Decomposition-integration-based prediction study on the development trend of film industry
Movies have the unique ability to both generate income and spread culture, thus predicting the direction of the film industry's growth has garnered a lot of interest. Given the volatility of the movie industry's entire box office revenue dataset and the peculiarities of tiny samples, this...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023084190 |
| _version_ | 1827616094251122688 |
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| author | Yuan Ni Siyuan Li |
| author_facet | Yuan Ni Siyuan Li |
| author_sort | Yuan Ni |
| collection | DOAJ |
| description | Movies have the unique ability to both generate income and spread culture, thus predicting the direction of the film industry's growth has garnered a lot of interest. Given the volatility of the movie industry's entire box office revenue dataset and the peculiarities of tiny samples, this article incorporates the decomposition-integration notion to build the EEMD-PSO-LSSVM model movie box office prediction model. The historical box office data are first broken down into many components using the ensemble empirical modal decomposition technique, and then, distinct sequences are predicted using the least squares support vector machine prediction method with particle swarm optimization, and ultimately, the predictions for each sequence are combined. The experimental results demonstrate the effectiveness of the decomposition-integration technique in illustrating the data fluctuation characteristics of quarterly movie box office revenues. When compared to other models, the model proposed in this study has clear advantages in the problem of predicting the time series data of box office revenues that are non-linear, non-smooth, and non-large samples. |
| first_indexed | 2024-03-09T09:19:53Z |
| format | Article |
| id | doaj.art-8e699e9c07a54bbfb8c501c47a5a1a6d |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-09T09:19:53Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-8e699e9c07a54bbfb8c501c47a5a1a6d2023-12-02T07:01:29ZengElsevierHeliyon2405-84402023-11-01911e21211Decomposition-integration-based prediction study on the development trend of film industryYuan Ni0Siyuan Li1School of Economics and Management, Beijing Information Science and Technology University, 12 Xiaoying East Road, Haidian District, Beijing, PR China; Beijing Key Laboratory of Green Development Big Data Decision Making, 12 Xiaoying East Road, Haidian District, Beijing, PR ChinaSchool of Economics and Management, Beijing Information Science and Technology University, 12 Xiaoying East Road, Haidian District, Beijing, PR China; Corresponding author.Movies have the unique ability to both generate income and spread culture, thus predicting the direction of the film industry's growth has garnered a lot of interest. Given the volatility of the movie industry's entire box office revenue dataset and the peculiarities of tiny samples, this article incorporates the decomposition-integration notion to build the EEMD-PSO-LSSVM model movie box office prediction model. The historical box office data are first broken down into many components using the ensemble empirical modal decomposition technique, and then, distinct sequences are predicted using the least squares support vector machine prediction method with particle swarm optimization, and ultimately, the predictions for each sequence are combined. The experimental results demonstrate the effectiveness of the decomposition-integration technique in illustrating the data fluctuation characteristics of quarterly movie box office revenues. When compared to other models, the model proposed in this study has clear advantages in the problem of predicting the time series data of box office revenues that are non-linear, non-smooth, and non-large samples.http://www.sciencedirect.com/science/article/pii/S2405844023084190Film industrySituation predictionDecomposition-integrationEEMD |
| spellingShingle | Yuan Ni Siyuan Li Decomposition-integration-based prediction study on the development trend of film industry Heliyon Film industry Situation prediction Decomposition-integration EEMD |
| title | Decomposition-integration-based prediction study on the development trend of film industry |
| title_full | Decomposition-integration-based prediction study on the development trend of film industry |
| title_fullStr | Decomposition-integration-based prediction study on the development trend of film industry |
| title_full_unstemmed | Decomposition-integration-based prediction study on the development trend of film industry |
| title_short | Decomposition-integration-based prediction study on the development trend of film industry |
| title_sort | decomposition integration based prediction study on the development trend of film industry |
| topic | Film industry Situation prediction Decomposition-integration EEMD |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023084190 |
| work_keys_str_mv | AT yuanni decompositionintegrationbasedpredictionstudyonthedevelopmenttrendoffilmindustry AT siyuanli decompositionintegrationbasedpredictionstudyonthedevelopmenttrendoffilmindustry |