Search Results - (( its application ((amh algorithm) OR (means algorithm)) ) OR ( _ application colony 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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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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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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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…Some of the examples highlighted by [13] are a combinatorial optimisation, routing communications network, as well as solving robotics applications. According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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Hybrid Metaheuristic Algorithm for Short Term Load Forecasting
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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 gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Metaheuristic algorithms have been adapted in various engineering applications due to their efficiencies in solving complex and larger real-life optimization problems. …”
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Optimization of multi-holes drilling toolpath using tiki-taka algorithm
Published 2024“…A computational experiment was conducted on 12 test problems across small, medium, and large problem categories using the TTA, then compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Crayfish Optimization Algorithm (COA), and Geometric Mean Optimizer (GMO). …”
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Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid
Published 2013“…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid
Published 2013“…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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Interacted Multiple Ant Colonies for Search Stagnation Problem
Published 2010“…Ant Colony Optimization (ACO) is a successful application of swarm intelligence. …”
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A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Ant colony algorithm for job scheduling in grid computing
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