Chuo-Yean Chang

Learn More
This paper presents an indoor positioning technique based on neural networks (NN). The received signal strengths (RSS) sensed by Zigbee wireless sensor network were used to estimate the position of object. From the simulation results shown, the NN technique proposed still has the high accuracy even the signal strengths sensed are unstable. Besides, from the(More)
In this paper, the transmittance estimation of touch panel decoration film by using quantum neural network (QNN) is proposed. This model is able to catch the complex relationship between the film’s transmittance and its possible influencing factors. An artificial intelligent (AI) mechanism for the decision of control parameters of film evaporation(More)
In this paper, a new logic circuit design technique by using neural network and particle swarm optimization (PSO) method is proposed. The neural network was used to substitute the logic unit and PSO algorithm was used to determine the possibility of connections among the logic units. By off-line gate-level samples, the simulation results clearly demonstrate(More)
In this paper, the estimations for the optical property of touch panel (TP) decoration film with two layers coating are presented. The technique of neural network is used to develop an artificial intelligent (AI) TP transmittance estimator which is able to catch the complicated relationship between TP transmittance and its all possible influencing factors,(More)
The paper presents an intelligent control mechanism for the ITO bar's resistance of touch panel (TP). The artificial neural network is used to catch the complex relationship between bar's resistance and its relevant manufacturing parameters during the printing and etching processes. An effective and accurate manufacturing mechanism of ITO bar is expected to(More)
This paper presents the chromatic aberration estimations of touch panel (TP) film by using quasi-Newton neural networks. The data of TP film with one layer coating was studied and simulated. Through the training of neural network, the complex relationship between the chromatic aberration, i.e., L.A.B. values, and the relative parameters of TP decoration(More)
This paper presents the identifications of ammonia concentration by using several different neural network (NN) models. The shear horizontal surface acoustic wave (SH-SAW) device coated with polyaniline (PANI) film was applied as ammonia sensor. The data sensed by SH-SAW sensor was implemented by these NN models. A reliable and superior intelligent(More)
In this paper, the signal processing by using polynomial neural network (NN) and its equivalent polynomial function is studied and simulated. To demonstrate the superiority of the equivalent polynomial function proposed, the signal recognition in a two-dimension (NC2) non-convex system and system identification were simulated and discussed. All simulations(More)
In this paper, the neural network estimator for mechanical property of rolled steel bar was proposed. Based on the learning capability of neural network, the nonlinear, complex relationships among the steel bar, the billet materials and the control parameters of production are expected to be automatically developed. Such a neural network estimator can help(More)
This paper presents the power load forecasting by using neural models for Toronto area, Canada. Different neural models were used to carry out the forecasting works. One-day-ahead daily total load and peak load forecasts were implemented by using different neural models in order to find the more accurate forecasting results. The load data and temperatures(More)