Research On The Evaluation Of The Development Capacity Of The Big Data Industry In The Underdeveloped Areas Of The West

In the context of the country's great efforts to develop big data,many western underdeveloped areas want to use big data to achieve overtaking in curve.Comparing with the developed areas,most of the undeveloped western regions,including Guizhou Province.Due to the constraints of weak information infrastructure,information technology application level is low,talent insufficiency and other factors,whether big data industry should be vigorously developed and whether it has the relevant basic conditions for the development of big data industries have always been a common concern of academia and the government.At the same time,how to evaluate the development ability of big data industry in various cities,to complete the spatial distribution of big data industry in various provinces and to realize the coordinated development of provinces and cities are the key tasks of formulating big data industry policy.Therefore,it is urgent to establish a set of scientific evaluation system and evaluation model for the development ability of large data industry,so as to accurately measure and reflect the development level and present situation of big data industry in underdeveloped areas of Western China,from theory and practice to guide construction and development of big data industry in undeveloped areas of Western China,to maintain and improve the regional competitive advantage.Is of special significance to obtain the best economic and social benefits.Firstly,this paper analyzes the basic factors,core factors and environmental factors that influence the development of big data industry in undeveloped areas of Western China.Referring to the evaluation system of the development of the new generation of information technology related industries and the principle of the construction of the index system,the evaluation index system for the development ability of the big data industry in the underdeveloped areas of the west is established.Secondly,the mainstream evaluation methods,such as AHP,principal component analysis,factor analysis are briefly summarized.Based on entropy weight-BP neural network,an evaluation model of big data industrial capacity in the underdeveloped areas of Western China are built.The entropy weight method is used to determine the weight of the index,and as the expected output of the BP network model,the larger error of the single BP neural network is optimized and the accuracy and objectivity of the evaluation are improved.Finally,the model simulation is carried out by MATLAB programming,and the effectiveness of the model is verified by the example of the evaluation of the development capability of the big data industry in Guizhou province.This paper analyzes the experience of rapid development of big data in Guizhou province,and puts forward three development measures for western underdeveloped areas from the following aspects: making big data plans and policies,building big data applications and platforms,cultivating big data talents and disciplines.