Stochastic similarities between hydrometeorogical and art processes for optimizing architecture and landscape aesthetic parameters

R. Ioannidis, P. Dimitriadis, G.-F. Sargentis, E. Frangedaki, T. Iliopoulou, and D. Koutsoyiannis, Stochastic similarities between hydrometeorogical and art processes for optimizing architecture and landscape aesthetic parameters, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-11403, European Geosciences Union, 2019.

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[English]

Stochastics help develop a unified perception for natural phenomena and expel dichotomies like random vs. deterministic, as both randomness and predictability coexist and are intrinsic to natural systems which can be deterministic and random at the same time, depending on the prediction horizon and the time scale. The high complexity and uncertainty of natural processes has been long identified through observations as well as extended analyses of hydrometeorological processes such as temperature, humidity, surface wind, precipitation, atmospheric pressure, river discharges etc. All these processes seem to exhibit high unpredictability due to the clustering of events. Art is a mix of determinism (e.g., certain rules have to be followed) and stochasticity (e.g., creativity and inspiration). However, in this analysis we analyse each artistic work in a stochastic approach, and attempt to identify their degree of intrinsic uncertainty. The stochastic analysis includes the investigation of possible Hurst-Kolmogorov behaviour in the art of different periods (visual arts, music, poetry) and of relationships with natural processes. Based on the stochastic analysis of different artworks, we make an image analysis of architectural elements in the landscape in order to formulate an indicator that can be used in engineering.

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This research has been supported by the OptArch project: "Optimization Driven Architectural Design of Structures" (No: 689983) belonging to the Marie Skłodowska-Curie Actions (MSCA) Research and Innovation Staff Exchange (RISE) H2020-MSCA-RISE-2015.