Search Results - (( java application using algorithm ) OR ( parameter selection model algorithm ))
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses -
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method
Published 2023“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…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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Conference or Workshop Item -
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…Support Vector Machine (SVM) is a present day classification approach originated from statistical approaches.Two main problems that influence the performance of SVM are selecting feature subset and SVM model selection. In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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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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Conference or Workshop Item -
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Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data
Published 2016“…Here, we have exhaustedly studied all the possible priors for location and scale parameters and come out with a few suggestions for the prior selection of a Gumbel model. …”
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Thesis -
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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review
Published 2024“…Overall, this comprehensive review provides valuable insights into the importance of algorithm development, optimization, and parameter selection in crop water modelling, specifically focusing on crop factors, soil factors, and weather factors.…”
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Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli
Published 2021“…For HDL-C, the SCG algorithm with a testing accuracy of 76.7%, sensitivity of 95.5% and specificity of 25.0% was selected as best performing models to indicate the relationship of the bioelectrical parameters and the lipid profile parameters.…”
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Thesis -
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…The validation test-through correlation analysis was used to validate the model. The model of model order 2 is chosen as the best model as it has fulfilled the criteria involved in selecting the accurate model. …”
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Model selection approaches of water quality index data
Published 2016“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…Previous studies usually concentrate on the forecasting stock index or selecting a few stocks with restricted features. Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”
thesis::master thesis -
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Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model
Published 2001“…Three methods for choosing the initial parameter of the fuzzy model are considered, namely the on-line, the off-line, and the random initial parameters. …”
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Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm
Published 2013“…The selection of optimal cutting parameters has always presented a critical quality concern in the micromachining process. …”
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Thesis -
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