Research On Enterprise Informationization Level Based On ANN

Modern enterprise is the main force to promote modern economic and technological progress. Business management effectiveness significantly influences productivity of enterprise and determines the competitiveness ability to survive. Infomationization is an important means of modern enterprise management. Whether the enterprise advanced or not can look at the level of development of infomationization. There are two disadvantages in traditional evaluation methods. First the index system is very complex second calculating skills are out of date. Very large amount of statistics and artifical factors make it difficult to guarantee the authenticity of results.This study is to look for a better path to do this kind of research. Artificial neural network (ANN) is simplicity and simulation of human thinking. ANN is good at simulating and used in every subjects very widely. For the level of infomationization I selected some representative high-tech enterprises in hefei high-tech zone as the research subjects. I evaluated these by ANN. In the work I select BP neural network. BP neural network is one of the artificial neural networks with simple operation and good generalization used very popularly. I reduce the traditional indexes system less to two parts including12indexes to make it more operational, more simple and effective. Then work by artificial neural network. I designed the neural network by toolbox in MATLAB software. First take20learning samples for training and the actual error of results controled between0.01and0.1. Second test the left30samples data into the trained network in order to get the final evaluation results.This paper is divided into the following five sections:First introduced background and significance of this research project. The literature review and summary of my own research methods and ideas.This part is the overall context of the full paper and all the work steps. First of all started from the definition of infomationization then sort out the domestic and foreign literature on the evaluation of the infomationization level especially domestic research results in the area. Make my own methods and ideas to synthesize the full text contents to outline things overall for the full paper.Second review of the definition of artificial neural networks including the definition of ANN, emergence and development history. Focused on the applications and features of the neural network and placed the simple three-layer BP neural network highlight to explain various ANN functions and operations of algorithm. By BP network we found some advantages in this method combined with this study.Third research and excavation of index system. Described the three principles: comprehensiveness, operational and scientific. By studying the common index system pointed out its deficiencies in practice and proposed my own set of practical indicators system. Then used scientific ways to weigh every index. A questionnaire used in this study designed on the basis in order to get reliable and complete data for study.Fourth the key part for this paper starting from the introduction of Hefei High-tech zone. And gradual transition to infomationization level evaluation of some enterprises in Hefei High-tech zone. Collect relevant data for each indicator by the evaluation index system designed.20representative enterprises data selected as the network learning samples for BP network evaluation conclusion practical. The remaining30enterprises data as the final test samples achieved final results by using the trained network tested.The last conclusions and outlook. Summarized and analyzed the results obtained in this study and pointed out that the results of research. Planed the future work and put up something need to improve and supplement for the detailed study.