Support vector machine-based open crop model (SBOCM) : case of rice production in China
Joint Authors
Ying Xue, Su
Huan, Xu
Li Jiao, Yan
Source
Saudi Journal of Biological Sciences
Issue
Vol. 24, Issue 3 (31 Mar. 2017), pp.537-547, 11 p.
Publisher
Publication Date
2017-03-31
Country of Publication
Saudi Arabia
No. of Pages
11
Main Subjects
Topics
Abstract EN
Existing crop models produce unsatisfactory simulation results and are operationally complicated.
The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation.
Using rice as the research crop, a support vector machinebased open crop model (SBOCM) was developed by integrating developmental stage and yield prediction models.
Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used.
Based on the principle of scale compatibility of modeling data, an open reading frame was designed for the dynamic daily input of meteorological data and output of rice development and yield records.
This was used to generate rice developmental stage and yield prediction models, which were integrated into the SBOCM system.
The parameters, methods, error resources, and other factors were analyzed.
Although not a crop physiology simulation model, the proposed SBOCM can be used for perennial simulation and one-year rice predictions within certain scale ranges.
It is convenient for data acquisition, regionally applicable, parametrically simple, and effective for multi-scale factor integration.
It has the potential for future integration with extensive social and economic factors to improve the prediction accuracy and practicability.
American Psychological Association (APA)
Ying Xue, Su& Huan, Xu& Li Jiao, Yan. 2017. Support vector machine-based open crop model (SBOCM) : case of rice production in China. Saudi Journal of Biological Sciences،Vol. 24, no. 3, pp.537-547.
https://search.emarefa.net/detail/BIM-761762
Modern Language Association (MLA)
Ying Xue, Su…[et al.]. Support vector machine-based open crop model (SBOCM) : case of rice production in China. Saudi Journal of Biological Sciences Vol. 24, no. 3 (Mar. 2017), pp.537-547.
https://search.emarefa.net/detail/BIM-761762
American Medical Association (AMA)
Ying Xue, Su& Huan, Xu& Li Jiao, Yan. Support vector machine-based open crop model (SBOCM) : case of rice production in China. Saudi Journal of Biological Sciences. 2017. Vol. 24, no. 3, pp.537-547.
https://search.emarefa.net/detail/BIM-761762
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 546-547
Record ID
BIM-761762