文章基本信息

标题：Identification of virtual plants using bayesian networks based on parametric L-system
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作者：Suhartono Suhartono ; Fachrul Kurniawan ; Bahtiar Imran 等
期刊名称：IJAIN (International Journal of Advances in Intelligent Informatics)
印刷版ISSN：2442-6571
电子版ISSN：2548-3161
出版年度：2018
卷号：4
期号：1
页码：40-52
DOI：10.26555/ijain.v4i1.157
语种：English
出版社：Universitas Ahmad Dahlan
摘要：Parametric L-System is a method for modelling virtual plants. Virtual plant modelling consists of components of axiom and production rules for alphabets in parametric L-System. Generally, to get the alphabet in parametric L-System, one would guess the production rules and perform a modification on the axiom. The objective of this study was to build virtual plant that was affected by the environment. The use of Bayesian networks was to extract the information structure of the growth of a plant as affected by the environment. The next step was to use the information to generate axiom and production rules for the alphabets in the parametric L-System. The results of program testing showed that among the five treatments, the combination of organic and inorganic fertilizer was the environmental factor for the experiment. The highest result of 6.41 during evaluation of the virtual plant came from the treatment with combination of high level of organic fertilizer and medium level of inorganic fertilizer. Mean error between real plant and virtual plan was 9.45 %.
关键词：plant growth modeling; Bayesian network; environment; distribution probability and L-system