基于数据挖掘的航班数据分析

With the advent of the cloud era, big data has attracted more and more attention. Internet of things, cloud computing, mobile internet, vehicle networking, phone, tablet, PC and a variety of sensors that throughout every corner of the earth, all of them are the sources of data or the way of data carrier. Meanwhile, the core value of big data is the storage and analysis of massive data. So far, most of the research is the analysis and implementation methods based on the aspects of flight delays. This paper aims to use the way of data mining, the method of principal component analysis in feature extraction technique, dig out the information of flight time accurately from large amounts of data, and then according to the current flight status, estimate the possible arrival time of the flight, it has definite reference value in drawing up the flight planning time; What's more, according to the space tables published on the airlines' websites, calculate the relative average prices of the space tables, estimate the total seats according to the maximum number of actual monthly airline passengers, calculate the attendance according to the number of passengers of China Southern Airlines 2013, then analyze the correlation coefficient between the relative average prices and attendance, it has definite reference value in drawing up the prices of the tickets.