Search Results - (( based constructive method algorithm ) OR ( parameter estimation model algorithm ))

PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

“…The parameter estimation step is concerned with the estimation of model parameters once the structure is known. …”
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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

“…This study constructs the flow of DNN based method with the K-Means algorithm. …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

“…Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…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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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…The estimation of SL values was achieved using inputs of previous SL and streamflow values provided to the models. …”

A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

“…Within the parameter learning steps, the MCMC algorithm requires to perform state estimation for which the target distribution is constructed by using the Ensemble Kalman filter (EnKF). …”
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Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass by Mohammad, Saleem Ethaib, Omar, Rozita, Mustapa Kamal, Siti Mazlina, Awang Biak, Dayang Radiah, S., Syafiie

“…The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. …”
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The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

“…The research indicates that confidence intervals can yield addition useful information about the estimated parameters. Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

“…The research indicates that confidence intervals can yield addition useful information about the estimated parameters. Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

“…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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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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Predicting the popularity of tweets using the theory of point processes. by Tan, Wai Hong

“…The knowledge is combined using a novel empirical Bayes type approach, where the prior distribution for the model parameter is constructed based on the external knowledge, and the likelihood is calculated based on the internal knowledge. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil

“…In addition, the technique is proposed as a new algorithm for joint channel est imation of the multi-cell model based on reduced rank technique handling the active users in serving cell and the strong interferers from the neighboring cells. …”
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Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen by Khoo, Wooi Chen

“…The iv score functions and information matrix have been derived to measure the asymptotic standard errors and to analyze the variance-covariance relationship among the parameters. 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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Development And Verification Of Traffic Noise Estimation Using Quarry Environmental Modeling (Qem) by Rahim, Nuramizah Abdul

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Accurate localization method combining optimized hybrid neural networks for geomagnetic localization with multi-feature dead reckoning by Yan, Suqing, Luo, Baihui, Sun, Xiyan, Xiao, Jianming, Ji, Yuanfa, Kamarul Hawari, Ghazali

“…However, the existing geomagnetic localization methods suffer from location ambiguity. To address these issues, we propose a fusion localization algorithm based on particle swarm optimization. …”
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Fault Detection and Identification in Quadrotor System (Quadrotor Robot) by Chan, Shi Jing, Pebrianti, Dwi

“…The aim of the research is to construct and design a Fault Detection and Isolation algorithm. …”
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Adaptive GRNN for the modelling of dynamic plants by Yusof, Rubiyah, Khalid, Marzuki, Teo, Lian Seng

“…The results show that the proposed methodology is computationally efficient and exhibits several attractive features such as fast learning, flexible network sizing and good robustness, which are suitable for the construction of estimators or predictors for many model-based adaptive control strategies.…”
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Proving the efficiency of alternative linear regression model based on mean square error (MSE) and average width using aquaculture data by Awang Nawi, Mohamad Arif, Wan Ahmad, Wan Muhamad Amir, Mohd Ibrahim, Mohamad Shafiq, Mamat, Mustafa, Khamis, Mohd Fahdli, Mohamed, Mohamad Afendee

“…The results of the study showed a positive improvement for the estimation of parameters generated through these alternative methods. © BEIESP.…”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…The proposed method leverages room geometry and takes advantage of the multipath signal propagation to construct multiple virtual base station system model. …”
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