Related references
Note: Only part of the references are listed.Performance evaluation of microbial fuel cell by artificial intelligence methods
A. Garg et al.
EXPERT SYSTEMS WITH APPLICATIONS (2014)
Nanomechanics of single walled carbon nanotube with water interactions under axial tension by using molecular dynamics simulation
V. Vijayaraghavan et al.
COMPUTATIONAL MATERIALS SCIENCE (2013)
Review of empirical modelling techniques for modelling of turning process
Akhil Garg et al.
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL (2013)
Support vector machines models for surface roughness prediction in CNC turning of AISI 304 austenitic stainless steel
Ulas Caydas et al.
JOURNAL OF INTELLIGENT MANUFACTURING (2012)
Nanomechanics of Nonideal Single- and Double-Walled Carbon Nanotubes
C. H. Wong et al.
JOURNAL OF NANOMATERIALS (2012)
The use of artificial neural networks in electrostatic force microscopy
Elena Castellano-Hernandez et al.
NANOSCALE RESEARCH LETTERS (2012)
The Effective Young's Modulus of Carbon Nanotubes in Composites
Libo Deng et al.
ACS APPLIED MATERIALS & INTERFACES (2011)
A molecular dynamics investigation of the torsional responses of defective single-walled carbon nanotubes
Y. Y. Zhang et al.
CARBON (2010)
Elastic properties of imperfect single-walled carbon nanotubes under axial tension
C. H. Wong
COMPUTATIONAL MATERIALS SCIENCE (2010)
Support vector machines improve the accuracy of evaluation for the performance of laparoscopic training tasks
Brian Allen et al.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES (2010)
Nanoscale Materials Modelling Using Neural Networks
Nikolaos Asproulis et al.
JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE (2009)
Buckling of carbon nanotubes at high temperatures
Y. Y. Zhang et al.
NANOTECHNOLOGY (2009)
An inverse problem solution for undetermined electrostatic force microscopy setups using neural networks
G. M. Sacha et al.
NANOTECHNOLOGY (2009)
The inverse of material properties of functionally graded pipes using the dispersion of guided waves and an artificial neural network
Jiangong Yu et al.
NDT & E INTERNATIONAL (2009)
Support vector machines
Alessia Mammone et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS (2009)
Quality classification via Raman identification and SEM analysis of carbon nanotube bundles using artificial neural networks
M. A. Al-Khedher et al.
NANOTECHNOLOGY (2007)
Nanomechanics of single and multiwalled carbon nanotubes
KM Liew et al.
PHYSICAL REVIEW B (2004)
Determination of elastic properties of a film-substrate system by using the neural networks
BQ Xu et al.
APPLIED PHYSICS LETTERS (2004)
Temperature measurement using a gallium-filled carbon nanotube nanothermometer
YH Gao et al.
APPLIED PHYSICS LETTERS (2003)
Comparison of model selection for regression
V Cherkassky et al.
NEURAL COMPUTATION (2003)
A second-generation reactive empirical bond order (REBO) potential energy expression for hydrocarbons
DW Brenner et al.
JOURNAL OF PHYSICS-CONDENSED MATTER (2002)
Share Paper
