Ontology-based simulation in agricultural systems modeling

Beck, Howard W.; Morgan, Kelly T.; Yun-Chul, Jung; Sabine, Grunwald; Kwon, Hoyoung; Wu, J.

doi:10.1016/j.agsy.2010.04.004

Cited by 30 publications

(26 citation statements)

References 22 publications

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“…One popular definition of ontology is ‘a formal explicit specification of a shared conceptualization’ (Gruber, ; Borst, ) and more practically it can be defined as real‐world semantics and consensual terminologies interweaving human and machine understanding (Fensel, ). Recently, ontology‐based technology was used to develop a platform for simulation modeling of dynamic soil–plant–nutrient processes in agro‐ecosystems, which is called ontology‐based simulation (OntoSim) (Beck et al ., ). In the OntoSim, complex processes, such as soil organic matter decay, water fluxes, and crop growth, are defined and described by a set of symbols and mathematical equations (Figures (a) and (b)).…”

Section: Methodsmentioning

confidence: 97%

Automatic Calibration of a Hydrologic Model for Simulating Groundwater Table Fluctuations on Farms in the Everglades Agricultural Area of South Florida

Kwon

Grunwald

Beck

et al. 2014

Irrigation and Drainage

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The Shuffled Complex Evolution—Universal Algorithm (SCE‐UA) is an automatic calibration algorithm that has shown success in finding a globally optimum objective function with more efficiency than other methods. We incorporated the SCE‐UA into our novel modeling environment, utilizing an ontology‐based simulation (OntoSim‐Sugarcane) framework adapted to analyze groundwater table (WT) fluctuations and drainage practices on four farm basins in the Everglades Agricultural Area of south Florida. Utilizing two water years (WY96–97) of farm WT fluctuations observed at a portion (<16 ha) of each farm basin, two parameters—lateral hydraulic conductivities of soil profile and vertical hydraulic conductivity of underlying limestone—were automatically calibrated. Regardless of farms, the best parameter sets that minimize the objective function of daily root mean square error could be found after 1500 simulation runs. The quality of matching simulated to observed values of farm WT were further assessed by the Nash–Sutcliffe efficiency coefficient (NSE). The NSE ranged from 0.38 to 0.75 (calibration period, WY96–97) and 0.10 to 0.76 (validation period, WY98–99) on all four farms. These results indicate that this coupling strengthens the capability of OntoSim‐Sugarcane to model hydrology by objectively finding the best parameter sets. Copyright © 2014 John Wiley & Sons, Ltd.

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Section: Methodsmentioning

confidence: 97%

Automatic Calibration of a Hydrologic Model for Simulating Groundwater Table Fluctuations on Farms in the Everglades Agricultural Area of South Florida

Kwon

Grunwald

Beck

et al. 2014

Irrigation and Drainage

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“…There is little literature directly concerned with the detailed design of citrus ontology. Beck et al (2010) modeled soil, water, and nutrient management in citrus and sugarcane planting using ontology. Their results highlight the advantages of an ontologybased approach in representing the model structure, equations, and symbols.…”

Section: Related Workmentioning

confidence: 99%

“…Some researchers concentrated on making use of semantic ontology to conceptually model and integrate agricultural knowledge (Jiang et al, 2009;Beck et al, 2010;Sun et al, 2011;Cao et al, 2012;Zhang et al, 2012). Beck et al (2010) and Yuan et al (2013) chose citrus as the domain for their ontology.…”

Section: Introductionmentioning

confidence: 99%

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An ontology-based approach to integration of hilly citrus production knowledge

Wang

Yuan

et al. 2015

Computers and Electronics in Agriculture

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“…This language is powerful as "it provides system-independent formats for describing product model data, and addresses the key engineering problems of portability, interoperability, longevity and extensibility" (Andersen and Vasilakis 2007, 26). Ontology-based simulation methodologies developed in agricultural systems modelling pave the way for developments related to the latter subject (Beck et al 2010). The ontology then becomes a legitimate design tool.…”

Section: 1: Evolutionary Design Reasoning Using Computational Ontolmentioning

confidence: 99%

Evolutionary inventive problem-solving in biology and architecture: ArchiTRIZ and Material-Ontology

Hensel

Vincent

2015

Intelligent Buildings International

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Phenotypic similarity between unrelated organisms, known as convergence, is a result of shared problems of adaptation to similar environments and limited ecological range. Their separate genetic histories imply a developmental route to biological innovation. Convergence as a model of evolutionary change has been applied to biological evolutionary reasoning and functional studies. We propose its application to biologically-driven convergence for innovations in design. This route necessitates at least the comparability of architecture with biology on three levels: (1) evolutionary design reasoning (2) convergence of design solutions, and (3) ecological niche concept. These combine in ArchiTRIZ, which is introduced as a derivative of TRIZ (a Russian system of inventive problem-solving) in architecture. We are building an ontology of convergence based on wood and ceramics on ArchiTRIZ model framework called Material-Ontology [MatOnt].As a computational design tool, MatOnt can activate systematic transfer of knowledge from biology to architecture and integrate data to develop materialbased structural systems with multi-functional and adaptive properties that can be adapted for locally specific architectural applications. Convergence gives direction by highlighting natural models with potential for innovative design, some of which are discussed briefly.

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Ontology-based simulation in agricultural systems modeling

Cited by 30 publications

References 22 publications

Automatic Calibration of a Hydrologic Model for Simulating Groundwater Table Fluctuations on Farms in the Everglades Agricultural Area of South Florida

Automatic Calibration of a Hydrologic Model for Simulating Groundwater Table Fluctuations on Farms in the Everglades Agricultural Area of South Florida

An ontology-based approach to integration of hilly citrus production knowledge

Evolutionary inventive problem-solving in biology and architecture: ArchiTRIZ and Material-Ontology

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