Search Results - (( _ application bee algorithm ) OR ( its application ((need algorithm) OR (means algorithm)) ))
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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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Data clustering using the bees algorithm
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In addition, ANFIS approach is implemented to predict the �436�45D of wind turbine blades for investigation of algorithms performance based on Coefficient Determination (R2) and Root Mean Square Error (RMSE). …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman
Published 2017“…This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This condition impeded the entropy-based heuristic of existing ATM algorithm to develop effective decision boundaries due to its biasness towards the dominant class. …”
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Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…This study explores the application of an artificial bee colony (ABC) to locate partial discharge (PD) in a test tank based on acoustic emission (AE) approach. …”
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Improved tree routing protocol in zigbee networks
Published 2010“…Wireless Sensor Networks (WSNs) is becoming more important in various application areas. Many application scenarios require connectivity between WSN’s nodes to transmit the collected data to a sink node. …”
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Thesis -
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A review of training methods of ANFIS for applications in business and economic
Published 2016“…Other than that, Genetic Algorithm (GA), Firefly Algorithm (FA), Ant Bee Colony (ABC) optimization methods have been employed for effective training of ANFIS networks when solving various problems in the field of business and finance.…”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Genetic algorithm was widely used because of its accuracy and simplicity. …”
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Academic Exercise -
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A review of training methods of ANFIS for applications in business and economics
Published 2016“…Other than that, Genetic Algorithm (GA), Firefly Algorithm (FA), Ant Bee Colony (ABC) optimization methods have been employed for effective training of ANFIS networks when solving various problems in the field of business and finance.…”
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Hybrid Metaheuristic Algorithm for Short Term Load Forecasting
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…As an algorithm, PSO can be applied to solve various function optimisation problems, as the main strength of the algorithm is its fast convergence [14]. …”
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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Final Year Project -
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A Hybrid Approach For Web Search Result Clustering Based On Genetic Algorithm With K-means
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Combined generative adversarial network and fuzzy C-means clustering for multi-class voice disorder detection with an imbalanced dataset
Published 2020“…An automatic diagnosis for voice disorders via machine learning algorithms is desired to reduce the cost and time needed for examination by doctors and speech-language pathologists. …”
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