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

Shengqing Ma¹, Fei Hao², Youwu Lin³

¹School of Economics and Management, Qinghai Normal University, Xining, Qinghai 810000, China.

Computational Intelligence and Neuroscience

|April 4, 2022

Summary

This study introduces a novel E-government big data algorithm for improved data filling and classification accuracy in cloud computing environments. The enhanced system achieves optimal performance with 24 decision trees, boosting efficiency.

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Area of Science:

Computer Science
Information Systems
Data Science

Background:

Traditional E-government big data systems suffer from low accuracy and efficiency in data filling and classification.
Challenges in information resource integration include incomplete systems, non-standardized management, and security threats.
The proliferation of big data and the Internet of Things necessitates advanced solutions for government information management.

Purpose of the Study:

To develop a new E-government big data filling and classification algorithm within a cloud computing environment.
To address issues of incomplete data, varying standards, and security vulnerabilities in government information systems.
To construct an intelligent computing system for E-government big data, enhancing data processing and security.

Main Methods:

Implementing a novel algorithm for E-government big data filling based on complete compatibility theory.
Developing an intelligent computing system in a cloud environment for parallel data processing.
Utilizing decision trees for data classification and implementing incremental update decision forest parallelization.

Main Results:

The proposed method successfully parallelizes data and classifies it using decision trees.
Experimental validation demonstrated the effectiveness of the decision forest algorithm.
The optimal number of decision trees for the classification model was determined to be 24.

Conclusions:

The new algorithm significantly improves the accuracy and efficiency of E-government big data processing.
The developed intelligent computing system offers a robust solution for managing and securing government information resources.
The findings support the adoption of advanced algorithms and cloud computing for modern E-government.