Application Of Factor Analysis And Neural Network In Shandong Province Transport Analysis

The rapid development of China’s economy has benefited from our network of transportation infrastructure construction to a large extent, on the one hand it is a large transportation network construction of infrastructure, has played a significant role in boosting investment, but more important is that the transport facilities improvement directly contributed to the progress of the transport sector, and it is strong support for the development of the logistics industry, especially with the popularity and the popularity of online shopping, it promoted the rapid development of China’s logistics industry. Transport has become one of the industry focuses on the development of all regions in our country, how to analyze the problem of the transport sector, and to make effective guidance to countries and regions is an important and meaningful issue.As calculating level of progress, especially the widespread using of scientific methods of calculation and accurate analytical data has become an important issue in various industries, the actual cover a wider range of transport sector, and it has a very large amount of data, so using of modern calculation method can achieve faster calculations, and it also can provide more accurate results. So we used the calculation factor analysis and neural network analysis of transportation data, and it is in order to improve the accuracy of the data analysis.In this paper, it researched transport data of Shandong Province’s 17prefecture-level cities, the data source is "Statistical Yearbook-2015 Shandong," Shandong Statistical Yearbook is a reflection of the socio-economic data and national situation of Shandong Province.Using analysis algorithms and neural network algorithm, it mainly completed thefollowing two tasks by studying statistical data of urban transport.First, using of factor analysis, it researched Shandong Province’s 17prefecture-level cities transport, and it got cities’ integrated sorting and obtained factor scores.Factor analysis is an algorithm analyzing the actual relationship between variables, and it is possible to find a handful of variables to represent the actual index,and there is a linear relationship between a handful of the original variables and indicator variables.Using factor analysis, it analyzed 45 properties of 17 prefecture-level cities’ urban transport, and it gave six common factors by calculating the factor score, so Shandong Province 17 prefecture-level cities on urban transport were ranked.Second, we use neural network algorithm to predict the transport route, and to look for growth in Shandong Province of the total length of transportation routes.Artificial neural network consists of a large number of neurons, and it achieved the purpose of information storage and transmission interconnected by neurons and the relationship between neurons. Neural network can simulate the characteristics of the human brain, nervous system, so it can establish relevant data model through the relationship between neurons and between neurons.Transport line length and length of railway lines, roads line length, line length of river in Shandong Province since 1949 were summarized, it established a neural network model, it forecasted the length of railway lines, roads line length, line length on the river of the next year’s using this year’s data. By the different neural network algorithm, it predicted the different results and analyzed the data.