Search Results - (( its applications ant algorithm ) OR ( _ application ((means algorithm) OR (bee algorithm)) ))*
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. …”
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…The main idea in this algorithm is the indirect communication between the ants which is established by the means of pheromones in finding the shortest path between their nest and food [14]. …”
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Optimal design of step – cone pulley problem using the bees algorithm
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Bees algorithm for Forest transportation planning optimization in Malaysia
Published 2021“…Algorithm is widely used in various areas due to its ability to solve classes of problems. …”
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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“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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Data clustering using the bees algorithm
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A near-optimal centroids initialization in K-means algorithm using bees algorithm
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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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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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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Nowadays, many task allocation techniques are used but the most efficient technique needs to be figured out. Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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Academic Exercise -
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Enhancing Solutions Of Capacity Vehicle Routing Problem Based On An Improvement Ant Colony System Algorithm
Published 2019“…It serves an important task in logistics and supply procession administration appropriate toward its wide applications in transport, product delivery, and services. …”
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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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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…In a case where PABC is not at its optimal stage or its best performance, the experiments of a test case are effectively competitive. PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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Multi objective bee colony optimization framework for grid job scheduling
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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Application of LSSVM by ABC in energy commodity price forecasting
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An application of grey wolf optimizer for commodity price forecasting
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