Results 161 to 170 of about 2,020,079 (204)
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Monarch butterfly optimization
Neural Computing and Applications, 2015In nature, the eastern North American monarch population is known for its southward migration during the late summer/autumn from the northern USA and southern Canada to Mexico, covering thousands of miles. By simplifying and idealizing the migration of monarch butterflies, a new kind of nature-inspired metaheuristic algorithm, called monarch butterfly ...
Gai-Ge Wang, Suash Deb, Zhihua Cui
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An image segmentation method based on improved Monarch Butterfly Optimization
Iran Journal of Computer Science, 2021Image segmentation refers to splitting an image into non-identical and significant parts for more accurate classification or interpretation. In general, multi-level thresholding methods are used to find the best threshold levels for image segmentation. Although researchers have proposed different techniques to find the optimal thresholds, this issue is
Babak Masoudi, Hadi S. Aghdasi
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Monarch butterfly optimization algorithm for computed tomography image segmentation
Multimedia Tools and Applications, 2021In the medical field, image segmentation provides important information for surgical planning and registration, and thus demands accurate segmentation. In order to improve the effectiveness and the threshold accuracy of segmentation, researchers have tended to use a metaheuristic algorithm as the operational algorithm to achieve better exploitation and
Osama M. Dorgham +5 more
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Harmony-based monarch butterfly optimization algorithm
2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 2015Monarch butterfly optimization (MBO) is a new metaheuristic algorithm mimics the migration of butterflies from northern USA to Mexico. In MBO, there are mainly two processes. In the first process, the algorithm emulates how some of the butterflies move from the current position to the new position by the migration operator.
Mohamed Ghetas +2 more
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International Journal of Hydrogen Energy, 2020 In this paper, a circuit-based model of proton exchange membrane fuel cell (PEMFC) is developed for optimal selection of the model parameters. The optimization is based on using an improved version of Monarch Butterfly Optimization (IMBO) algorithm for
Abdullah Yildizbasi +2 more
exaly +1 more source
A new monarch butterfly optimization with an improved crossover operator
Operational Research, 2016Recently, by examining and simulating the migration behavior of monarch butterflies in nature, Wang et al. proposed a new swarm intelligence-based metaheuristic algorithm, called monarch butterfly optimization (MBO), for addressing various global optimization tasks.
Gai-Ge Wang +3 more
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The monarch butterfly optimization algorithm for solving feature selection problems
Neural Computing and Applications, 2020Feature selection (FS) is considered to be a hard optimization problem in data mining and some artificial intelligence fields. It is a process where rather than studying all of the features of a whole dataset, some associated features of a problem are selected, the aim of which is to increase classification accuracy and reduce computational time.
Mohammed Alweshah +5 more
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A Multi-objective Optimization Algorithm Based on Monarch Butterfly Optimization
2019Swarm intelligence optimization algorithm is an important technology that solves the complex optimization problem by simulating the behavior of biological groups in nature. Monarch butterfly optimization (MBO) algorithm is such a swarm intelligence algorithm that simulates the migration behavior of the monarch butterflies in nature.
Rui Hu +3 more
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A Discrete Monarch Butterfly Optimization for Chinese TSP Problem
2016Recently, Wang et al. proposed a new kind of metaheuristic algorithm, called Monarch Butterfly Optimization (MBO), for global continuous optimization tasks. It has experimentally proven that it has better performance than some other heuristic search strategies.
Gai-Ge Wang +3 more
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Modified Monarch Butterfly Optimization Algorithm for RFID Network Planning
2018 6th International Conference on Multimedia Computing and Systems (ICMCS), 2018This paper presents an implementation of the modified monarch butterfly optimization algorithm for solving the RFID network planning problem. This problem is one of the most studied challenges in the RFID domain, and was not tackled with the monarch butterfly optimization metaheuristic before.
Marko Beko +2 more
exaly +2 more sources