Search Results - regression ((ant algorithm) OR (((bat algorithm) OR (based algorithm))))
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…SVR however is inferior in accuracy and thus this paper discusses the usage of an optimized SVR with Evolved Bat Algorithm (EBA) to handle the missing value accurately with high execution time. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…Therefore, it is still necessary to develop the model for the discharge-sediment relationship. New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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A novel prediction of the PV system output current based on integration of optimized hyperparameters of multi-layer neural networks and polynomial regression models
Published 2025“…The experimental results demonstrated that the proposed IMGO algorithm is very effective in addressing complex problems with high accuracy, capability, and speedy convergence. …”
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The Integration of Nature-Inspired Algorithms with Least Square Support Vector Regression Models: Application to Modeling River Dissolved Oxygen Concentration
Published 2018“…The current study investigates an improved version of Least Square Support Vector Machines integrated with a Bat Algorithm (LSSVM-BA) for modeling the dissolved oxygen (DO) concentration in rivers. …”
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Enhanced Taguchi�s T-method using angle modulated Bat algorithm for prediction
Published 2023“…In response to this issue, this paper proposed an angle modulated Bat algorithm to be integrated with the T-method in optimizing the prediction model. …”
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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A survey on improvement of Mahalanobis Taguchi system and its application
Published 2024Subjects:Article -
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TOPSIS-based Regression Algorithms Evaluation
Published 2022“…The alternative judgment identified positive and negative ideal alternatives in the alternative space. The compared regression alternatives were scored and ranked based on their distance from these alternatives. …”
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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…Design-based regression testing approaches have been proposed to address changes at higher levels of abstraction, these approaches may not detect changes in the method body and several of the code based addresses procedural programs. …”
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Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Regression test case selection & prioritization using dependence graph and genetic algorithm
Published 2014“…Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. …”
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