Search Results - (( model evaluation index algorithm ) OR ( parameters estimation based algorithm ))
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Three case studies with lateral flow were considered for this study, including the Wilson flood, Karahan flood, and Myanmar flood. Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. …”
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Properties of selected garma models and their estimation procedures
Published 2012“…Evaluation of the performance of two estimators based on the Hannan-Rissanen Algorithm Estimator (HRA) and the Whittle's Estimator (WE) through a series of simulation studies have been conducted in this thesis. …”
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A Hydrologic Model for Studying the Climate Change Impact on Evapotranspiration and Water Yield in a Humid Tropical Watershed
Published 1998“…A distributed parameter modelling approach was used whereby a watershed was subdivided into relatively homogeneous ground response units (GRUs) to provide distributed parameter capabilities. …”
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Bayesian logistic regression model on risk factors of type 2 diabetes mellitus
Published 2016“…Estimates of the coefficients for the variables are obtained via the method of maximum likelihood based on the frequentist point of view. …”
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Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data
Published 2024Proceedings Paper -
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction
Published 2013“…In this regard, genetic algorithm generates different initial conditions of premise parameters to and the best one. …”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…We carefully selected relevant metrics based on existing research and conducted a multicollinearity analysis on each parameter to ensure the model?…”
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Control of an underactuated double-pendulum overhead crane using improved model reference command shaping: Design, simulation and experiment
Published 2024journal::journal article -
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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