Search Results - (( (variable OR variables) selection _ algorithm ) OR ( java application optimized algorithm ))
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1
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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2
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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3
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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4
Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025Subjects:Conference paper -
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
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6
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The significance of the selected input variable vectors is studied to analyze their effects on the prediction process. …”
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7
Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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8
Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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9
Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…To overcome the instability selection problem, a stability selection approach is put forward to enhance the performance of single-split variable selection method. …”
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10
Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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11
Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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12
Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm
Published 2023“…This study proposes a new wavelength selection method, interval flower pollination algorithm (iFPA), for spectral variable selection in the partial least squares regression (PLSR) model. …”
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13
Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…The penalized regularization methods are statistical techniques used to regularize and select the necessary predictor variables that have substantial effects on the response variable. …”
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14
SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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15
Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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16
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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17
Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…Among the others, the selection of most influential input variables has a critical effect on the forecast results. …”
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18
Variable order variable stepsize algorithm for solving nonlinear Duffing oscillator
Published 2017“…By selecting the appropriate restrictions, the VOS algorithm provides a cost efficient computational code without affecting its accuracy. …”
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Development of genetic algorithm for optimization of yield models in oil palm production
Published 2018“…This research concludes that the GA method is a user-friendly variable selection tool with excellent results because it can choose variables correctly.…”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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