TY  - CHAP
AU  - Sílvia Antunes
AU  - Oliveira Pires
AU  - Alfredo Rocha
ED  - Parinya Sanguansat
Y1  - 2012-03-07
PY  - 2012
T1  - Improving the Knowledge of Climatic Variability Patterns Using Spatio-Temporal Principal Component Analysis
N2  - This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as energy, multi-sensor data fusion, materials science, gas chromatographic analysis, ecology, video and image processing, agriculture, color coating, climate and automatic target recognition.
BT  - Principal Component Analysis
SP  - Ch. 10
UR  - https://doi.org/10.5772/38448
DO  - 10.5772/38448
SN  - 
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-05-10
ER  -