Analysis of Stability Big Data Environment of Intelligent Financial Data Abnormal QoS System based on Wolf Pack Algorithm

A new swarm intelligence algorithm, the Wolf Pack Algorithm has been proposed in this paper, and the convergence of the algorithm is proved based on the Markov chain theory. It reduces the risk of the algorithm falling into local optimum due to the excessively large penalty parameter. Inspired by the reproduction mode of wol ves, a big data environment analysis for the stability of the QoS system for abnormal data is proposed based on the binary wolf pack algorithm. Moreover, the Convolutional Neural Network with 4 hidden layers is used to classify and evaluate the constructed time series financial data. Data testing and analysis are performed using actual financial data. It is believed that the supervision system and relevant laws and regulations need to be improved first; secondly, the big data is used to collect personal credit records so as to establish a sound credit system as soon as possible; finally, through big data and computer technology, risk control methods are innovated to enhance the stability of Internet finance.