Construction of Social Security Fund Cloud Audit Platform Based on Fuzzy Data Mining Algorithm
Author(s) -
Yangting Huai,
Qianxiao Zhang
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/9939454
Subject(s) - computer science , cloud computing , audit , fuzzy logic , algorithm , information security audit , data mining , social network (sociolinguistics) , cloud computing security , computer security , accounting , artificial intelligence , network security policy , world wide web , business , social media , operating system
Guided by the theories of system theory, synergetic theory, and other disciplines and based on fuzzy data mining algorithm, this article constructs a three-tier social security fund cloud audit platform. Firstly, the article systematically expounds the current situation of social security fund and social security fund audit, such as the technical basis of cloud computing and data mining. Combined with the actual work, the necessity and feasibility of building a cloud audit platform for social security funds are analyzed. (is article focuses on the construction of the cloud audit platform for social security funds. (e general idea of using fuzzy data mining algorithm to build the social security fund audit cloud platform is to compress the knowledge contained in a large number of data into the weights between nodes and optimize the weights through the learning of the neural network system. (rough the optimization function, the information contained in the neural network is stored in a few weights as far as possible. (e main information is further highlighted by network clipping and removing weights that have little impact on the output.
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