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Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…The selected most optimized models were then can be used to classify between clean water and polluted water based on capacitance input.…”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Model structure selection is one of the important steps in a system identification process. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The algorithm searches the solution space by selecting various model structures and evaluating its fitness. …”
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Application of memetic algorithm in modelling discrete-time multivariable dynamics systems
Published 2008“…The results indicate that the proposed algorithm is able to select the model structure of a system successfully. …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…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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Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach
Published 2001“…(Wong et aL 1997) developed fuzzy models for machinability data selection. There are more than 2 x 1029 possible sets of rules for each model. …”
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A clonal selection algorithm model for daily rainfall data prediction
Published 2014“…This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data
Published 2016“…By using a Bivariate extreme model and the slice sampler algorithm, the relationship between the gold and American dollar returns in Malaysian market has been considered.…”
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Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm
Published 2017“…Model structure selection is a problem in system identification which addresses selecting an adequate model i.e. a model that has a good balance between parsimony and accuracy in approximating a dynamic system. …”
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Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
Published 2013“…Several goodness of fit tests are compute for selecting the best model. The application is on the monthly maxima PM10 data for Johor state.…”
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Development of genetic algorithm-based fuzzy rules design for metal cutting data selection
Published 2002“…The authors have developed fuzzy models for machinability data selection (Int. J. Flexible Autom. …”
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