Search Results - (( data selection methods algorithm ) OR ( parameter evaluation method algorithm ))
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1
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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2
Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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3
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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A combinatory algorithm of univariate and multivariate gene selection
Published 2009“…Gene selection is usually based on univariate or multivariate methods. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…However, different clustering algorithms have different parameters that need to be specified. …”
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6
Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…By setting the ML algorithms and their parameter along with using Walk-Forward Analysis (WFA) method, the algorithm design of trading signal was evaluated based on two groups of evaluation indicators, namely directional and performance. …”
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…It utilizes the concept of classical gradient descent method with modification on the gradient selection. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…The methodology used includes data collection, preprocessing, and algorithm implementation with evaluation using crossvalidation techniques. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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12
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Secondly, the modeling method of the proposed PV module is validated by experimental data. …”
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13
Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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14
Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The proposed framework and methods are evaluated using the state-of-the-art datasets from the NASA metric data repository. …”
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15
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…The aim of this work is to develop an improved optimization method for IDS that can be efficient and effective in subset feature selection and parameters optimization. …”
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Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali
Published 2024“…To address relay node selection and data scheduling issues, Energy-Efficient Scheduling (EES) and Energy-Efficient Un-Scheduling (EEUS) methods have been introduced using the Improved Discrete Bat Algorithm (IDBA) along with the Adaptive Warshal Floyd algorithm (AWF). …”
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17
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…System identification is a method to build a model for a dynamic system from the experimental 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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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…Five algorithms were evaluated namely VGG16, VGG19, InceptionV3, DeepLoc and Squeezenet. …”
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