Particle Swarm Algorithm
Mostrando 1-12 de 47 artigos, teses e dissertações.
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1. Efficient Low-Complexity Optimized Channel Estimating Methods for OFDM-Based Low-Voltage Broadband Power Line Communication Systems
Abstract Broadband Power Line Communication (BB-PLC) technology enables data transmission for smart grid applications. Nevertheless, channel equalizers are required in the receiver to estimate and compensate for the nonlinear time-variant impulse response and noise interference effects introduced by the BB-PLC channel. In this paper, we append the Particle S
Journal of Microwaves, Optoelectronics and Electromagnetic Applications. Publicado em: 2022
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2. Characterization of Otto Chips by Particle Swarm Optimization
Abstract Recently a surface plasmon resonance (SPR) optical sensor, based on the Otto configuration — the Otto chip — has been developed. One essential step in the quality control of the fabrication process is characterization of the active region of several devices in a batch. Characterization is done by measuring the angular spectrum of the optical re
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2021-03
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3. Optimal pressure management in water distribution networks through district metered area creation based on machine learning
RESUMO A gestão integrada dos sistemas de abastecimento de água com o uso eficiente dos recursos requer a otimização das operações. O agrupamento das redes de abastecimento de água em pequenas unidades, chamadas de distritos de medição (DMAs), é uma estratégia que permite o desenvolvimento de regras operacionais específicas, responsáveis por mel
RBRH. Publicado em: 26/09/2019
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4. Synthesis of New Reconfigurable Limited Size FSS Structures Using an Improved Hybrid Particle Swarm Optimization
Abstract This paper describes a new design methodology for reconfigurable printed circuits with limited size, using an improved hybrid particle swarm optimization (HPSO) algorithm, reducing the search space by the definition of negative zones (NZ), regions where the swarm of particles should not travel. The proposed design methodology (HPSO-NZ) is used in th
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 19/06/2019
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5. Two-Level Allocation for H-CRAN Architecture Based in Offloading
Abstract The accelerated data and apps growth represents significant challenges to the next generation of mobile networks. Amongst them, it is highlighted the necessity for a co-existence of new and old patterns during the transition of architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 19/06/2019
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6. A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
Abstract: In this paper, we introduce a new three-parameter distribution by compounding the Nadarajah-Haghighi and geometric distributions, which can be interpreted as a truncated Marshall-Olkin extended Weibull. The compounding procedure is based on the work by Marshall and Olkin 1997. We prove that the new distribution can be obtained as a compound model w
An. Acad. Bras. Ciênc.. Publicado em: 08/04/2019
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7. A Model Updating Method for Plate Elements Using Particle Swarm Optimization (PSO), Modeling the Boundary Flexibility, Including Uncertainties on Material and Dimensional Properties
Abstract It is a well-known fact that, in a real engineering situation, fixtures are not ideally stiff, so numerical simulations using them are unlikely to present results that are consistent with the experimental ones. The present paper intends to describe a model updating methodology inserting translational and rotational springs in order to better represe
Lat. Am. j. solids struct.. Publicado em: 22/10/2018
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8. Automatic Identification of Cigarette Brand Using Near-Infrared Spectroscopy and Sparse Representation Classification Algorithm
A cigarette brand automatic classification method using near-infrared (NIR) spectroscopy and sparse representation classification (SRC) algorithm is put forward by the paper. Comparing with the traditional methods, it is more robust to redundancy because it uses non-negative least squares (NNLS) sparse coding instead of principal component analysis (PCA) for
J. Braz. Chem. Soc.. Publicado em: 2018-07
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9. Power Allocation in PON-OCDMA with Improved Chaos Particle Swarm Optimization
Abstract In this work, it is investigated an improved chaos particle swarm optimization (IC-PSO) scheme to refine the quality of the algorithm solutions regarding to solve the optimal power allocation in next generation passive optical networks (NG-PON)s. The proposed IC-PSO scheme utilizes the Beta distribution instead of uniform distribution of the traditi
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2018-06
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10. Design of Microwave Absorbers using Improvised Particle Swarm Optimization Algorithm
Abstract Particle Swarm Optimization (PSO) algorithm has been applied in electromagnetics to design microwave absorbers. Generally, microwave absorbers are used for absorbing the electromagnetic radiation caused due to numerous electronic equipments and is being extensively used in stealth technology. The main aim of this paper is to find and analyze the min
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2018-06
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11. Updating Finite Element Model Using Stochastic Subspace Identification Method and Bees Optimization Algorithm
Abstract This study investigates the application of operational modal analysis along with bees optimization algorithm for updating the finite element model of structures. Bees algorithm applies instinctive behavior of honeybees as they look for nectar of flowers. The parameters that needed to be updated are uncertain parameters such as geometry and material
Lat. Am. j. solids struct.. Publicado em: 26/04/2018
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12. Design of Waveguide Structures Using Improved Neural Networks
Abstract In this paper, an improved neural networks (INN) strategy is proposed to design two waveguide filters (Pseudo-elliptic waveguide filter and Broad-band e-plane filters with improved stop-band). INN is trained by an efficient optimization algorithm called teaching–learning-based optimization (TLBO). To validate the effective of this proposed strateg
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2017-12