Study on the analysis method of data based on neural network algorithm
With the advent of the depth of the Internet era,the great economic and scientific value of the big data is gradually highlighted. However,there are technical barriers to the data analysis methods of big data.In order to explore the value space of big data,we need to abandon the traditional program and develop new data analysis methods.The deep neural network algorithm uses bionic learning algorithm to integrate huge heterogeneous data,filters multi-source information,and realizes dynamic capture, which can perfect the bridge of transforming big data into value information. This paper focuses on the analysis of "big data + neural network" deep learning algorithm in unstructured model,changeable, characteristics of cross domain data in extraction mode,and feedforward neural network based on infinite connection method,coupling time parameter prediction feature extraction and more accurate data. The final test of its application in speech recognition and image analysis,the results show that the infinite neural network in data processing compared with the ordinary algorithm have more computational efficiency and powerful performance advantage.
data characteristicsneural network algorithmartificial intelligenceneural networkRTRL algorithm
NETL
NSTL
万方数据
维普
