Hurricane genesis modelling based on the relationship between solar activity and hurricanes
Authorized Users Only
2017
Authors
Vyklyuk, YaroslavRadovanović, Milan M.
Milovanović, Boško
Leko, Taras
Milenković, Milan
Milošević, Zoran
Milanović Pešić, Ana
Jakovljević, Dejana M.
Article (Published version)
,
Springer Science+Business Media Dordrecht
Metadata
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The work examines the potential causative link between the flow of charged particles that are coming from the Sun and hurricanes. For establishing eventual link, the method of correlation analysis is applied, but with the phase shift of 0–5 days. There are nine parameters which are observed as an input, and daily values of the hurricane phenomenon are observed as an output in the period May–October 1999–2013. The results that have been obtained are considerably weak, leading to the need of applying the method of nonlinear analysis. The R/S analysis was conducted to determine the degree of randomness for time series of input and output parameters. The calculated Hurst index of variables X4–X9 is persistent (0.71–0.96). That allows us to conclude that the dynamics of these time series is heavily dependent on the same factors or on each other. Unlike the previous index, we have concluded that the behavior of high-energy protons (X1–X3) and the number of hurricane time series are completel...y stochastic. The problem of finding hidden dependencies in large databases refers to problems of data mining. The Sugeno function of zero order was selected as a method of output fuzzy system. Bearing in mind the available equipment, the models had to be shortened to the phase shift of 0–3 days. The “brute-force attack” method was used to find the most significant factors from all data. Within the experiments, six input factors were calculated which became the basis for building the final ANFIS models. These models can predict 22–26 % of the hurricanes.
Keywords:
Solar activity / Hurricanes / Hurst index / ANFIS modelsSource:
Natural Hazards, 2017, 85, 2, 1043-1062Publisher:
- Springer Netherlands
Funding / projects:
- Geography of Serbia (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-47007)
DOI: 10.1007/s11069-016-2620-6
ISSN: 1573-0840
WoS: 000391611900021
Scopus: 2-s2.0-84991672199
Institution/Community
Географски институт „Јован Цвијић“ САНУ / Geographical Institute Jovan Cvijić SASATY - JOUR AU - Vyklyuk, Yaroslav AU - Radovanović, Milan M. AU - Milovanović, Boško AU - Leko, Taras AU - Milenković, Milan AU - Milošević, Zoran AU - Milanović Pešić, Ana AU - Jakovljević, Dejana M. PY - 2017 UR - https://dais.sanu.ac.rs/123456789/1058 AB - The work examines the potential causative link between the flow of charged particles that are coming from the Sun and hurricanes. For establishing eventual link, the method of correlation analysis is applied, but with the phase shift of 0–5 days. There are nine parameters which are observed as an input, and daily values of the hurricane phenomenon are observed as an output in the period May–October 1999–2013. The results that have been obtained are considerably weak, leading to the need of applying the method of nonlinear analysis. The R/S analysis was conducted to determine the degree of randomness for time series of input and output parameters. The calculated Hurst index of variables X4–X9 is persistent (0.71–0.96). That allows us to conclude that the dynamics of these time series is heavily dependent on the same factors or on each other. Unlike the previous index, we have concluded that the behavior of high-energy protons (X1–X3) and the number of hurricane time series are completely stochastic. The problem of finding hidden dependencies in large databases refers to problems of data mining. The Sugeno function of zero order was selected as a method of output fuzzy system. Bearing in mind the available equipment, the models had to be shortened to the phase shift of 0–3 days. The “brute-force attack” method was used to find the most significant factors from all data. Within the experiments, six input factors were calculated which became the basis for building the final ANFIS models. These models can predict 22–26 % of the hurricanes. PB - Springer Netherlands T2 - Natural Hazards T1 - Hurricane genesis modelling based on the relationship between solar activity and hurricanes SP - 1043 EP - 1062 VL - 85 IS - 2 DO - 10.1007/s11069-016-2620-6 UR - https://hdl.handle.net/21.15107/rcub_dais_1058 ER -
@article{ author = "Vyklyuk, Yaroslav and Radovanović, Milan M. and Milovanović, Boško and Leko, Taras and Milenković, Milan and Milošević, Zoran and Milanović Pešić, Ana and Jakovljević, Dejana M.", year = "2017", abstract = "The work examines the potential causative link between the flow of charged particles that are coming from the Sun and hurricanes. For establishing eventual link, the method of correlation analysis is applied, but with the phase shift of 0–5 days. There are nine parameters which are observed as an input, and daily values of the hurricane phenomenon are observed as an output in the period May–October 1999–2013. The results that have been obtained are considerably weak, leading to the need of applying the method of nonlinear analysis. The R/S analysis was conducted to determine the degree of randomness for time series of input and output parameters. The calculated Hurst index of variables X4–X9 is persistent (0.71–0.96). That allows us to conclude that the dynamics of these time series is heavily dependent on the same factors or on each other. Unlike the previous index, we have concluded that the behavior of high-energy protons (X1–X3) and the number of hurricane time series are completely stochastic. The problem of finding hidden dependencies in large databases refers to problems of data mining. The Sugeno function of zero order was selected as a method of output fuzzy system. Bearing in mind the available equipment, the models had to be shortened to the phase shift of 0–3 days. The “brute-force attack” method was used to find the most significant factors from all data. Within the experiments, six input factors were calculated which became the basis for building the final ANFIS models. These models can predict 22–26 % of the hurricanes.", publisher = "Springer Netherlands", journal = "Natural Hazards", title = "Hurricane genesis modelling based on the relationship between solar activity and hurricanes", pages = "1043-1062", volume = "85", number = "2", doi = "10.1007/s11069-016-2620-6", url = "https://hdl.handle.net/21.15107/rcub_dais_1058" }
Vyklyuk, Y., Radovanović, M. M., Milovanović, B., Leko, T., Milenković, M., Milošević, Z., Milanović Pešić, A.,& Jakovljević, D. M.. (2017). Hurricane genesis modelling based on the relationship between solar activity and hurricanes. in Natural Hazards Springer Netherlands., 85(2), 1043-1062. https://doi.org/10.1007/s11069-016-2620-6 https://hdl.handle.net/21.15107/rcub_dais_1058
Vyklyuk Y, Radovanović MM, Milovanović B, Leko T, Milenković M, Milošević Z, Milanović Pešić A, Jakovljević DM. Hurricane genesis modelling based on the relationship between solar activity and hurricanes. in Natural Hazards. 2017;85(2):1043-1062. doi:10.1007/s11069-016-2620-6 https://hdl.handle.net/21.15107/rcub_dais_1058 .
Vyklyuk, Yaroslav, Radovanović, Milan M., Milovanović, Boško, Leko, Taras, Milenković, Milan, Milošević, Zoran, Milanović Pešić, Ana, Jakovljević, Dejana M., "Hurricane genesis modelling based on the relationship between solar activity and hurricanes" in Natural Hazards, 85, no. 2 (2017):1043-1062, https://doi.org/10.1007/s11069-016-2620-6 ., https://hdl.handle.net/21.15107/rcub_dais_1058 .