A modified electromagnetism-like mechanism (EM) algorithm is proposed to identify structural model parameters using modal data. EM is a heuristic algorithm, which utilizes an attraction-repulsion mechanism to move the sample points towards the optimal solution. In order to improve the performance of original algorithm, a new local search strategy, new charge and force calculation formulas, new particle movement and updating rules are proposed. The test results of benchmark functions show that the modified EM algorithm has better accuracy and faster convergence rate than the original EM algorithm and the particle swarm optimization (PSO) algorithm. In order to investigate the applicability of this approach in parameter identification of structural models, one numerical truss model and one experimental shear-building model are presented as illustrative examples. The identification results show that this approach can achieve remarkable parameter identification even in the case of large noise contamination and few measurements. The modified EM algorithm can also be used to solve other optimization problems.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506646 | PMC |
| http://dx.doi.org/10.3390/s20174789 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Thermophysical properties of graphene reinforced with polymethyl methacrylate nanoparticles for technological applications: a molecular model.
J Mol Model
January 2025
Escuela Superior de Física y Matemáticas, IPN S/N, Edificio 9 de la Unidad Profesional "Adolfo López Mateos", Col. Lindavista, Alc. Gustavo A. Madero, 07738, Mexico City, Mexico.
Context: "Nanostructure of graphene-reinforced with polymethyl methacrylate" (PMMA-G), and vice versa, is investigated using its molecular structure, in the present work. The PMMA-G nanostructure was constructed by bonding PMMA with graphene nanosheet in a sense to get three different configurations. Each configuration consisted of polymeric structures with three degrees of polymerization (such as monomers, dimers, and trimers polymers, respectively).
View Article and Find Full Text PDFMachine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder.
Neuroradiology
January 2025
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Introduction: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI and machine learning techniques to determine whether regional morphological differences could distinguish patients with BD and MDD.
Methods: A total of 123 participants, including BD (n = 31), MDD (n = 48), and healthy controls (HC, n = 44), underwent high-resolution 3D T1-weighted imaging.
Membrane Proteins in Nanodiscs: Methods and Applications.
ChemMedChem
January 2025
Nankai University, State Key Laboratory of Elemento-Organic Chemistry and Department of Chemical Biology, College of Chemistry, 94 Weijin Road, 300071, Tianjin, CHINA.
Membrane proteins, a principal class of drug targets, play indispensable roles in various biological processes and are closely associated with essential life functions. Their study, however, is complicated by their low solubility in aqueous environments and distinctive structural characteristics, necessitating a suitable native-like environment for molecular analysis. Nanodisc technology has revolutionized this field, providing biochemists with a powerful tool to stabilize membrane proteins and significantly enhance their research possibilities.
View Article and Find Full Text PDFA four-level model of political polarization over science: Evidence from 10 European countries.
Public Underst Sci
January 2025
Radboud University, The Netherlands; University of Gothenburg, Sweden; Leibniz University Hannover, Germany.
Citizens' trust in science increasingly depends on their political leaning. Structural equation models on survey data from 10 European countries ( = 5306) demonstrate that this can be captured by a model with four levels of generalization. Voters of populist parties distrust the in general, which indirectly fuels a broad science skepticism.
View Article and Find Full Text PDFTagGen: Diffusion-based generative model for cardiac MR tagging super resolution.
Magn Reson Med
January 2025
Department of Radiology, University of Missouri, Columbia, Missouri, USA.
Purpose: The aim of the work is to develop a cascaded diffusion-based super-resolution model for low-resolution (LR) MR tagging acquisitions, which is integrated with parallel imaging to achieve highly accelerated MR tagging while enhancing the tag grid quality of low-resolution images.
Methods: We introduced TagGen, a diffusion-based conditional generative model that uses low-resolution MR tagging images as guidance to generate corresponding high-resolution tagging images. The model was developed on 50 patients with long-axis-view, high-resolution tagging acquisitions.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!