Multi-Objective Optimization of Laminated Functionally Graded Carbon Nanotube-Reinforced Composite Plates Using Deep Feedforward Neural Networks-NSGAII Algorithm

DOI10.1142/S0219876221500651OpenAlexW3208053422MaRDI QIDQ5865926

Tam T. Truong, Unnamed Author, Trung Nguyen-Thoi

Publication date: 10 June 2022

Published in: International Journal of Computational Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0219876221500651

zbMATH Keywords

multi-objective optimizationdeep feedforward neural networklaminated functionally graded carbon nanotube-reinforced composite quadrilateral platesnondominated sorting genetic algorithm II

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Operations research, mathematical programming (90-XX)

Related Items (3)

Nonlinear active control of thermally induced pyro-coupled vibrations in porous-agglomerated CNT core sandwich plate with magneto-piezo-elastic facings ⋮ Multiscale Modeling of Metal-Ceramic Spatially Tailored Materials via Gaussian Process Regression and Peridynamics ⋮ Optimization Design of Laminated Functionally Carbon Nanotube-Reinforced Composite Plates Using Deep Neural Networks and Differential Evolution

Uses Software

• GDE3
• AdaGrad
• Adam
• ADADELTA

Cites Work

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