Analysis Model for Fire Accidents of Electric Bicycles Based on Principal Component Analysis
Ying Nian Wu, Zhu Yong-ping, Fang Xu, Jian Feng Xu · 2017
In this paper, we present an analysis model for fire accidents of electric bicycles based on principal component analysis (PCA). Our schema proposes a method to extract fire data of electric bicycle and analyzes the features selected as representative of fire data. The PCA method, which is one of the most popular methods of feature extraction at present, is introduced to the analysis model for fire accidents of electric bicycles. PCA has been widely used in pattern recognition, digital image processing, signal processing and other fields. Therefore, in this paper, we design an analysis model for fire accidents of electric bicycles based on PCA. We also give the system architecture and analysis process of our model which includes data pre-processing phase, training phase and analysis phase. With using PCA, our model can reduce the number of dimensions of fire data of electric bicycles; therefore it has certain theory and the practical application value.