Abstract: The ambient light of cockpit is usually under mesopic vision, and it’s mainly related to the cockpit’s interior. In this paper, a SB model is come up to simplify the relationship between the mesopic luminous efficiency and the different photometric and colorimetric variables in the cockpit. Self-Organizing Map (SOM) network is demonstrated classifying and selecting samples. A Back-Propagation (BP) network can automatically learn the relationship between material characteristics and mesopic luminous efficiency. Comparing with the MOVE model, SB model can quickly calculate the mesopic luminous efficiency with certain accuracy.

Dongdong WEI and Gang SUN, “Mesopic Visual Performance of Cockpit’s Interior based on Artificial Neural Network” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 1(6), 2012. http://dx.doi.org/10.14569/IJARAI.2012.010603

@article{WEI2012,
title = {Mesopic Visual Performance of Cockpit’s Interior based on Artificial Neural Network},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2012.010603},
url = {http://dx.doi.org/10.14569/IJARAI.2012.010603},
year = {2012},
publisher = {The Science and Information Organization},
volume = {1},
number = {6},
author = {Dongdong WEI and Gang SUN}
}