The Construction of Big Data Computational Intelligence System for E-Government in Cloud Computing Environment and Its Development Impact

Abstract

The traditional E-government big data system fills and classifies algorithms with low accuracy and poor work efficiency. With the development and wide application of big data, the internet of things, and other technologies, the integration of information resources has become the key to information construction. In the process of information resource integration, there are still outstanding problems such as incomplete government information resource system, different standards of government information resource management system construction, and serious threats to network and information security. In order to solve this problem, a new E-government big data system filling and classification algorithm is studied in the cloud computing environment; E-government big data filling is carried out on the basis of complete compatibility theory; and the E-government big data computing intelligence system in the cloud computing environment is constructed and its development impact, so as to parallelize the data, classify the data through decision trees, and realize incremental update decision forest parallelization processing. To verify the effectiveness of the method, comparative experiments are set, and the results demonstrate that experiment one is randomly built into the classification model, and according to the decision forest algorithm, the optimal number of decision trees is 24.

Retracted: The Construction of Big Data Computational Intelligence System for E‐Government in Cloud Computing Environment and Its Development Impact

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”