Search Results - (( parallel optimization bees algorithm ) OR ( pattern classification learning algorithm ))
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. …”
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Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
Published 2024“…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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Multilevel learning in Kohonen SOM network for classification problems
Published 2006“…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. …”
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The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition
Published 2016“…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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Machine Learning Approach Regarding The Classification And Prediction Of Dog Sounds: A Case Study Of South Indian Breeds
Published 2024journal::journal article -
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Design of a pattern classification system using extreme learning machine
Published 2024text::Final Year Project -
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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Design of a pattern classification system using extreme learning machine
Published 2023text::Final Year Project -
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Comparative study of machine learning algorithms in data classification
Published 2025“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…Nowadays, there are increasingly numbers of studies on seeking ways to mine Twitter for sentiment analysis. Machine learning approach such as immune system based learning methods is an alternative way for sentiment classification.This method is centered on prominent immunological theory as computation mechanisms that emulate processes in biological immune system in achieving higher probability for pattern recognition. …”
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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