shaping for vibration control of a flexible manipulator using genetic algorithm by Rudrusamy, Bhuvendra

“…This thesis presents optimization of input shaping technique for vibration control of a flexible robot manipulator using genetic algorithms (GA). This simulation work is designed in Matlab based environment with sampling frequency of 2 kHz and implemented on a Pentium 4 2.66 GHz processor and the responses are presented in time and frequency domains. …”
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Estimating Marine CSEM Responses Using Gaussian Process Regression Based on Synthetic Models by Mohd Aris, M.N., Daud, H., Mohd Noh, K.A., Dass, S.C.

“…Current practice for processing marine CSEM responses utilizes meshes-based algorithms. The ad hoc algorithms require high computational time to solve the integrals and linear equations. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”

Railway wheelset parameter estimation using signals from lateral velocity sensor by Selamat, H., Alimin, A. J., Sam, Y.M.

“…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter by Yazid, E., Liew, M.S., Parman, S., Kurian, V.J.

“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…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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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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Time Varying Channel Estimation for Amplify-and-Forward Relay Network by Rabbi, M. F., Yusnita, Rahayu, Kamarul Hawari, Ghazali

“…Then a Least Square (LS) and a Linear MMSE (LMMSE) based algorithm is applied to estimate BEM coefficients which are used for channel reconstruction later. …”
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