Abstract
Nowadays, while performing their investigations, researchers often face large datasets requiring fast processing for analysis and drawing adequate conclusions. Data mining, statistical methods and big data analytics provide an impressive arsenal of tools allowing scientists to address those tasks. However, in some cases investigators need techniques enabling on the base of relatively simple and cheap measurements of easily accessible parameters to build useful and meaningful concepts of an area of research.
In our paper two classes of dynamical models aimed at revealing between-component relationships in natural systems with feedback are presented. The idea of the both models follows from the frameworks of theoretical biology and ecology, where pairwise interactions between the parts of a system are regarded as background of the system’s behavior. Both deterministic and stochastic cases are considered, that allow us to determine the direction of pairwise relationships in deterministic case and the direction and strength of relationships in stochastic one.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Margalef, R.: Perspectives in Ecological Theory. Chicago University Press, Chicago (1968)
Lidicker Jr., W.Z.: A clarification of interactions in ecological systems. Bioscience 29(8), 475–477 (1979)
Abrams, P.A.: On classifying interactions between populations. Oecologia 73(2), 272–281 (1987)
Wootton, J.T., Emmerson, M.: Measurement of interaction strength in nature. Ann. Rev. Ecol. Evol. Syst. 36, 419–444 (2005)
Shipley, B.: Cause and Correlation in Biology. Cambridge University Press, Cambridge (2004)
Spirtes, P., Glymour, C.N., Scheines, R.: Causation, Prediction, and Search. MIT Press, Cambridge (2000)
Pearl, J.: Causality: Models, Reasoning, and Inference. Cambridge University Press, Cambridge (2009)
Bollen, K.A., Pearl, J.: Eight myths about causality and structural equation models. In: Morgan, S.L. (ed.) Handbook of Causal Analysis for Social Research, pp. 301–328. Springer, Dordrecht (2013). https://doi.org/10.1007/978-94-007-6094-3_15
Elwert, F.: Graphical causal models. In: Morgan, S.L. (ed.) Handbook of Causal Analysis for Social Research, pp. 245–273. Springer, Dordrecht (2013). https://doi.org/10.1007/978-94-007-6094-3_13
Menzies, P.: Causal models, token causation, and processes. Philos. Sci. 71(5), 820–832 (2004)
Zholtkevych, G.N., Bespalov, Y.G., Nosov, K.V., Abhishek, M.: Discrete modeling of dynamics of zooplankton community at the different stages of an antropogeneous eutrophication. Acta. Biotheor. 61(4), 449–465 (2013)
Kalman, R.E., Falb, P.L., Arbib, M.A.: Topics in Mathematical System Theory. McGraw-Hill, New York (1969)
Blalock, H.M.: Social Statistics. McGraw-Hill, New York (1972)
Boyd, D., Ellison, N.: Social network sites: definition, history, and scholarsh. J. Comput. Mediated Commun. 13(1), 210–230 (2007)
Di Caprio, D., Santos-Arteaga, F.J., Tavana, M.: Self-organizing social networks by preference similarity and the networking capacity of their users. Procedia Comput. Sci. 83, 496–503 (2016)
Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mobile. Netw. Appl. 19, 171–209 (2014)
Cole, T.J., Bellizzi, M.C., Flegal, K.M., Dietz, W.H.: Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ Clin. Res. 320, 1–6 (2000)
ICES: Report of the Benchmark Workshop on Arctic Stocks (WKARCT), 26–30 January 2015. ICES Headquarters, Denmark. ICES CM 2015/ACOM:30 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Zholtkevych, G.N. et al. (2017). Descriptive Models of System Dynamics. In: Ginige, A., et al. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2016. Communications in Computer and Information Science, vol 783. Springer, Cham. https://doi.org/10.1007/978-3-319-69965-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-69965-3_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69964-6
Online ISBN: 978-3-319-69965-3
eBook Packages: Computer ScienceComputer Science (R0)