Open AccessApplication of hybrid model of big data and BP network on strategy prediction
Author(s) -
Tengteng Qin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1941/1/012044
Subject(s) - big data , artificial neural network , computer science , data mining , mode (computer interface) , data set , set (abstract data type) , asset (computer security) , process (computing) , artificial intelligence , stability (learning theory) , machine learning , computer security , programming language , operating system
Big data refers to the data set that cannot be captured, managed and processed by conventional software tools within a certain period of time. It is a massive, high growth rate and diversified information asset that needs new processing mode to have stronger decision-making power, insight and process optimization ability. BP neural network can be applied to the prediction of models and the study of the relationship between different models. Therefore, the combination of big data technology and BP neural network can deal with large and complex nonlinear structural problems from a statistical point of view, and with high stability and accuracy. This paper collects a cloud computing revenue from 2015 to 2019, and analyzes the impact of strategy mode value by using the combination of big data and BP neural network. The conclusion is that the correlation coefficient is 0.99762, which proves that big data combined with BP neural network can make accurate and effective decision prediction.