Bio-inspired optimization algorithms applied to rectenna design

He, Menglong; Wang, Zhao; Leach, Mark; Jiang, Zhenzhen; Lim, Eng Gee

doi:10.1186/s41044-017-0026-4

Cited by 7 publications

(1 citation statement)

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“…Swarm intelligence and optimization techniques have piqued the scientific group's interest in past few decades owing to their remarkable flexibility to cope their technique to complicated situations. These methods are classified as microbially computational models seen in environment because they imitate the aggregated behaviour of people engaging in their surroundings 1) . Many of these processes, including genetic algorithms, differential evolution, ant colony system, & particle swarm optimization, were becoming popular approaches, and they remain at the forefront of major research in the optimal control area 2) .…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Machine Learning Modelling through Adaptive Hybrid Swarm Optimization Techniques for Machine Management

Joshila Grace L.K,

Maneengam,

Pradeep Kumar K V

et al. 2023

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Because of the billions of transactions that take place every day, the volumes of information is always growing. There are a plethora of categorization techniques accessible for extracting usable information from the massive quantity of information obtained. Swarm optimization methods, as well as hybridizations of these techniques, are now playing a significant role in classifications, and they do so in a very efficient way. An introduction and thorough comparison of many swarm optimization techniques & hybrid swarm optimization techniques that have been published in the academic journals are presented in this article. Bio-inspired computing is a fascinating field of machine learning that investigates how natural occurrences may serve as a rich source of motivation for the development of clever processes that can be turned into strong algorithms in the future. In categorization, prediction, & optimization issues, several of these methods have been utilised effectively. In the field of optimization, swarm intelligence techniques are a kind of microbially algorithm that has been proven to be very effective for quite some time. However, in order for these algorithms to function at their peak levels, the starting variables must be adjusted correctly by a skilled user who knows what they're doing. The development and expansion of machine management are aided greatly by the use of efficient machinery and equipment. Different research investigations are engaged in the execution of the study and reviewers have concluded that machine learning technologies are the most effective means of supporting this expansion of the research. In order to better understand machine learning technologies and machine learning algorithms, the majority of implementations are investigated using swarm intelligence optimization techniques. As a result, they may be used as an essential judgement tool in the manufacturing industry.

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Section: Introductionmentioning

confidence: 99%