Abstract
This paper is oriented to the credit investigation scenario of power grid supply chain enterprises and proposes a blockchain user credit assessment method based on improved Softmax regression in Power IoT. This method first designs a credit-rating mechanism that meets industry characteristics based on business needs. Second, it proposes a user credit evaluation model based on the blockchain architecture. Finally, the improved Softmax regression algorithm is used to train the proposed credit evaluation model, which effectively solves the credit rating. The multiclassification problem has achieved the goal of categorizing the credit rating of the enterprise. The simulation results show that the credit evaluation mechanism proposed in this paper can accurately evaluate the multisource credit data that lacks trust foundation and effectively realize the credit rating of power grid material supply chain enterprises. The credit evaluation mechanism proposed for Power IoT in this paper could have high potential for entity identity authentication and rating for securing mobile video communications.
Highlights
Credit industry is an important part of China’s social credit system, which can reduce the harm caused by information asymmetry to capital transactions and can solve the bottleneck problem that restricts credit transactions
In view of the existing problems in the field of the credit industry, such as scattered credit data sources and low willingness of enterprises to share data, this paper studies the multiagency credit evaluation in the power grid supply chain scenario and proposes a blockchain user credit assessment method based on Softmax regression to solve the credit rating problem among the power grid supply chain agencies
This paper proposes a credit evaluation model based on improved Softmax regression, which effectively solves the problem of multiclassification of credit rating. e simulation results show that the blockchain-based Softmax regression algorithm can effectively solve the problem of multiagency credit evaluation in the power grid supply chain and improve the accuracy of credit evaluation. e credit evaluation mechanism proposed for Power IoT in this paper could have high potential for the entity identity authentication and rating for securing mobile video communications
Summary
Credit industry is an important part of China’s social credit system, which can reduce the harm caused by information asymmetry to capital transactions and can solve the bottleneck problem that restricts credit transactions. In view of the existing problems in the field of the credit industry, such as scattered credit data sources and low willingness of enterprises to share data, this paper studies the multiagency credit evaluation in the power grid supply chain scenario and proposes a blockchain user credit assessment method based on Softmax regression to solve the credit rating problem among the power grid supply chain agencies. E simulation results show that the blockchain-based Softmax regression algorithm can effectively solve the problem of multiagency credit evaluation in the power grid supply chain and improve the accuracy of credit evaluation. (2) In view of the difficult integration of multiagency credit assessment data in the power grid supply chain, this paper designs a blockchain-based credit evaluation system model for power grid enterprises, using smart contracts to achieve multitrust intelligent collaboration. E structure of this paper is as follows: Section 2 elaborates the related work, Section 3 proposes the blockchain-based credit evaluation model and the improved Softmax regression, Section 4 is shows experimental verification of the proposed method, and Section 5 is a summary of the whole paper
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