Data-driven novel agricultural operation subject credit rating generation method and device
A credit rating, data-driven technology, applied in data processing applications, special data processing applications, unstructured text data retrieval, etc., can solve the problems that hinder the widespread application of machine learning credit rating generation, and cannot share data, so as to improve evaluation Accuracy, improvement of acquisition efficiency, and the effect of improving the level of intelligence
Pending Publication Date: 2022-05-03
北京市农林科学院信息技术研究中心
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However, due to the influence of legal policies, economic interests and other factors, the participants are faced with the dilemma of unwillingness, daring, and inability to share data, which seriously hinders the widespread application of data-driven machine learning credit rating generation
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[0026] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
[0027] Combine below Figure 1 to Figure 3 Describe the data-driven method and device for generating credit ratings for new agricultural business entities of the present invention. figure 1 It is a schematic flow chart of the data-driven new method for generating credit ratings of agricultural business entities provided by the present invention, as shown in figure 1 As shown, the present in...
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The invention provides a data-driven novel agricultural operation subject credit rating generation method and device. The method comprises the following steps: obtaining evaluation data related to each subordinate operation subject from a plurality of data sources; according to different credit rating index sets, calculating all credit rating index values of each operation subject based on the evaluation data; inputting the rating index value into a preset credit rating division model, and outputting the credit rating of each operation subject; constructing an operation subject knowledge graph, and performing visual expression and knowledge reasoning on credit information of an operation subject; wherein the credit rating model is obtained by performing local training on each credit server based on local training data and then performing global training according to training parameters of all credit servers. According to the method, local data privacy can be guaranteed, the problems of data islands, data privacy and the like in model training are well solved, and a credit rating result can more objectively and accurately reflect the credit condition of an operation subject.
Description
technical field [0001] The invention relates to the field of intelligent agricultural information processing, in particular to a data-driven method and device for generating credit ratings of new agricultural business entities. Background technique [0002] In recent years, various new types of agricultural management entities represented by family farms, large professional households, farmers' cooperatives, and leading agricultural industrialization enterprises have played an important role in ensuring food security and promoting the development of agricultural and rural economies. An important force for increasing income and effective supply of agricultural products. At the same time, new-type agricultural business entities are also generally faced with problems such as small business scale, non-standard operation, low management level, and lack of effective collateral. The characteristics of high market risk make it difficult for a market-oriented financial system that i...
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IPC IPC(8): G06Q40/02G06Q50/02G06Q10/06G06F16/36G06N20/00
CPCG06Q50/02G06Q10/06393G06F16/367G06N20/00G06Q40/03
Inventor 潘守慧王开义赵向宇韩焱云刘忠强杨锋
Owner 北京市农林科学院信息技术研究中心