Abstract
This paper presents the transmittance estimation of touch panel (TP) film with two layers coating by using quantum neural network (QNN) model. Due to the capability of classifying the features of signals, QNN model was used to catch the complex relationship between TP transmittance and its all possible influencing factors. An artificial intelligence (AI) evaporation decision mechanism is expected to be developed. Such an AI system could help the technician to set the control parameters before the TP film’s evaporation process is taken. This smart system can not only help technician to improve the work efficiency, but also reduce the company’s cost. In order to demonstrate the possibility and superiority of the research, several QNN models with different input combinations were simulated and reported. The simulation results are shown as a comparison.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
