A supply chain financial credit analysis method based on multi-layer genetic method under the background of big data

An analysis method and supply chain technology, applied in data processing applications, finance, genetic models, etc., can solve problems such as inaccurate supply chain financial data analysis

Active Publication Date: 2021-05-14
湖南衍金征信数据服务有限公司
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Problems solved by technology

[0005] In order to solve the technical problem that the current supply chain financial data analysis is not accurate enough, the present invention provides a supply chain financial credit analysis method based on a multi-layer genetic method under the background of big data, in order to achieve accurate supply chain financial credit analysis

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  • A supply chain financial credit analysis method based on multi-layer genetic method under the background of big data
  • A supply chain financial credit analysis method based on multi-layer genetic method under the background of big data
  • A supply chain financial credit analysis method based on multi-layer genetic method under the background of big data

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Embodiment Construction

[0036] Data Obfuscation

[0037] In supply chain finance, there are a large number of evaluation indicators, and the data format is not uniform. In order to facilitate computer analysis and processing, this embodiment will fuzzy the original data used as evaluation indicators.

[0038] First, the present embodiment defines the original data matrix L={l n,m | l n,m ∈{0,1}} N×M It is used to represent all the evaluation data of a certain company within a certain period of time, where l n,m Indicates the value of the mth evaluation indicator at the nth unit time.

[0039] Then, this embodiment performs fuzzy processing on the data by classifying the data. In order to make this method have a higher degree of adaptability, this embodiment does not specifically limit the number of data classification stages, but as an initial parameter, before the calculation starts Make settings. Define the desirable maximum value of the Mth index of the original data as FC, and divide the dat...

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Abstract

The invention discloses a supply chain financial credit analysis method based on a multi-layer genetic method under the background of big data. The invention designs a data classification method to perform fuzzy processing on it, effectively speeding up the computer's analysis and calculation of data; at the same time , in the coding stage, this embodiment divides the supply chain data into three layers according to the characteristics, and each layer designs a corresponding crossover method. As the genetic segment at the bottom layer, this embodiment designs random intersection points to meet the diversity of the population; as the chromosome at the middle layer, it plays a vital role in finding the local optimal solution, so this embodiment uses the golden section method to design Fixed intersection points, while avoiding the interaction between different types of data; as the top layer of the nucleus, the purpose of the intersection is to gather chromosomes with high fitness into one chromosome, speed up the evolution of the nucleus, and improve the convergence speed of the method.

Description

technical field [0001] The invention relates to a supply chain financial credit analysis method based on a multi-layer genetic method under the background of big data. Background technique [0002] At present, in the banking business, the main source of income is to provide financing for enterprises, that is, financial lending services. However, due to the different operating conditions of each enterprise, in order to reduce the possible risks of bank financing as much as possible, before starting financing, the bank will To evaluate the corresponding enterprises, the evaluation needs to collect the corresponding financial data of the enterprises and conduct effective analysis. [0003] But at present, traditional bank financing relies on less information and static analysis. However, in supply chain finance, the amount of data generated every day is very large, and it is dynamic data, but the importance of these data to credit ratings is not the same. It is too large, and...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q40/02G06N3/12
Inventor 杨智曾峰
Owner 湖南衍金征信数据服务有限公司
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