基于PSO-SVR的国产电影著作权价值评估研究
Research on Domestic Film Copyright Value Evaluation Based on PSO-SVR
张强 1郭红霞1
作者信息
- 1. 广西科技大学 经济与管理学院,广西 柳州 545000
- 折叠
摘要
文章选取支持向量回归机SVR与粒子群算法PSO相结合的模型,将 2019-2022 年每年的票房收入前 30 位,共计 100 部国产电影的票房收入及其影响因素作为学习样本,利用粒子群算法对支持向量机参数进行优化,通过训练、测试得到具有良好学习与推广能力的国产电影票房预测模型.再引入分成法和收益法来评估出国产电影著作权的具体价值,同时通过案例电影《万里归途》来证实这一模型的合理性.
Abstract
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".
关键词
国产电影著作权/票房收入/粒子群算法/支持向量机/收益法Key words
domestic film copyright/box office revenue/particle swarm optimization/support vector machine/revenue method引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据