Research on Domestic Film Copyright Value Evaluation Based on PSO-SVR
The paper selects support vector regression machine(SVR)and particle swarm optimization(PSO)model,annual revenue top 30 from 2019 to 2022,a total of 100 domestic film box office revenue and its influencing factors as learning samples,uses particle swarm optimization to optimize support vector machine parameters,and gets domestic film box office prediction model with good learning and promotion abilities through training and test.The sharing method and the income method are introduced to evaluate the specific value of domestic film copyright,and the rationality of this model is confirmed through the case film"Home Coming".
domestic film copyrightbox office revenueparticle swarm optimizationsupport vector machinerevenue method
NETL
NSTL
万方数据
维普
