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专利权作为无形资产,其风险状况比有形资产高,且难以量化识别,是导致该业务发展缓慢,商业银行参与贷款积极性不高的重要原因。构建BP神经网络模型,对专利权质押贷款的风险进行识别,并借助MATLAB工具,实现了对质押案例的仿真实验。仿真结果显示:风险量化模型的整体准确率高达96%。说明该模型能够识别专利权质押贷款的风险类型,为商业银行提供风险预警,进而为其从事专利权质押贷款决策提供参考。
Patent rights, as intangible assets, have a higher risk status than tangible assets and are difficult to quantify and identify. This is an important reason that the development of this business is sluggish and commercial banks are not enthusiastic about participating in loans. The model of BP neural network is constructed to identify the risk of patent pledge loan. With the aid of MATLAB tools, the simulation experiment of pledge case is realized. The simulation results show that the overall accuracy of the quantitative model of risk is as high as 96%. It shows that this model can identify the risk type of pledge loan, provide risk warning to commercial banks, and provide reference for decision - making of pledge loan.