An Effective Credit Evaluation Mechanism with Softmax Regression and Blockchain in Power IoT. (14th February 2022) - Li, Da; Wang, Dong; Jiang, Wei; Guo, Qinglei; Bai, Desheng; Shi, Wei; Ruan, Linna
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.