A comparison of principal component regression and artificial neural network in fruits quality prediction

• 主要な著者: Kim, Seng Chia, Abd. Rahim, Herlina, Abd. Rahim, Ruzairi
• フォーマット: Book Section
• 出版事項: IEEE Explore 2011
• 主題: QA75 Electronic computers. Computer science
• オンライン･アクセス: http://eprints.utm.my/id/eprint/24291/; http://dx.doi.org/10.1109/CSPA.2011.5759884

Generally, non-linear predictive models should be superior to linear predictive models. The objective of this study is to compare the performance of soluble solid content (SSC) prediction via Artificial Neural Network with Principal Components (PCs-ANN) and Principal Component Regression (PCR) in Vi...