TY  - JOUR
AU  - Malinović-Milićević, Slavica
AU  - Radovanović, Milan M.
AU  - Radenković, Sonja D.
AU  - Vyklyuk, Yaroslav
AU  - Milovanović, Boško
AU  - Milanović Pešić, Ana
AU  - Milenković, Milan
AU  - Popović, Vladimir
AU  - Petrović, Marko
AU  - Sydor, Petro
AU  - Gajić, Mirjana
PY  - 2023
UR  - https://dais.sanu.ac.rs/123456789/14049
AB  - This research is devoted to the determination of hidden dependencies between the flow of particles that come from the Sun and precipitation-induced floods in the United Kingdom (UK). The analysis covers 20 flood events during the period from October 2001 to December 2019. The parameters of solar activity were used as model input data, while precipitations data in the period 10 days before and during each flood event were used as model output. The time lag of 0–9 days was taken into account in the research. Correlation analysis was conducted to determine the degree of randomness for the time series of input and output parameters. For establishing a potential causative link, machine learning classification predictive modeling was applied. Two approaches, the decision tree, and the random forest were used. We analyzed the accuracy of classification models forecast from 0 to 9 days in advance. It was found that the most important factors for flood forecasting are proton density with a time lag of 9, differential proton flux in the range of 310–580 keV, and ion temperature. Research in this paper has shown that the decision tree model is more accurate and adequate in predicting the appearance of precipitation-induced floods up to 9 days ahead with an accuracy of 91%. The results of this study confirmed that by increasing technical capabilities, using improved machine learning techniques and large data sets, it is possible to improve the understanding of the physical link between the solar wind and tropospheric weather and help improve severe weather forecasting.
PB  - MDPI AG
T2  - Mathematics
T1  - Application of Solar Activity Time Series in Machine Learning Predictive Modeling of Precipitation-Induced Floods
SP  - 795
VL  - 11
IS  - 4
DO  - 10.3390/math11040795
UR  - https://hdl.handle.net/21.15107/rcub_dais_14049
ER  - 

@article{
author = "Malinović-Milićević, Slavica and Radovanović, Milan M. and Radenković, Sonja D. and Vyklyuk, Yaroslav and Milovanović, Boško and Milanović Pešić, Ana and Milenković, Milan and Popović, Vladimir and Petrović, Marko and Sydor, Petro and Gajić, Mirjana",
year = "2023",
abstract = "This research is devoted to the determination of hidden dependencies between the flow of particles that come from the Sun and precipitation-induced floods in the United Kingdom (UK). The analysis covers 20 flood events during the period from October 2001 to December 2019. The parameters of solar activity were used as model input data, while precipitations data in the period 10 days before and during each flood event were used as model output. The time lag of 0–9 days was taken into account in the research. Correlation analysis was conducted to determine the degree of randomness for the time series of input and output parameters. For establishing a potential causative link, machine learning classification predictive modeling was applied. Two approaches, the decision tree, and the random forest were used. We analyzed the accuracy of classification models forecast from 0 to 9 days in advance. It was found that the most important factors for flood forecasting are proton density with a time lag of 9, differential proton flux in the range of 310–580 keV, and ion temperature. Research in this paper has shown that the decision tree model is more accurate and adequate in predicting the appearance of precipitation-induced floods up to 9 days ahead with an accuracy of 91%. The results of this study confirmed that by increasing technical capabilities, using improved machine learning techniques and large data sets, it is possible to improve the understanding of the physical link between the solar wind and tropospheric weather and help improve severe weather forecasting.",
publisher = "MDPI AG",
journal = "Mathematics",
title = "Application of Solar Activity Time Series in Machine Learning Predictive Modeling of Precipitation-Induced Floods",
pages = "795",
volume = "11",
number = "4",
doi = "10.3390/math11040795",
url = "https://hdl.handle.net/21.15107/rcub_dais_14049"
}

Malinović-Milićević, S., Radovanović, M. M., Radenković, S. D., Vyklyuk, Y., Milovanović, B., Milanović Pešić, A., Milenković, M., Popović, V., Petrović, M., Sydor, P.,& Gajić, M.. (2023). Application of Solar Activity Time Series in Machine Learning Predictive Modeling of Precipitation-Induced Floods. in Mathematics
MDPI AG., 11(4), 795.
https://doi.org/10.3390/math11040795
https://hdl.handle.net/21.15107/rcub_dais_14049

Malinović-Milićević S, Radovanović MM, Radenković SD, Vyklyuk Y, Milovanović B, Milanović Pešić A, Milenković M, Popović V, Petrović M, Sydor P, Gajić M. Application of Solar Activity Time Series in Machine Learning Predictive Modeling of Precipitation-Induced Floods. in Mathematics. 2023;11(4):795.
doi:10.3390/math11040795
https://hdl.handle.net/21.15107/rcub_dais_14049 .

Malinović-Milićević, Slavica, Radovanović, Milan M., Radenković, Sonja D., Vyklyuk, Yaroslav, Milovanović, Boško, Milanović Pešić, Ana, Milenković, Milan, Popović, Vladimir, Petrović, Marko, Sydor, Petro, Gajić, Mirjana, "Application of Solar Activity Time Series in Machine Learning Predictive Modeling of Precipitation-Induced Floods" in Mathematics, 11, no. 4 (2023):795,
https://doi.org/10.3390/math11040795 .,
https://hdl.handle.net/21.15107/rcub_dais_14049 .

TY  - JOUR
AU  - Nina, Aleksandra
AU  - Milovanović, Boško
AU  - Malinović-Milićević, Slavica
AU  - Pulinets, Sergey
PY  - 2023
UR  - https://dais.sanu.ac.rs/123456789/14585
PB  - Switzerland : Frontiers Media
T2  - Frontiers in Environmental Science
T1  - Editorial: Atmospheric disturbances: responses to phenomena from lithosphere to outer space
VL  - 11
IS  - 1199573
DO  - 10.3389/fenvs.2023.1199573
UR  - https://hdl.handle.net/21.15107/rcub_dais_14585
ER  - 

@article{
author = "Nina, Aleksandra and Milovanović, Boško and Malinović-Milićević, Slavica and Pulinets, Sergey",
year = "2023",
publisher = "Switzerland : Frontiers Media",
journal = "Frontiers in Environmental Science",
title = "Editorial: Atmospheric disturbances: responses to phenomena from lithosphere to outer space",
volume = "11",
number = "1199573",
doi = "10.3389/fenvs.2023.1199573",
url = "https://hdl.handle.net/21.15107/rcub_dais_14585"
}

Nina, A., Milovanović, B., Malinović-Milićević, S.,& Pulinets, S.. (2023). Editorial: Atmospheric disturbances: responses to phenomena from lithosphere to outer space. in Frontiers in Environmental Science
Switzerland : Frontiers Media., 11(1199573).
https://doi.org/10.3389/fenvs.2023.1199573
https://hdl.handle.net/21.15107/rcub_dais_14585

Nina A, Milovanović B, Malinović-Milićević S, Pulinets S. Editorial: Atmospheric disturbances: responses to phenomena from lithosphere to outer space. in Frontiers in Environmental Science. 2023;11(1199573).
doi:10.3389/fenvs.2023.1199573
https://hdl.handle.net/21.15107/rcub_dais_14585 .

Nina, Aleksandra, Milovanović, Boško, Malinović-Milićević, Slavica, Pulinets, Sergey, "Editorial: Atmospheric disturbances: responses to phenomena from lithosphere to outer space" in Frontiers in Environmental Science, 11, no. 1199573 (2023),
https://doi.org/10.3389/fenvs.2023.1199573 .,
https://hdl.handle.net/21.15107/rcub_dais_14585 .

TY  - CONF
AU  - Radovanović, Milan M.
AU  - Malinović-Milićević, Slavica
AU  - Radenković, Sonja
AU  - Milenković, Milan
AU  - Milovanović, Boško
AU  - Milanović Pešić, Ana
AU  - Popović, Vladimir
PY  - 2022
UR  - https://dais.sanu.ac.rs/123456789/13864
AB  - This paper investigates hidden dependencies between the flow of particles coming from the Sun and 20 flood events in the United Kingdom (UK). The dataset analyzed in the study contains historical data covered on the daily level for the period October 2001 – December 2019. Solar activity parameters were used as model input, while rainfall data 10 days before and during each flood event were used as model output. To determine the degree of randomness for the time series of input and output parameters the correlation analysis has been performed. Machine Learning Classification Predictive Modelling is then applied to try to establish an eventual link between input and output data. Specifically, the decision tree, as the machine learning approach is used. In addition, it is analyzed the accuracy of classification models forecast. It is found that the most important factors for flood forecasting are proton density, differential proton flux in the range of 310-580 keV, and ion temperature. Research in this paper has shown that the classification model is accurate and adequate to predict the appearance of precipitation-induced floods.
PB  - Russian Federation : Faculty of Geography, Lomonosov Moscow State University
C3  - Рациональное природопользование: традиции и иновации. Материалы III Международной конференци
T1  - Influence of Space Weather on Precipitation-Induced Floods – Applying of Solar Activity Time Series in the Prediction of Precipitation-Induced Floods by Using the Machine Learning
SP  - 90
EP  - 97
UR  - https://hdl.handle.net/21.15107/rcub_dais_13864
ER  - 

@conference{
author = "Radovanović, Milan M. and Malinović-Milićević, Slavica and Radenković, Sonja and Milenković, Milan and Milovanović, Boško and Milanović Pešić, Ana and Popović, Vladimir",
year = "2022",
abstract = "This paper investigates hidden dependencies between the flow of particles coming from the Sun and 20 flood events in the United Kingdom (UK). The dataset analyzed in the study contains historical data covered on the daily level for the period October 2001 – December 2019. Solar activity parameters were used as model input, while rainfall data 10 days before and during each flood event were used as model output. To determine the degree of randomness for the time series of input and output parameters the correlation analysis has been performed. Machine Learning Classification Predictive Modelling is then applied to try to establish an eventual link between input and output data. Specifically, the decision tree, as the machine learning approach is used. In addition, it is analyzed the accuracy of classification models forecast. It is found that the most important factors for flood forecasting are proton density, differential proton flux in the range of 310-580 keV, and ion temperature. Research in this paper has shown that the classification model is accurate and adequate to predict the appearance of precipitation-induced floods.",
publisher = "Russian Federation : Faculty of Geography, Lomonosov Moscow State University",
journal = "Рациональное природопользование: традиции и иновации. Материалы III Международной конференци",
title = "Influence of Space Weather on Precipitation-Induced Floods – Applying of Solar Activity Time Series in the Prediction of Precipitation-Induced Floods by Using the Machine Learning",
pages = "90-97",
url = "https://hdl.handle.net/21.15107/rcub_dais_13864"
}

Radovanović, M. M., Malinović-Milićević, S., Radenković, S., Milenković, M., Milovanović, B., Milanović Pešić, A.,& Popović, V.. (2022). Influence of Space Weather on Precipitation-Induced Floods – Applying of Solar Activity Time Series in the Prediction of Precipitation-Induced Floods by Using the Machine Learning. in Рациональное природопользование: традиции и иновации. Материалы III Международной конференци
Russian Federation : Faculty of Geography, Lomonosov Moscow State University., 90-97.
https://hdl.handle.net/21.15107/rcub_dais_13864

Radovanović MM, Malinović-Milićević S, Radenković S, Milenković M, Milovanović B, Milanović Pešić A, Popović V. Influence of Space Weather on Precipitation-Induced Floods – Applying of Solar Activity Time Series in the Prediction of Precipitation-Induced Floods by Using the Machine Learning. in Рациональное природопользование: традиции и иновации. Материалы III Международной конференци. 2022;:90-97.
https://hdl.handle.net/21.15107/rcub_dais_13864 .

Radovanović, Milan M., Malinović-Milićević, Slavica, Radenković, Sonja, Milenković, Milan, Milovanović, Boško, Milanović Pešić, Ana, Popović, Vladimir, "Influence of Space Weather on Precipitation-Induced Floods – Applying of Solar Activity Time Series in the Prediction of Precipitation-Induced Floods by Using the Machine Learning" in Рациональное природопользование: традиции и иновации. Материалы III Международной конференци (2022):90-97,
https://hdl.handle.net/21.15107/rcub_dais_13864 .

TY  - JOUR
AU  - Vyklyuk, Yaroslav
AU  - Radovanović, Milan M.
AU  - Milovanović, Boško
AU  - Milenković, Milan
AU  - Petrović, Marko
AU  - Doljak, Dejan
AU  - Malinović-Milićević, Slavica
AU  - Vuković, Natalia
AU  - Vujko, Aleksandra
AU  - Matsiuk, Nataliia
AU  - Mukherjee, Saumitra
PY  - 2019
UR  - https://dais.sanu.ac.rs/123456789/13408
AB  - This research is devoted to the determination of the causal relationship between the flow of particles that are coming from the Sun and the hurricanes Irma, Jose, and Katia. To accomplish this, the lag correlation analysis was performed. High correlation coefficients confirmed a preliminary conclusion about the relationship between solar activities and the hurricane phenomenon, which allows further research. Five parameters i.e. characteristics of solar activity (10.7 cm solar radio flux (F10.7), the flows of protons and electrons with maximum energy, speed and density of solar wind particles) were chosen as model input, while the wind speed and air pressure of Irma, Jose, and Katia hurricanes were used as model output. Input data were sampled to a six hours interval in order to adapt the time interval to the observed data about hurricanes, in the period between September 28 and December 21, 2017. As a result of the preliminary analysis, using 12,274,264 linear models by parallel calculations, six of them were chosen as best. The identified lags were the basis for refinement of models with the artificial neural networks. Multilayer perceptrons with back propagation and recurrent LSTM have been chosen as commonly used artificial neural networks. Comparison of the accuracy of both linear and artificial neural networks results confirmed the adequacy of these models and made it possible to take into account the dynamics of the solar wind. Sensitivity analysis has shown that F10.7 has the greatest impact on the wind speed of the hurricanes. Despite low sensitivity of pressure to change the parameters of the solar wind, their strong fluctuations can cause a sharp decrease in pressure, and therefore the appearance of hurricanes.
PB  - Switzerland : Springer Nature
T2  - Astrophysics and Space Science
T1  - Space weather and hurricanes Irma, Jose and Katia
VL  - 364
IS  - 154
DO  - 10.1007/s10509-019-3646-5
UR  - https://hdl.handle.net/21.15107/rcub_dais_13408
ER  - 

@article{
author = "Vyklyuk, Yaroslav and Radovanović, Milan M. and Milovanović, Boško and Milenković, Milan and Petrović, Marko and Doljak, Dejan and Malinović-Milićević, Slavica and Vuković, Natalia and Vujko, Aleksandra and Matsiuk, Nataliia and Mukherjee, Saumitra",
year = "2019",
abstract = "This research is devoted to the determination of the causal relationship between the flow of particles that are coming from the Sun and the hurricanes Irma, Jose, and Katia. To accomplish this, the lag correlation analysis was performed. High correlation coefficients confirmed a preliminary conclusion about the relationship between solar activities and the hurricane phenomenon, which allows further research. Five parameters i.e. characteristics of solar activity (10.7 cm solar radio flux (F10.7), the flows of protons and electrons with maximum energy, speed and density of solar wind particles) were chosen as model input, while the wind speed and air pressure of Irma, Jose, and Katia hurricanes were used as model output. Input data were sampled to a six hours interval in order to adapt the time interval to the observed data about hurricanes, in the period between September 28 and December 21, 2017. As a result of the preliminary analysis, using 12,274,264 linear models by parallel calculations, six of them were chosen as best. The identified lags were the basis for refinement of models with the artificial neural networks. Multilayer perceptrons with back propagation and recurrent LSTM have been chosen as commonly used artificial neural networks. Comparison of the accuracy of both linear and artificial neural networks results confirmed the adequacy of these models and made it possible to take into account the dynamics of the solar wind. Sensitivity analysis has shown that F10.7 has the greatest impact on the wind speed of the hurricanes. Despite low sensitivity of pressure to change the parameters of the solar wind, their strong fluctuations can cause a sharp decrease in pressure, and therefore the appearance of hurricanes.",
publisher = "Switzerland : Springer Nature",
journal = "Astrophysics and Space Science",
title = "Space weather and hurricanes Irma, Jose and Katia",
volume = "364",
number = "154",
doi = "10.1007/s10509-019-3646-5",
url = "https://hdl.handle.net/21.15107/rcub_dais_13408"
}

Vyklyuk, Y., Radovanović, M. M., Milovanović, B., Milenković, M., Petrović, M., Doljak, D., Malinović-Milićević, S., Vuković, N., Vujko, A., Matsiuk, N.,& Mukherjee, S.. (2019). Space weather and hurricanes Irma, Jose and Katia. in Astrophysics and Space Science
Switzerland : Springer Nature., 364(154).
https://doi.org/10.1007/s10509-019-3646-5
https://hdl.handle.net/21.15107/rcub_dais_13408

Vyklyuk Y, Radovanović MM, Milovanović B, Milenković M, Petrović M, Doljak D, Malinović-Milićević S, Vuković N, Vujko A, Matsiuk N, Mukherjee S. Space weather and hurricanes Irma, Jose and Katia. in Astrophysics and Space Science. 2019;364(154).
doi:10.1007/s10509-019-3646-5
https://hdl.handle.net/21.15107/rcub_dais_13408 .

Vyklyuk, Yaroslav, Radovanović, Milan M., Milovanović, Boško, Milenković, Milan, Petrović, Marko, Doljak, Dejan, Malinović-Milićević, Slavica, Vuković, Natalia, Vujko, Aleksandra, Matsiuk, Nataliia, Mukherjee, Saumitra, "Space weather and hurricanes Irma, Jose and Katia" in Astrophysics and Space Science, 364, no. 154 (2019),
https://doi.org/10.1007/s10509-019-3646-5 .,
https://hdl.handle.net/21.15107/rcub_dais_13408 .

TY  - JOUR
AU  - Vyklyuk, Yaroslav
AU  - Radovanović, Milan. M.
AU  - Stanojević, Gorica B.
AU  - Milovanović, Boško
AU  - Taras, Leko
AU  - Milenković, Milan
AU  - Petrović, Marko
AU  - Yamashkin, Anatoly A.
AU  - Milanović Pešić, Ana
AU  - Jakovljević, Dejana
AU  - Malinović Milićević, Slavica
PY  - 2018
UR  - https://dais.sanu.ac.rs/123456789/13855
AB  - This research presents improved results on modelling relationship between the flow of charged particles that are coming from the Sun and hurricanes. For establishing eventual link, the methods of Big Data, such as Adaptive Neuro Fuzzy Inference System (ANFIS), Parallel Calculations, Fractal analysis etc., are applied. The parameters of solar activity were used as model input data, while data on hurricane phenomenon were used as model output, and both of these on daily level for May–October in period 1999–2013. The nonlinear R/S analysis was conducted to determine the degree of randomness for time series of input and output parameters. The time lag of 0–10 days was taken into account in the research. It led to growing input parameters up to 99. The problem of finding hidden dependencies in large databases refers to the problems of Data Mining. The ANFIS with Sugeno function of zero order was selected as a method of output fuzzy system. The “brute-force attack” method was used to find the most significant factors from all data. To do this, more than 3 million ANFIS models were tested on Computer Cluster using Parallel Calculation. Within the experiments, eight input factors were calculated as a base for building the final ANFIS models. These models can predict up to 39% of the hurricanes. This means, if causal link exists, approximately every third penetration of charged particles from coronary hole(s) or/and from the energetic region(s) toward the Earth precede the hurricanes.
PB  - Netherlands : Elsevier Ltd.
T2  - Journal of Atmospheric and Solar-Terrestrial Physics
T1  - Hurricane genesis modeling based on the relationship between solar activity and hurricanes II
SP  - 159
EP  - 164
VL  - 180
DO  - 10.1016/j.jastp.2017.09.008
UR  - https://hdl.handle.net/21.15107/rcub_dais_13855
ER  - 

@article{
author = "Vyklyuk, Yaroslav and Radovanović, Milan. M. and Stanojević, Gorica B. and Milovanović, Boško and Taras, Leko and Milenković, Milan and Petrović, Marko and Yamashkin, Anatoly A. and Milanović Pešić, Ana and Jakovljević, Dejana and Malinović Milićević, Slavica",
year = "2018",
abstract = "This research presents improved results on modelling relationship between the flow of charged particles that are coming from the Sun and hurricanes. For establishing eventual link, the methods of Big Data, such as Adaptive Neuro Fuzzy Inference System (ANFIS), Parallel Calculations, Fractal analysis etc., are applied. The parameters of solar activity were used as model input data, while data on hurricane phenomenon were used as model output, and both of these on daily level for May–October in period 1999–2013. The nonlinear R/S analysis was conducted to determine the degree of randomness for time series of input and output parameters. The time lag of 0–10 days was taken into account in the research. It led to growing input parameters up to 99. The problem of finding hidden dependencies in large databases refers to the problems of Data Mining. The ANFIS with Sugeno function of zero order was selected as a method of output fuzzy system. The “brute-force attack” method was used to find the most significant factors from all data. To do this, more than 3 million ANFIS models were tested on Computer Cluster using Parallel Calculation. Within the experiments, eight input factors were calculated as a base for building the final ANFIS models. These models can predict up to 39% of the hurricanes. This means, if causal link exists, approximately every third penetration of charged particles from coronary hole(s) or/and from the energetic region(s) toward the Earth precede the hurricanes.",
publisher = "Netherlands : Elsevier Ltd.",
journal = "Journal of Atmospheric and Solar-Terrestrial Physics",
title = "Hurricane genesis modeling based on the relationship between solar activity and hurricanes II",
pages = "159-164",
volume = "180",
doi = "10.1016/j.jastp.2017.09.008",
url = "https://hdl.handle.net/21.15107/rcub_dais_13855"
}

Vyklyuk, Y., Radovanović, Milan. M., Stanojević, G. B., Milovanović, B., Taras, L., Milenković, M., Petrović, M., Yamashkin, A. A., Milanović Pešić, A., Jakovljević, D.,& Malinović Milićević, S.. (2018). Hurricane genesis modeling based on the relationship between solar activity and hurricanes II. in Journal of Atmospheric and Solar-Terrestrial Physics
Netherlands : Elsevier Ltd.., 180, 159-164.
https://doi.org/10.1016/j.jastp.2017.09.008
https://hdl.handle.net/21.15107/rcub_dais_13855

Vyklyuk Y, Radovanović MM, Stanojević GB, Milovanović B, Taras L, Milenković M, Petrović M, Yamashkin AA, Milanović Pešić A, Jakovljević D, Malinović Milićević S. Hurricane genesis modeling based on the relationship between solar activity and hurricanes II. in Journal of Atmospheric and Solar-Terrestrial Physics. 2018;180:159-164.
doi:10.1016/j.jastp.2017.09.008
https://hdl.handle.net/21.15107/rcub_dais_13855 .

Vyklyuk, Yaroslav, Radovanović, Milan. M., Stanojević, Gorica B., Milovanović, Boško, Taras, Leko, Milenković, Milan, Petrović, Marko, Yamashkin, Anatoly A., Milanović Pešić, Ana, Jakovljević, Dejana, Malinović Milićević, Slavica, "Hurricane genesis modeling based on the relationship between solar activity and hurricanes II" in Journal of Atmospheric and Solar-Terrestrial Physics, 180 (2018):159-164,
https://doi.org/10.1016/j.jastp.2017.09.008 .,
https://hdl.handle.net/21.15107/rcub_dais_13855 .

TY  - JOUR
AU  - Milovanović, Boško
AU  - Ducić, Vladan
AU  - Radovanović, Milan
AU  - Milivojević, Milovan
PY  - 2017
UR  - https://dais.sanu.ac.rs/123456789/12570
AB  - The paper presents a concise overview of the theoretical framework on which climate classifications are based. Beside short review of climate classifications, namely climatic regionalization for Serbia (or wider area including Serbia), main deficiency of these research was ascertained (which primarily relate to the period on the basis of which climate regionalization was carried out). The criteria of the Koppen climate classification are presented, on the basis of which the climate regionalization of Serbia has been carried out. The methodology of making maps of air temperatures and precipitation amounts has been described, on the basis of which a map of the climate regions of Serbia has been created. Spatial distribution of the types and subtypes of the climates in Serbia has been briefly described. It has been pointed to the constraints of the climate regionalization that arise from the theoretical bases of the climate classifications, but also from nature of the collected data and the applied methodology.
PB  - Srpska akademija nauka i umetnosti SANU - Geografski institut 'Jovan Cvijić', Beograd
T2  - Zbornik radova Geografskog instituta "Jovan Cvijić", SANU
T1  - Climate regionalization of Serbia according to koppen climate classification
SP  - 103
EP  - 114
VL  - 67
IS  - 2
DO  - 10.2298/IJGI1702103M
UR  - https://hdl.handle.net/21.15107/rcub_dais_12570
ER  - 

@article{
author = "Milovanović, Boško and Ducić, Vladan and Radovanović, Milan and Milivojević, Milovan",
year = "2017",
abstract = "The paper presents a concise overview of the theoretical framework on which climate classifications are based. Beside short review of climate classifications, namely climatic regionalization for Serbia (or wider area including Serbia), main deficiency of these research was ascertained (which primarily relate to the period on the basis of which climate regionalization was carried out). The criteria of the Koppen climate classification are presented, on the basis of which the climate regionalization of Serbia has been carried out. The methodology of making maps of air temperatures and precipitation amounts has been described, on the basis of which a map of the climate regions of Serbia has been created. Spatial distribution of the types and subtypes of the climates in Serbia has been briefly described. It has been pointed to the constraints of the climate regionalization that arise from the theoretical bases of the climate classifications, but also from nature of the collected data and the applied methodology.",
publisher = "Srpska akademija nauka i umetnosti SANU - Geografski institut 'Jovan Cvijić', Beograd",
journal = "Zbornik radova Geografskog instituta "Jovan Cvijić", SANU",
title = "Climate regionalization of Serbia according to koppen climate classification",
pages = "103-114",
volume = "67",
number = "2",
doi = "10.2298/IJGI1702103M",
url = "https://hdl.handle.net/21.15107/rcub_dais_12570"
}

Milovanović, B., Ducić, V., Radovanović, M.,& Milivojević, M.. (2017). Climate regionalization of Serbia according to koppen climate classification. in Zbornik radova Geografskog instituta "Jovan Cvijić", SANU
Srpska akademija nauka i umetnosti SANU - Geografski institut 'Jovan Cvijić', Beograd., 67(2), 103-114.
https://doi.org/10.2298/IJGI1702103M
https://hdl.handle.net/21.15107/rcub_dais_12570

Milovanović B, Ducić V, Radovanović M, Milivojević M. Climate regionalization of Serbia according to koppen climate classification. in Zbornik radova Geografskog instituta "Jovan Cvijić", SANU. 2017;67(2):103-114.
doi:10.2298/IJGI1702103M
https://hdl.handle.net/21.15107/rcub_dais_12570 .

Milovanović, Boško, Ducić, Vladan, Radovanović, Milan, Milivojević, Milovan, "Climate regionalization of Serbia according to koppen climate classification" in Zbornik radova Geografskog instituta "Jovan Cvijić", SANU, 67, no. 2 (2017):103-114,
https://doi.org/10.2298/IJGI1702103M .,
https://hdl.handle.net/21.15107/rcub_dais_12570 .

TY  - 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 .

TY  - BOOK
AU  - Миловановић, Бошко
PY  - 2017
UR  - https://dais.sanu.ac.rs/123456789/13093
AB  - Тема климатских промена последњих година заокупља пажњу научне заједнице широм света. Чини се да је у научним публикацијама много више пажње посвећено антропогеном утицају него природним факторима формирања климе. Међутим, адекватна процена антропогеног ефекта на колебање климе, захтева претходну оцену и других климатских фактора као што су Сунчева и вулканска активност и оцену Ел Нињо/Ла Ниња догађаји. С обзиром на то да Сунце представља главни спољашњи извор енергије за Земљу, као и да утицај снажних вулканских ерупција кроз избацивање огромних количина аеросола у атмосферу „представља аналог последица удара метеорита или нуклеарне зиме“, у овој књизи је посебна пажња посвећена овим климатским факторима.
PB  - Београд : Географски институт "Јован Цвијић" САНУ
T1  - Природни фактори колебања климе у Србији
T1  - Natural causes of climate variability in Serbia
UR  - https://hdl.handle.net/21.15107/rcub_dais_13093
ER  - 

@book{
author = "Миловановић, Бошко",
year = "2017",
abstract = "Тема климатских промена последњих година заокупља пажњу научне заједнице широм света. Чини се да је у научним публикацијама много више пажње посвећено антропогеном утицају него природним факторима формирања климе. Међутим, адекватна процена антропогеног ефекта на колебање климе, захтева претходну оцену и других климатских фактора као што су Сунчева и вулканска активност и оцену Ел Нињо/Ла Ниња догађаји. С обзиром на то да Сунце представља главни спољашњи извор енергије за Земљу, као и да утицај снажних вулканских ерупција кроз избацивање огромних количина аеросола у атмосферу „представља аналог последица удара метеорита или нуклеарне зиме“, у овој књизи је посебна пажња посвећена овим климатским факторима.",
publisher = "Београд : Географски институт "Јован Цвијић" САНУ",
title = "Природни фактори колебања климе у Србији, Natural causes of climate variability in Serbia",
url = "https://hdl.handle.net/21.15107/rcub_dais_13093"
}

Миловановић, Б.. (2017). Природни фактори колебања климе у Србији. 
Београд : Географски институт "Јован Цвијић" САНУ..
https://hdl.handle.net/21.15107/rcub_dais_13093

Миловановић Б. Природни фактори колебања климе у Србији. 2017;.
https://hdl.handle.net/21.15107/rcub_dais_13093 .

Миловановић, Бошко, "Природни фактори колебања климе у Србији" (2017),
https://hdl.handle.net/21.15107/rcub_dais_13093 .

TY  - JOUR
AU  - Ducić, Vladan
AU  - Milovanović, Boško
AU  - Đurđić, Snežana
PY  - 2011
UR  - https://dais.sanu.ac.rs/123456789/12545
AB  - The recent climate changes, among others, have contributed to the change in elevation of the upper tree line in high mountainous areas. At the same time, direct anthropogenic impact on the fragile ecosystems of high mountains has also been significant. The aim of this paper is to determine the actual dynamics of the formation of upper tree line in eastern Serbia and to identify the recent factors which condition it. The results obtained show that preconditions have been accomplished for the upper tree line increase, but this has not completely been confirmed by previous field researches.
PB  - Srpsko biološko društvo, Beograd, i dr.
T2  - Archives of Biological Sciences
T1  - Identification of recent factors that affect the formation of the upper tree line in eastern Serbia
SP  - 825
EP  - 830
VL  - 63
IS  - 3
DO  - 10.2298/ABS1103825D
UR  - https://hdl.handle.net/21.15107/rcub_dais_12545
ER  - 

@article{
author = "Ducić, Vladan and Milovanović, Boško and Đurđić, Snežana",
year = "2011",
abstract = "The recent climate changes, among others, have contributed to the change in elevation of the upper tree line in high mountainous areas. At the same time, direct anthropogenic impact on the fragile ecosystems of high mountains has also been significant. The aim of this paper is to determine the actual dynamics of the formation of upper tree line in eastern Serbia and to identify the recent factors which condition it. The results obtained show that preconditions have been accomplished for the upper tree line increase, but this has not completely been confirmed by previous field researches.",
publisher = "Srpsko biološko društvo, Beograd, i dr.",
journal = "Archives of Biological Sciences",
title = "Identification of recent factors that affect the formation of the upper tree line in eastern Serbia",
pages = "825-830",
volume = "63",
number = "3",
doi = "10.2298/ABS1103825D",
url = "https://hdl.handle.net/21.15107/rcub_dais_12545"
}

Ducić, V., Milovanović, B.,& Đurđić, S.. (2011). Identification of recent factors that affect the formation of the upper tree line in eastern Serbia. in Archives of Biological Sciences
Srpsko biološko društvo, Beograd, i dr.., 63(3), 825-830.
https://doi.org/10.2298/ABS1103825D
https://hdl.handle.net/21.15107/rcub_dais_12545

Ducić V, Milovanović B, Đurđić S. Identification of recent factors that affect the formation of the upper tree line in eastern Serbia. in Archives of Biological Sciences. 2011;63(3):825-830.
doi:10.2298/ABS1103825D
https://hdl.handle.net/21.15107/rcub_dais_12545 .

Ducić, Vladan, Milovanović, Boško, Đurđić, Snežana, "Identification of recent factors that affect the formation of the upper tree line in eastern Serbia" in Archives of Biological Sciences, 63, no. 3 (2011):825-830,
https://doi.org/10.2298/ABS1103825D .,
https://hdl.handle.net/21.15107/rcub_dais_12545 .

TY  - BOOK
AU  - Миловановић, Бошко
PY  - 2010
UR  - https://dais.sanu.ac.rs/123456789/13080
AB  - Основни предмет истраживања je особеност климе Старе планине. Примарни задатак је временска и просторна анализа климатских елемената, тј. одређивање климатских региона на посматраном простору. Захваљујући великој вертикалној рашчлањености рељефа и другим модификаторима, на Старој планини заступљен је прави мозаик климата. Oва регионално климатолошка студија би временом могла послужити као „подлога“ за одређена апликативна истраживања.
PB  - Београд : Географски институт "Јован Цвијић" САНУ
T1  - Клима Старе планине
T1  - Climate of the Mountain Stara planina
UR  - https://hdl.handle.net/21.15107/rcub_dais_13080
ER  - 

@book{
author = "Миловановић, Бошко",
year = "2010",
abstract = "Основни предмет истраживања je особеност климе Старе планине. Примарни задатак је временска и просторна анализа климатских елемената, тј. одређивање климатских региона на посматраном простору. Захваљујући великој вертикалној рашчлањености рељефа и другим модификаторима, на Старој планини заступљен је прави мозаик климата. Oва регионално климатолошка студија би временом могла послужити као „подлога“ за одређена апликативна истраживања.",
publisher = "Београд : Географски институт "Јован Цвијић" САНУ",
title = "Клима Старе планине, Climate of the Mountain Stara planina",
url = "https://hdl.handle.net/21.15107/rcub_dais_13080"
}

Миловановић, Б.. (2010). Клима Старе планине. 
Београд : Географски институт "Јован Цвијић" САНУ..
https://hdl.handle.net/21.15107/rcub_dais_13080

Миловановић Б. Клима Старе планине. 2010;.
https://hdl.handle.net/21.15107/rcub_dais_13080 .

Миловановић, Бошко, "Клима Старе планине" (2010),
https://hdl.handle.net/21.15107/rcub_dais_13080 .

TY  - JOUR
AU  - Milenković, Milan
AU  - Ducić, Vladan
AU  - Milovanović, Boško
PY  - 2010
UR  - https://dais.sanu.ac.rs/123456789/11886
AB  - The connection between the solar flux at 2.8 GHz (based on mean monthly values) and the outbreaks of gypsy moths (Lymantria dispar L.) in Serbia was investigated. The researches included six outbreaks from 1952 to 2007. The average values of the solar flux ranged between 83.8 and 101.8 sfu during the outbreaks, whereas they were between 147.9 and 188.3 sfu for the periods without outbreaks. The results of the research showed that the increase in the number of gypsy moths appears when the values of the solar flux at 2.8 GHz range from 70 to 120 sfu.
PB  - Beograd : Srpsko biološko društvo i dr.
T2  - Archives of Biological Sciences
T1  - The influence of the solar flux at 2.8 GHz on outbreaks of gypsy moth (Lymantria dispar L.) (Lepidoptera: Lymantriidae) in Serbia
SP  - 1021
EP  - 1025
VL  - 62
IS  - 4
DO  - 10.2298/ABS1004021M
UR  - https://hdl.handle.net/21.15107/rcub_dais_11886
ER  - 

@article{
author = "Milenković, Milan and Ducić, Vladan and Milovanović, Boško",
year = "2010",
abstract = "The connection between the solar flux at 2.8 GHz (based on mean monthly values) and the outbreaks of gypsy moths (Lymantria dispar L.) in Serbia was investigated. The researches included six outbreaks from 1952 to 2007. The average values of the solar flux ranged between 83.8 and 101.8 sfu during the outbreaks, whereas they were between 147.9 and 188.3 sfu for the periods without outbreaks. The results of the research showed that the increase in the number of gypsy moths appears when the values of the solar flux at 2.8 GHz range from 70 to 120 sfu.",
publisher = "Beograd : Srpsko biološko društvo i dr.",
journal = "Archives of Biological Sciences",
title = "The influence of the solar flux at 2.8 GHz on outbreaks of gypsy moth (Lymantria dispar L.) (Lepidoptera: Lymantriidae) in Serbia",
pages = "1021-1025",
volume = "62",
number = "4",
doi = "10.2298/ABS1004021M",
url = "https://hdl.handle.net/21.15107/rcub_dais_11886"
}

Milenković, M., Ducić, V.,& Milovanović, B.. (2010). The influence of the solar flux at 2.8 GHz on outbreaks of gypsy moth (Lymantria dispar L.) (Lepidoptera: Lymantriidae) in Serbia. in Archives of Biological Sciences
Beograd : Srpsko biološko društvo i dr.., 62(4), 1021-1025.
https://doi.org/10.2298/ABS1004021M
https://hdl.handle.net/21.15107/rcub_dais_11886

Milenković M, Ducić V, Milovanović B. The influence of the solar flux at 2.8 GHz on outbreaks of gypsy moth (Lymantria dispar L.) (Lepidoptera: Lymantriidae) in Serbia. in Archives of Biological Sciences. 2010;62(4):1021-1025.
doi:10.2298/ABS1004021M
https://hdl.handle.net/21.15107/rcub_dais_11886 .

Milenković, Milan, Ducić, Vladan, Milovanović, Boško, "The influence of the solar flux at 2.8 GHz on outbreaks of gypsy moth (Lymantria dispar L.) (Lepidoptera: Lymantriidae) in Serbia" in Archives of Biological Sciences, 62, no. 4 (2010):1021-1025,
https://doi.org/10.2298/ABS1004021M .,
https://hdl.handle.net/21.15107/rcub_dais_11886 .