Search Results - (( simulation estimation method algorithm ) OR ( variable evaluation method algorithm ))
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1
Comparing three methods of handling multicollinearity using simulation approach
Published 2006“…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases was less than the number of observations were used. …”
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Thesis -
2
Neighbour-based on-demand routing algorithms for mobile ad hoc networks
Published 2017“…All the three proposed algorithms are evaluated using discrete event simulation, in particular Network Simulator tool (NS2), and compared with the latest routing algorithm (NCPR ) and fundamental algorithm (AODV) using five performance metrics. …”
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3
Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…Simulation and empirical studies are conducted in validating the performance of the two algorithms. …”
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4
Hybrid optimization approach to estimate random demand
Published 2012“…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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Conference or Workshop Item -
5
A Comparative Study On Some Methods For Handling Multicollinearity Problems
Published 2006“…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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6
A comparative study on some methods for handling multicollinearity problems
Published 2006“…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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7
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Various experiments were carried out to assess and test components of IFS algorithm. The first test was designed to evaluate the formulated IFS Selection Criterion Strategy (MI estimator) by comparing it with six different MI estimator benchmarks. …”
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9
Robust Kernel Density Function Estimation
Published 2010“…To evaluate the efficiency of the proposed method, comprehensive contaminated models are designed and simulated. …”
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10
Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission
Published 2011“…It is designed based on the Shaped VBR (SVBR) algorithm and was implemented in the Network Simulator 2 (ns-2). …”
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11
Potential Evapotranspiration Estimation Methods for Water Balance Analysis Using SWAT: A Case Study of Kelantan River Basin, Kelantan
Published 2023“…29.3% and ?28.5%. The P-M method tends to estimate lower PET than HG and P-T with yearly simulated was accounted for approximately 66%, 70%, and 71% respectively of annual precipitation. …”
Book Chapter -
12
Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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13
Neural network based adaptive pid controller for shell-and-tube heat exchanger
Published 2019“…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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Student Project -
14
Neural network based adaptive pid controller for shell-and-tube heat exchanger: article
Published 2019“…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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15
Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…The nonlinear solutions coupled with some improved robust methods such as Diagnostic Robust Generalized Potential (DRGP) method and GM6-Estimator are also introduced. …”
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16
Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The speed for the sensorless vector control and closed loop V/F controllers is evaluated through the model reference adaptive control estimator. …”
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17
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The simulation results indicate that the proposed method is suitable to detect a single outlier. …”
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18
Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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19
New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique
Published 2016“…These 6 algorithms are divided into 3 main methods namely Method A, Method B, and Method C depending on their search patterns and strategies. …”
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20
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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