Research on Community Competition and Adaptive Genetic Algorithm for Automatic Generation of Tang Poetry. (10th April 2016)
- Record Type:
- Journal Article
- Title:
- Research on Community Competition and Adaptive Genetic Algorithm for Automatic Generation of Tang Poetry. (10th April 2016)
- Main Title:
- Research on Community Competition and Adaptive Genetic Algorithm for Automatic Generation of Tang Poetry
- Authors:
- Yang, Wujian
Cheng, Yining
He, Jie
Hu, Wenqiong
Lin, Xiaojia - Other Names:
- Jazar Reza Academic Editor.
- Abstract:
- Abstract : As there are many researches about traditional Tang poetry, among which automatically generated Tang poetry has arouse great concern in recent years. This study presents a community-based competition and adaptive genetic algorithm for automatically generating Tang poetry. The improved algorithm with community-based competition that has been added aims to maintain the diversity of genes during evolution; meanwhile, the adaptation means that the probabilities of crossover and mutation are varied from the fitness values of the Tang poetry to prevent premature convergence and generate better poems more quickly. According to the analysis of experimental results, it has been found that the improved algorithm is superior to the conventional method.
- Is Part Of:
- Mathematical problems in engineering. Volume 2016(2016)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2016(2016)
- Issue Display:
- Volume 2016, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 2016
- Issue:
- 2016
- Issue Sort Value:
- 2016-2016-2016-0000
- Page Start:
- Page End:
- Publication Date:
- 2016-04-10
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2016/4076154 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10306.xml