Flower Pollination Algorithm for the optimization of stair casting parameter for the preparation of AMC

Adithiyaa, T.; Chandramohan, D.; Sathish, T.

doi:10.1016/j.matpr.2019.07.711

Cited by 91 publications

(9 citation statements)

References 5 publications

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“…e flower pollen algorithm simulates the pollination of flowering plants [41][42][43], which is divided into global pollination and local pollination. is study was inspired by global pollination, which simulates the process by a flying insect carries pollen from one flowering plant over a distance to another.…”

Section: Step Factor Of the Flower Pollen Algorithmmentioning

confidence: 99%

Mutigroup-Based Phasmatodea Population Evolution Algorithm with Mutistrategy for IoT Electric Bus Scheduling

Zhu

Yan

Pan

et al. 2022

Wireless Communications and Mobile Computing

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The Phasmatodea population evolution algorithm (PPE) is a novel metaheuristic algorithm proposed in recent years, which simulates the evolutionary trend of stick insect population. In this article, a multigroup-based Phasmatodea population evolution algorithm with mutistrategy (MPPE) is proposed to further improve the overall performance of PPE. During the initialization period, the stick insect population is divided into multiple groups, and the step factor of the flower pollen algorithm is introduced into the population growth model of no more than half of the groups. This makes the population evolution trend diversified and prevents the algorithm from falling into the local optimal solution to a certain extent. In terms of intergroup communication, two communication strategies are adopted to mutate and replace the inferior particles, respectively, which improves the convergence speed and search ability of the algorithm. In the MPPE performance test, we compared it with PPE, five standard algorithms, and other parallel algorithms in CEC 2013 Benchmark Suite. Finally, this algorithm is applied to the IoT based electric bus scheduling for urban waterlogging situation, and the excellent performance of MPPE is verified comprehensively.

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Section: Step Factor Of the Flower Pollen Algorithmmentioning

confidence: 99%

Mutigroup-Based Phasmatodea Population Evolution Algorithm with Mutistrategy for IoT Electric Bus Scheduling

Zhu

Yan

Pan

et al. 2022

Wireless Communications and Mobile Computing

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“…FPA can be stimulated by the process of flow pollination of flowering plants [23]. FPA can be utilized towards solve optimization problems.…”

Section: Process Of Flower Pollination Algorithmmentioning

confidence: 99%

Dynamic Analysis of AC-DC Microgrid with Aid of Golden Search with Flower Pollination Algorithm

Mythili

Narasimhulu²

2021

Preprint

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In recent years, the power system stability enhancement and power flow analysis are essential task in AC-DC microgrid system. Hence, in this paper, Golden Search-based Flower Pollination Algorithm (GSFPA) to solve the optimal power flow invention in AC-DC microgrid system. In the projected methodology, the objective functions are framed to enable the optimal power flow in microgrid system such as total cost of generation in AC as well as DC systems and cost of active power transmission to DC grid from AC microgrid. The objective functions are related with the constraints such as AC-DC power electronics converters limits, power flows and voltage magnitude limits. Additionally, power loss and voltage deviation of the microgrid system also reduced which enhance the system performance. The proposed methodology is utilized to select optimal control parameters for enabling the stable operation of microgrid system. The proposed methodology is validated by using IEEE 30 bus system which associated with 9-bus DC microgrids and 6-bus DC microgrids. The projected method is applied in MATLAB and performances are analyzed with normal as well as contingency conditions. The projected method is contrasted with the conventional methods such as Flower Pollination Algorithm (FPA), chaos based FPA (CFPA) and Levy Flight based Black Widow Optimization (LF-BWO) respectively.

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“…Bit extra quantity of hardener is taken for the wastage at the same time. Hardener should taken minutely bearing in mind the way that little further quantity of hardener can destroy the compound [17][18][19].…”

Section: Specimen and Experimentalmentioning

confidence: 99%

Mechanical and Material Properties of Areca/ Epoxy Composite

Kumar,

Jeevarathinam

et al. 2019

IJITEE

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The contemporary test targets learning the perfunctory conduct of half breed regular fiber combinations. Tests of a few Areca-Epoxy were made utilizing layup strategy where the assembling of handles was substitute and the weightiness division of polymer % and fiber& network was kept at 90%- 10% , 80% - 20% and 30%-70%.Specimens were cut from the created cover as indicated by the ASTM models for various analyses. For Ductile test and flexural test were cut fit as a fiddle and level bar shape separately.

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Flower Pollination Algorithm for the optimization of stair casting parameter for the preparation of AMC

Cited by 91 publications

References 5 publications

Mutigroup-Based Phasmatodea Population Evolution Algorithm with Mutistrategy for IoT Electric Bus Scheduling

Mutigroup-Based Phasmatodea Population Evolution Algorithm with Mutistrategy for IoT Electric Bus Scheduling

Dynamic Analysis of AC-DC Microgrid with Aid of Golden Search with Flower Pollination Algorithm

Mechanical and Material Properties of Areca/ Epoxy Composite

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