TY - GEN
T1 - A SysML-based simulation model aggregation framework for seedling propagation system
AU - Meng, Chao
AU - Kim, Sojung
AU - Son, Young Jun
AU - Kubota, Chieri
PY - 2013
Y1 - 2013
N2 - This paper proposes a Systems Modeling Language (SysML)-based simulation model aggregation framework to develop aggregated simulation models with high accuracy. The framework consists of three major steps: 1) system conceptual modeling, 2) simulation modeling, and 3) additive regression model-based parameter estimation. SysML is first used to construct the system conceptual model for a generic seedling propagation system in terms of system structure and activities in a hierarchical manner (i.e. low, medium and high levels). Simulation models conforming to the conceptual model are then constructed in Arena. An additive regression model-based approach is proposed to estimate parameters for the aggregated simulation model. The proposed framework is demonstrated via one of the largest grafted seedling propagation systems in North America. The results reveal that 1) the proposed framework allows us to construct accurate but computationally affordable simulation models for seedling propagation system, and 2) model aggregation increases the randomness of simulation outputs.
AB - This paper proposes a Systems Modeling Language (SysML)-based simulation model aggregation framework to develop aggregated simulation models with high accuracy. The framework consists of three major steps: 1) system conceptual modeling, 2) simulation modeling, and 3) additive regression model-based parameter estimation. SysML is first used to construct the system conceptual model for a generic seedling propagation system in terms of system structure and activities in a hierarchical manner (i.e. low, medium and high levels). Simulation models conforming to the conceptual model are then constructed in Arena. An additive regression model-based approach is proposed to estimate parameters for the aggregated simulation model. The proposed framework is demonstrated via one of the largest grafted seedling propagation systems in North America. The results reveal that 1) the proposed framework allows us to construct accurate but computationally affordable simulation models for seedling propagation system, and 2) model aggregation increases the randomness of simulation outputs.
UR - http://www.scopus.com/inward/record.url?scp=84894121473&partnerID=8YFLogxK
U2 - 10.1109/WSC.2013.6721595
DO - 10.1109/WSC.2013.6721595
M3 - Conference contribution
AN - SCOPUS:84894121473
SN - 9781479939503
T3 - Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013
SP - 2180
EP - 2191
BT - Proceedings of the 2013 Winter Simulation Conference - Simulation
T2 - 2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013
Y2 - 8 December 2013 through 11 December 2013
ER -