Time series solving method and system for music traffic prediction

Abstract

The invention belongs to the technical field of music prediction model, and discloses a time series solving method and system for music traffic prediction. The method comprises the following steps that: carrying out model construction for a music user, and using a weighted fuzzy kernel clustering model to carry out a music use clustering operation; on the basis of artist dataset obtained by user clustering, carrying out the construction of the music traffic prediction model, and using algorithm based on feasible coefficient space segmentation for prediction; and verifying the efficiency and the accuracy of the artist music traffic prediction in ta music playing traffic prediction model. The method assists a player manufacturer to reasonably arrange a player background and a proper networkbandwidth so as to effectively lower the probability of occurrence of crash, meanwhile, through the research of the integral classification of music users and a classification prediction result of music, the analysis of the player manufacture for the development tendency of the music traffic is improved, and a result generated by prediction reduces loss for enterprises.

Description

technical field [0001] The invention belongs to the technical field of music prediction models, and in particular relates to a time series decomposition method and system for solving music flow prediction. Background technique [0002] In recent years, with the improvement of the accuracy of traffic forecasting, music song traffic forecasting in traffic forecasting has also become more and more important. As the core basis of music song traffic prediction, music songs have been valued and explored by many researchers, mainly for two problems of music genre recognition and audience listening to song recognition. At present, many scholars and relevant experts have proposed some corresponding solutions, but there are still many problems to be solved so far. [0003] In 2016, the market size of digital media music in China was as high as 60 billion yuan. Among them, the scale of the PC-side music song market is 8 billion yuan, an increase of 13.4% year-on-year; the mobile phon...

AI Technical Summary

Problems solved by technology

[0008] In the existing forecast, when solving the accuracy of artist song traffic forecast, the forecast deviation is large due to the excessive fluctuation of data; the previous data classification forecast is difficult due to different user preferences

Images