Search Results - (( parameter estimation method algorithm ) OR ( data combination method algorithm ))

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

“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”

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

“…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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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

“…Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

“…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

“…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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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

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

“…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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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

“…In this paper, an approach termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is basically based on Gravitational Search Algorithm (GSA), is proposed to combine these two parts into a simultaneous solution. …”
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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

“…The applicability of the proposed methods is tested in three simulated data and one experimental data. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

“…For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. …”
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm by Basri Badyalina, Nurkhairany Amyra Mokhtar, Nur Amalina Mat Jan, Muhammad Fadhil Marsani, Mohamad Faizal Ramli, Muhammad Majid, Fatin Farazh Ya'acob

“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…However, proper selection of RFR architecture and hyper-parameters combination remains a key issue to be explored. …”

Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

“…Bayesian techniques for bivariate model have not yet received much attention due to the hitches in dealing with much more parameters. Literature on Bayesian extremes based on MCMC techniques are dealing with either Gibbs sampling method or MH method, or the combination of both methods. …”
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Reference evapotranspiration estimation using adaptive neuro-fuzzy inference system by Karimaldini, Fatemeh

“…In addition, traditional methods that require limited climatic parameters for ETO estimation are not applicable to all climatic conditions. …”
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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.

“…The applicability of the proposed methods is tested in three simulated data and one experimental data. …”
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant by Bunyamin M.A., Yap K.S., Aziz N.L.A.A., Tiong S.K., Wong S.Y., Kamal M.F.

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