Research on Computer Simulation Big Data Intelligent Collection and Analysis System

Abstract

As a characteristic of big data, the individual data in it is no longer isolated, and the data and its underlying mechanisms have complex associations, which make all data into an indivisible whole. The dynamic generation and disappearance of data will change its original relationship and affect the overall characteristics of the data. This feature of big data makes the subject-oriented analysis methods such as data mining present limitations: the presupposition of the subject and the analysis by subject split the interaction relationship between the subjects, leading to the loss of the implicit mechanism in these relationships. Aiming at the problems of traditional network big data multi-resolution acquisition methods such as high acquisition cost, long completion time and low acquisition accuracy, a JA-va3D-based big data network multi-resolution acquisition method is proposed, and average interactive data is introduced. The extraction method estimates the power spectral density of the network data multi-resolution acquisition, and uses the ADASYN algorithm to remove the invalid multi-resolution data, and realizes the large data multi-resolution accurate acquisition. Experimental results show that the proposed method has lower acquisition cost, shorter completion time, and higher acquisition accuracy; it has certain practical value and can be widely used in various fields.