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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…However, hybrid algorithms are also a fundamental concern in the optimization field, which aim to cumulate the advantages of different algorithms into one algorithm. …”
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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…In this paper, we evaluated and proposed a pairwise strategy named Pairwise Artificial Bee Colony algorithm (PABC). …”
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Ant colony optimization in dynamic environments
Published 2010“…When coupled with a local search technique, a significant improvement can be seen for ACS using the 3-opt local search algorithm. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
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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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Optimizing support vector machine parameters using continuous ant colony optimization
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An Enhanced Ant Colony Optimisation Algorithm with the Hellinger Distance for Shariah-Compliant Securities Companies Bankruptcy Prediction
Published 2024“…The application of ant colony optimization (ACO) algorithms has been limited by their performance on imbalanced datasets, particularly within bankruptcy prediction where the some of bankruptcy cases lead to skewed data distributions. …”
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…Several areas of engineering have adopted the idea that swarms can solve complex problems and some of them are described in [13]. Some of the examples highlighted by [13] are a combinatorial optimisation, routing communications network, as well as solving robotics applications. …”
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A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network
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QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs)
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…However, linear regression does not capture the complex nonlinear relationship between predictor and target variables. It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem
Published 2021“…This paper presents a comparative performance analysis of some metaheuristics such as the African Buffalo Optimization algorithm (ABO), Improved Extremal Optimization (IEO), Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO), Max-Min Ant System (MMAS), Cooperative Genetic Ant System (CGAS), and the heuristic, Randomized Insertion Algorithm (RAI) to solve the asymmetric Travelling Salesman Problem (ATSP). …”
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Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm
Published 2020“…There are many researchers that have been developed a pairwise testing strategy. Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. …”
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