ScholarWorks@동국대학교

초록

This study aims to analyze a technology forecasting model that defines the characteristics of the technological development of flat panel displays and predicts the release year of the technology using a number of technical indicators as predictors. To this end, we review the general technology forecasting methodology along with an understanding of the development trend of flat panel display technology. Next, we set the target of technology forecasting as a research model and establish a technology forecasting model consisting of predictor variables, target variables, and a machine learning model. Then, we collect data on the technical characteristics of 575 flat panel display products manufactured by 39 companies from 1995 to 2022, and apply technology prediction models based on machine learning models such as linear regression, decision tree, AdaBoost, Gradient Boosting, random forest, and kNN. Finally, we analyze the prediction performance of each technology prediction model to derive the characteristics of each model and how to use them.

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