Research Development On Risk Analysis Of Technology Contract Based On Neural Network

In the deepening of contract management and risk management to gradually improve the development of today,along with science and technology development and research and education investment in our nation,technology contract signing and management needs are also in the urgent growth,but in the process for the risk of technical contracts Management has become an important part of people ignore.Therefore,technology contract risk analysis becomes more and more important in the management of technology contracts,which becomes the key problem in the field.Based on the research background and significance of risk analysis,contract risk analysis and technology contract risk analysis,this paper,based on the relevant theories of technology contract and relevant knowledge of risk assessment as the technical support,A set of risk factors theory of technology contract,and introduces a series of concepts,such as general risk factor of contract,dynamic risk factor of contract,contract risk factor library,importance degree and risk value,and then put forward a risk factor different from the traditional risk factor identification method Dynamic identification algorithm,which is based on historical document analysis and text analysis technology,constructs the basic risk factor library,and relies on the natural language processing method and the web crawler technology to excavate the dynamic risk factor of technology contract,and obtain the contract risk factor library after the second integration of the factor library.Then,the qualitative data of the contract risk factor library are evaluated and the input value of the neural network model is obtained by using the two-factor risk factor quantification method proposed in this paper.Finally,based on the knowledge of neural network,the risk analysis model of technology contract is constructed,and the risk pre-warning is given,so as to achieve the risk analysis of technology contract by using neural network.In the end,tthe training and testing of the neural network model are carried out on the experimental dataset,and the effectiveness of the proposed model in the technical contract risk analysis is verified by comparing the experts' scores.