Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Software Engineering > Software Development

Research and Realization of Industry Injury Early Warning System Based on Web and Neural Networks

Author GuoHengChuan
Tutor ZhaoWenJing
School Xi'an University of Architecture and Technology
Course Applied Computer Technology
Keywords Industry injury RBF neural network Index system Early warning system
CLC TP311.52
Type Master's thesis
Year 2011
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Along with our country economy’s unceasing development, a lot of foreign-invested companies give great importance to China’s market due to gradually reduced tariffs and other canceled non-tariff measures such as quotas, licensing since China has entered into WTO. In order to get more profits, some enterprises dump their products, which has exerted great impact on our industries concerned, brought greater economic losses and disrupted the normal order of market economy. Therefore, the great priority should be offered to establish or improve warning and monitoring mechanisms for industrial injury, develop warning system so as to accurately forecast the industrial injury as soon as possible.Firstly, this article describes the research background of industry injury at home and abroad, introduces its research on the related fields and states the program’s current status, purposes and significance of research. Then, it discusses the principles, methods and key technologies involved in this subject, and points out the disadvantages of traditional algorithm in prediction of industrial injury index as well as the disadvantages of artificial prediction. Meanwhile, the feasibility of Neural Network imposed on industry injury is discussed on the basis of a series analysis of its principles, traits and its nonlinear approximation ability. According to the market demand, the appropriate methods are selected to improve the system. On this basis, I have established the warning indicator system structure for industry injury, carried out demand analysis so as to determine the system’s function and structure. At last, by means of adopting improved RBF Neural Network, I have built the environment of ASP.NET+IIS+SQL SERVER so as to achieve Web-based or Neural Network-based warning system.With application of Web technology, the system has collected, inquired and analyzed industrial production data. According to a variety of prediction algorithms in system, it has figured out the graphic display of industry injury data, data query and reminder function. Currently, this system has been applied by Department of Commerce of Henan Province. It has been widely received by the leaders of the Department and the enterprise users in Henan Province. It has resulted in significant economic benefit. The production effectiveness has also been improved too. It will help enterprises to respond to industry injuries timely and reduce economic losses. A series of practical effects demonstrate that this system have a high accuracy to predict the industry injury index, and can help enterprises to achieve the industry injury warning system automatically and intelligently. Therefore, the system will be of great significance for the actual production progress.

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