PERFORMANCE COMPARISON OF ANFIS, ANN, SVR, CART AND MLR TECHNIQUES FOR GEOMETRY OPTIMIZATION OF CARBON NANOTUBES USING CASTEP

Abstract

Density Functional Theory (DFT) calculations used in the Carbon Nanotubes (CNT) design take a very long time even in the simulation environment as it is well known in literature. In this study, calculation time of DFT for geometry optimization of CNT is reduced from days to minutes using seven artificial intelligence-based and one statistical-based methods and the results are compared. The best results are achieved from ANFIS and ANN based models and these models can be used instead of CNT simulation software with high accuracy. 

Keywords

• Geometry Optimization
• Cnt
• Dft
• Artificial Intelligence

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