Search Results - (( evolution estimation method algorithm ) OR ( learning classification problem algorithm ))
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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4
Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
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Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…This paper presents parameters estimation techniques for coupled industrial tanks using the mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) method. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. …”
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9
Classification model for water quality using machine learning techniques
Published 2015“…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…The successful work on hybridization of ACO and SA algorithms has led to the improved learning ability of ACO for classification. …”
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12
Differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…This paper looks at the feasibility of using the differential evolution algorithm to estimate the linear frequency modulation received signal parameters for radar signal denoising. …”
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Conference or Workshop Item -
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
Conference Paper -
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A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification
Published 2006“…The purpose of this project is to study the performance, leaning time and, output of Levenberg-Marquardt (LM) intelligent system and Bayesian Regularization (BR) intelligent system through a classification problem. These studies will help in choosing the right training algorithm for classification problem involved. …”
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Monograph -
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Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…One of the most powerful machine learning methods to handle classification problems is the decision tree. …”
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