Title :
An intelligent data mining technique for the estimations of TP film´s chromatic aberration
Author :
Yu-Ju Chen ; Pu-Ten Hsu ; Wang, S.T. ; Chi-Yen Shen ; Shen-Whan Chen ; Rey-Chue Hwang
Author_Institution :
Inf. Manage. Dept., Cheng-Shiu Univ., Kaohsiung, Taiwan
Abstract :
This paper presents a novel intelligent data mining technique to estimate the optical properties of touch panel (TP) with different layers coating. The neural network (NN) model is developed to be the intelligent tool for the data analyzer. The new computational method based on well-trained NN´s weights is used to analyze the influencing factors of TP film´s chromatic aberration, i.e. L.a.b. values. The influence degree of each input variable to the net output could be determined through the computational results. The useful and important information for TP film´s chromatic aberration then can be obtained. In this research, the data of TP film with Cr and Cr2O3 coating are studied. All possible influencing factors are collected and considered. An artificial intelligent (Al) estimator using the best influencing factors is expected to be developed so that the optical properties of TP decoration film could be precisely estimated before the evaporation process is taken.
Keywords :
aberrations; data mining; decorative coatings; learning (artificial intelligence); neural nets; optical engineering computing; touch sensitive screens; AI estimator; L.a.b. values; TP decoration film; TP film chromatic aberration estimations; artificial intelligent estimator; chromium coating; chromium(III) oxide coating; coating layers; computational method; data analyzer; evaporation process; influence degree; input variable; intelligent data mining technique; intelligent tool; neural network model; optical properties; touch panel optical property estimation; trained NN model weights; Artificial neural networks; Coatings; Data mining; Estimation; Films; Training; data mining; influence degree; neural network; optical properties; touch panel;
Conference_Titel :
Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
Conference_Location :
Toronto, ON
DOI :
10.1109/IMSNA.2013.6743379