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Mechanics of Composite Materials
Erschienen in: Mechanics of Composite Materials 3/2023

28.06.2023

A Comparative Study of the Estimated Bending Strength of Sandwich Panels by an Artificial Neural Network and an Adaptive Neuro-Fuzzy Inference System

verfasst von: M. Nazerian, B. S. Deghatkar, E. Vatankhah

Erschienen in: Mechanics of Composite Materials | Ausgabe 3/2023

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Abstract

The effects of cattail/poplar straw weight ratio, sandwich panel thickness, and the number of kraft paper layers at the core of sandwich panels on the modulus of rupture (MOR) of the panels were predicted using an artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS). The prediction accuracy of the MOR based on experimental data, in terms of the mean absolute percentage error, was smaller than 1.4 and 1.1%, with coefficients of determination 0.94 and 0.995 for the ANN and ANFIS models, respectively. These models can easily predict the bending strength of lignocellulosic-based sandwich panels with a high precision in the manufacturing process.
Vorheriger Artikel Dynamic Stability of a Composite Sandwich Shell with Longitudinal Ribs and an Internal Cylinder Loaded by an External Pressure and a Time-Varying Axial Force
Nächster Artikel Size-Dependent Thermal Backbone Curves for Nanocomposite Reddy Microbeams Reinforced with Graphene Platelets and Resting on Elastic Foundation

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Metadaten
Titel
A Comparative Study of the Estimated Bending Strength of Sandwich Panels by an Artificial Neural Network and an Adaptive Neuro-Fuzzy Inference System
verfasst von
M. Nazerian
B. S. Deghatkar
E. Vatankhah
Publikationsdatum
28.06.2023
Verlag
Springer US
Erschienen in
Mechanics of Composite Materials / Ausgabe 3/2023
Print ISSN: 0191-5665
Elektronische ISSN: 1573-8922
DOI
https://doi.org/10.1007/s11029-023-10118-6

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