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논문 기본 정보

자료유형
학술저널
저자정보
Yang, Sang-Yun (Department of Forest Sciences, Seoul National University) Park, Yonggun (Department of Forest Sciences, Seoul National University) Chung, Hyunwoo (Department of Forest Sciences, Seoul National University) Kim, Hyunbin (Department of Forest Sciences, Seoul National University) Park, Se-Yeong (Department of Forest Sciences, Seoul National University) Choi, In-Gyu (Department of Forest Sciences, Seoul National University) Kwon, Ohkyung (National Instrumentation Center for Environmental Management, Seoul National University) Yeo, Hwanmyeong (Department of Forest Sciences, Seoul National University)
저널정보
한국목재공학회 목재공학(Journal of the Korean Wood Science and Technology) 목재공학 제47권 제1호
발행연도
2019.1
수록면
101 - 109 (9page)

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This paper examines the classification of five coniferous species, including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa), using near-infrared (NIR) spectra. Fifty lumber samples were collected for each species. After air-drying the lumber, the NIR spectra (wavelength = 780-2500 nm) were acquired on the wide face of the lumber samples. Soft independent modeling of class analogy (SIMCA) was performed to classify the five species using their NIR spectra. Three types of spectra (raw, standard normal variated, and Savitzky-Golay $2^{nd}$ derivative) were used to compare the classification reliability of the SIMCA models. The SIMCA model based on Savitzky-Golay $2^{nd}$ derivatives preprocessing was determined as the best classification model in this study. The accuracy, minimum precision, and minimum recall of the best model (PCA models using Savitzky-Golay $2^{nd}$ derivative preprocessed spectra) were evaluated as 73.00%, 98.54% (Korean pine), and 67.50% (Korean pine), respectively.

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