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

Authors : Mehmet ACI, Çiğdem İnan ACI, Mutlu AVCI

Pages : 119-124

Doi:10.31127/tuje.408976

View : 57 | Download : 14

Publication Date : 2018-09-01

Article Type : Research Paper

Abstract :Density Functional Theory insert ignore into journalissuearticles values(DFT); calculations used in the Carbon Nanotubes insert ignore into journalissuearticles values(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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