Search Results - (( web application bee algorithm ) OR ( _ ((application ant) OR (application a)) algorithm ))*
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Furthermore, CloudSim simulator will be used to evaluate the performance of this algorithm. The result of the algorithm performance will be appeared in web application system. …”
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Academic Exercise -
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Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony
Published 2022“…In this project, a comparative evaluation of selected algorithms is done to ascertain their applicability, practicality, and adaptability in a cloud scenario. …”
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Academic Exercise -
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Objects tracking from natural features in mobile augmented reality
Published 2013“…The pose matrix from extracted features was calculated by Homography. The adapted algorithm was tested in a mobile AR-prototype application using iPhone. …”
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Ant colony optimization in dynamic environments
Published 2010“…The first objective of this study is to identify which ant algorithm performs the best under a dynamic environment. …”
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Thesis -
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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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An Enhanced Ant Colony Optimisation Algorithm with the Hellinger Distance for Shariah-Compliant Securities Companies Bankruptcy Prediction
Published 2024“…This study addresses the challenge of applying ant colony optimisation algorithms to imbalanced datasets, focusing on a bankruptcy dataset. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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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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AntNet: a robust routing algorithm for data networks
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DACS3:Embedding Individual Ant Behavior in Ant Colony System
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Ant colony optimization for rule induction with simulated annealing for terms selection
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Ant colony algorithm for job scheduling in grid computing
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