Competitiveness Of Chinese High-technology Industry

The 21st Century is the era which is based Knowledge economy, and dominated by science and technology. Science and technology are primary productive forces. High-tech, which has become one of productivity factors, is the main content of contemporary advanced productive forces. And it has become a main symbol of the advanced productivity. As a pillar industry of the knowledge economy, the high-tech plays a leading role in economic growth. Instead of traditional industries, it gradually becomes the backbone of the national economy in many countries, especially in developed countries and newly industrialized countries. And an important national strategic task of these countries is enhancing the competitiveness of high-tech industry. China has been among the world's major nations of the high-tech industries, but there are still many problems, such as a lack of innovation, imbalance of the industry development and so on. How to make a better and more accurate evaluation of the competitiveness of China's high-tech industry, and how to solve these problems become the primary task of the study on the competitiveness of high-tech industry. So, under the guidance of economic, this paper establishes a comprehensive index system, in order to evaluate competitive of high-tech industry.On the basis of original research results, this paper structure a assessment indicator system, which consistent with the law of economics, and can reflect the situation of the high-tech industry's competitiveness in China. Based on the annual data of high-tech industry, it uses BP neural network mode to analyze the high-tech industry competitiveness evaluation index system. Identified the key factors that affect competitiveness of high-tech industry, and took comprehensive evaluation to competitiveness of Chinese high-tech industry from the key factors.And to some extents, it analyzes the influence factor of the five high-tech industries. BP neural network is good at decision-making in the approximate and uncertain knowledge environment. It can solve weight design and calculation of correlation coefficient. And it is more suitable for solving the problems in the industry competitiveness evaluation, such as incomplete information, more Indicator and nonlinear correlation between some indicators. So, compared with other methods, BP neural network has more advantages in identification and evaluation of the competitiveness of high-tech industry.Based on the evaluation of the competitiveness of high-tech industries and empirical Papers obtained the competitiveness of Chinese high-tech industry and shortage. From the empirical results, eliminated deficiencies and made policy and suggestions for improve competitiveness of high-tech industry.