TY  - JOUR
AU  - Malinović-Milićević, Slavica
AU  - Mihailović, Anja
AU  - Mihailović, Dragutin T.
PY  - 2022
UR  - https://dais.sanu.ac.rs/123456789/13300
AB  - Influenced by stratospheric total ozone column (TOC), cloud cover, aerosols, albedo, and other factors, levels of daily erythemal dose (H_er) in a specific geographic region show significant variability in time and space. To investigate the degree of randomness and predictability of H_er time series from ground-based observations in Novi Sad, Serbia, during the 2003–2012 time period, we used a set of information measures: Kolmogorov complexity, Kolmogorov complexity spectrum, running Kolmogorov complexity, the largest Lyapunov exponent, Lyapunov time, and Kolmogorov time. The result reveals that fluctuations in daily H_er are moderately random and exhibit low levels of chaotic behavior. We found a larger number of occurrences of deviation from the mean in the time series during the years with lower values of H_er (2007–2009, 2011–2012), which explains the higher complexity. Our analysis indicated that the time series of daily values of H_er show a tendency to increase the randomness when the randomness of cloud cover and TOC increases, which affects the short-term predictability. The prediction horizon of daily H_er values in Novi Sad given by the Lyapunov time corrected for randomness by Kolmogorov is between 1.5 and 3.5 days.
PB  - Switzerland, Basel : MDPI
T2  - Atmosphere
T1  - Kolmogorov Complexity Analysis and Prediction Horizon of the Daily Erythemal Dose Time Series
VL  - 13
IS  - 746
DO  - 10.3390/atmos13050746
UR  - https://hdl.handle.net/21.15107/rcub_dais_13300
ER  - 

@article{
author = "Malinović-Milićević, Slavica and Mihailović, Anja and Mihailović, Dragutin T.",
year = "2022",
abstract = "Influenced by stratospheric total ozone column (TOC), cloud cover, aerosols, albedo, and other factors, levels of daily erythemal dose (H_er) in a specific geographic region show significant variability in time and space. To investigate the degree of randomness and predictability of H_er time series from ground-based observations in Novi Sad, Serbia, during the 2003–2012 time period, we used a set of information measures: Kolmogorov complexity, Kolmogorov complexity spectrum, running Kolmogorov complexity, the largest Lyapunov exponent, Lyapunov time, and Kolmogorov time. The result reveals that fluctuations in daily H_er are moderately random and exhibit low levels of chaotic behavior. We found a larger number of occurrences of deviation from the mean in the time series during the years with lower values of H_er (2007–2009, 2011–2012), which explains the higher complexity. Our analysis indicated that the time series of daily values of H_er show a tendency to increase the randomness when the randomness of cloud cover and TOC increases, which affects the short-term predictability. The prediction horizon of daily H_er values in Novi Sad given by the Lyapunov time corrected for randomness by Kolmogorov is between 1.5 and 3.5 days.",
publisher = "Switzerland, Basel : MDPI",
journal = "Atmosphere",
title = "Kolmogorov Complexity Analysis and Prediction Horizon of the Daily Erythemal Dose Time Series",
volume = "13",
number = "746",
doi = "10.3390/atmos13050746",
url = "https://hdl.handle.net/21.15107/rcub_dais_13300"
}

Malinović-Milićević, S., Mihailović, A.,& Mihailović, D. T.. (2022). Kolmogorov Complexity Analysis and Prediction Horizon of the Daily Erythemal Dose Time Series. in Atmosphere
Switzerland, Basel : MDPI., 13(746).
https://doi.org/10.3390/atmos13050746
https://hdl.handle.net/21.15107/rcub_dais_13300

Malinović-Milićević S, Mihailović A, Mihailović DT. Kolmogorov Complexity Analysis and Prediction Horizon of the Daily Erythemal Dose Time Series. in Atmosphere. 2022;13(746).
doi:10.3390/atmos13050746
https://hdl.handle.net/21.15107/rcub_dais_13300 .

Malinović-Milićević, Slavica, Mihailović, Anja, Mihailović, Dragutin T., "Kolmogorov Complexity Analysis and Prediction Horizon of the Daily Erythemal Dose Time Series" in Atmosphere, 13, no. 746 (2022),
https://doi.org/10.3390/atmos13050746 .,
https://hdl.handle.net/21.15107/rcub_dais_13300 .

TY  - JOUR
AU  - Mihailović, Dragutin T.
AU  - Nikolić-Đorić, Emilija
AU  - Malinović-Milićević, Slavica
AU  - Singh, Vijay P.
AU  - Mihailović, Anja
AU  - Stošić, Tatjana
AU  - Stošić, Borko
AU  - Drešković, Nusret
PY  - 2019
UR  - https://dais.sanu.ac.rs/123456789/12914
AB  - The purpose of this paper was to choose an appropriate information dissimilarity measure for hierarchical clustering of daily streamflow discharge data, from twelve gauging stations on the Brazos River in Texas (USA), for the period 1989–2016. For that purpose, we selected and compared the average-linkage clustering hierarchical algorithm based on the compression-based dissimilarity
measure (NCD), permutation distribution dissimilarity measure (PDDM), and Kolmogorov distance (KD). The algorithm was also compared with K-means clustering based on Kolmogorov complexity (KC), the highest value of Kolmogorov complexity spectrum (KCM), and the largest Lyapunov exponent (LLE). Using a dissimilarity matrix based on NCD, PDDM, and KD for daily streamflow,
the agglomerative average-linkage hierarchical algorithm was applied. The key findings of this study are that: (i) The KD clustering algorithm is the most suitable among others; (ii) ANOVA analysis shows that there exist highly significant differences between mean values of four clusters, confirming that the choice of the number of clusters was suitably done; and (iii) from the clustering we found that the predictability of streamflow data of the Brazos River given by the Lyapunov time (LT), corrected for randomness by Kolmogorov time (KT) in days, lies in the interval from two to five days.
PB  - Switzerland, Basel : MDPI
T2  - Entropy
T1  - The Choice of an Appropriate Information Dissimilarity Measure for Hierarchical Clustering of River Streamflow Time Series, Based on Calculated Lyapunov Exponent and Kolmogorov Measures
SP  - 215
VL  - 21
IS  - 2
DO  - 10.3390/e21020215
UR  - https://hdl.handle.net/21.15107/rcub_dais_12914
ER  - 

@article{
author = "Mihailović, Dragutin T. and Nikolić-Đorić, Emilija and Malinović-Milićević, Slavica and Singh, Vijay P. and Mihailović, Anja and Stošić, Tatjana and Stošić, Borko and Drešković, Nusret",
year = "2019",
abstract = "The purpose of this paper was to choose an appropriate information dissimilarity measure for hierarchical clustering of daily streamflow discharge data, from twelve gauging stations on the Brazos River in Texas (USA), for the period 1989–2016. For that purpose, we selected and compared the average-linkage clustering hierarchical algorithm based on the compression-based dissimilarity
measure (NCD), permutation distribution dissimilarity measure (PDDM), and Kolmogorov distance (KD). The algorithm was also compared with K-means clustering based on Kolmogorov complexity (KC), the highest value of Kolmogorov complexity spectrum (KCM), and the largest Lyapunov exponent (LLE). Using a dissimilarity matrix based on NCD, PDDM, and KD for daily streamflow,
the agglomerative average-linkage hierarchical algorithm was applied. The key findings of this study are that: (i) The KD clustering algorithm is the most suitable among others; (ii) ANOVA analysis shows that there exist highly significant differences between mean values of four clusters, confirming that the choice of the number of clusters was suitably done; and (iii) from the clustering we found that the predictability of streamflow data of the Brazos River given by the Lyapunov time (LT), corrected for randomness by Kolmogorov time (KT) in days, lies in the interval from two to five days.",
publisher = "Switzerland, Basel : MDPI",
journal = "Entropy",
title = "The Choice of an Appropriate Information Dissimilarity Measure for Hierarchical Clustering of River Streamflow Time Series, Based on Calculated Lyapunov Exponent and Kolmogorov Measures",
pages = "215",
volume = "21",
number = "2",
doi = "10.3390/e21020215",
url = "https://hdl.handle.net/21.15107/rcub_dais_12914"
}

Mihailović, D. T., Nikolić-Đorić, E., Malinović-Milićević, S., Singh, V. P., Mihailović, A., Stošić, T., Stošić, B.,& Drešković, N.. (2019). The Choice of an Appropriate Information Dissimilarity Measure for Hierarchical Clustering of River Streamflow Time Series, Based on Calculated Lyapunov Exponent and Kolmogorov Measures. in Entropy
Switzerland, Basel : MDPI., 21(2), 215.
https://doi.org/10.3390/e21020215
https://hdl.handle.net/21.15107/rcub_dais_12914

Mihailović DT, Nikolić-Đorić E, Malinović-Milićević S, Singh VP, Mihailović A, Stošić T, Stošić B, Drešković N. The Choice of an Appropriate Information Dissimilarity Measure for Hierarchical Clustering of River Streamflow Time Series, Based on Calculated Lyapunov Exponent and Kolmogorov Measures. in Entropy. 2019;21(2):215.
doi:10.3390/e21020215
https://hdl.handle.net/21.15107/rcub_dais_12914 .

Mihailović, Dragutin T., Nikolić-Đorić, Emilija, Malinović-Milićević, Slavica, Singh, Vijay P., Mihailović, Anja, Stošić, Tatjana, Stošić, Borko, Drešković, Nusret, "The Choice of an Appropriate Information Dissimilarity Measure for Hierarchical Clustering of River Streamflow Time Series, Based on Calculated Lyapunov Exponent and Kolmogorov Measures" in Entropy, 21, no. 2 (2019):215,
https://doi.org/10.3390/e21020215 .,
https://hdl.handle.net/21.15107/rcub_dais_12914 .

TY  - JOUR
AU  - Bessafi, Miloud
AU  - Mihailović, Dragutin T.
AU  - Malinović-Milićević, Slavica
AU  - Mihailović, Anja
AU  - Jumaux, Guillaume
AU  - Bonnardot, François
AU  - Fanchette, Yannick
AU  - Chabriat, Jean-Pierre
PY  - 2018
UR  - https://dais.sanu.ac.rs/123456789/13302
AB  - Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural intermittency of solar irradiation is mainly triggered by atmospheric turbulent conditions, radiative transfer, optical properties of cloud and aerosol, moisture and atmospheric stability, orographic and thermal forcing, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the period 2011–2015, at 32 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use the tools of non-linear dynamics: the intermittency and chaos analysis, the largest Lyapunov exponent, Sample entropy, the Kolmogorov complexity and its derivatives (Kolmogorov complexity spectrum and its highest value), and spatial weighted Kolmogorov complexity combined with Hamming distance to assess complexity and corresponding predictability. Finally, we have clustered the Kolmogorov time (that
quantifies the time span beyond which randomness significantly influences predictability) for daily cumulative solar irradiation for all stations. We show that under the record-breaking 2011–2012 La Nina event and preceding a very strong El-Nino 2015–2016 event, the predictability of daily incident solar energy over La Réunion is affected.
PB  - Switzerland, Basel : MDPI
T2  - Entropy
T1  - Spatial and Temporal Non-Linear Dynamics Analysis and Predictability of Solar Radiation Time Series for La Reunion Island (France)
VL  - 20
IS  - 946
DO  - 10.3390/e20120946
UR  - https://hdl.handle.net/21.15107/rcub_dais_13302
ER  - 

@article{
author = "Bessafi, Miloud and Mihailović, Dragutin T. and Malinović-Milićević, Slavica and Mihailović, Anja and Jumaux, Guillaume and Bonnardot, François and Fanchette, Yannick and Chabriat, Jean-Pierre",
year = "2018",
abstract = "Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural intermittency of solar irradiation is mainly triggered by atmospheric turbulent conditions, radiative transfer, optical properties of cloud and aerosol, moisture and atmospheric stability, orographic and thermal forcing, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the period 2011–2015, at 32 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use the tools of non-linear dynamics: the intermittency and chaos analysis, the largest Lyapunov exponent, Sample entropy, the Kolmogorov complexity and its derivatives (Kolmogorov complexity spectrum and its highest value), and spatial weighted Kolmogorov complexity combined with Hamming distance to assess complexity and corresponding predictability. Finally, we have clustered the Kolmogorov time (that
quantifies the time span beyond which randomness significantly influences predictability) for daily cumulative solar irradiation for all stations. We show that under the record-breaking 2011–2012 La Nina event and preceding a very strong El-Nino 2015–2016 event, the predictability of daily incident solar energy over La Réunion is affected.",
publisher = "Switzerland, Basel : MDPI",
journal = "Entropy",
title = "Spatial and Temporal Non-Linear Dynamics Analysis and Predictability of Solar Radiation Time Series for La Reunion Island (France)",
volume = "20",
number = "946",
doi = "10.3390/e20120946",
url = "https://hdl.handle.net/21.15107/rcub_dais_13302"
}

Bessafi, M., Mihailović, D. T., Malinović-Milićević, S., Mihailović, A., Jumaux, G., Bonnardot, F., Fanchette, Y.,& Chabriat, J.. (2018). Spatial and Temporal Non-Linear Dynamics Analysis and Predictability of Solar Radiation Time Series for La Reunion Island (France). in Entropy
Switzerland, Basel : MDPI., 20(946).
https://doi.org/10.3390/e20120946
https://hdl.handle.net/21.15107/rcub_dais_13302

Bessafi M, Mihailović DT, Malinović-Milićević S, Mihailović A, Jumaux G, Bonnardot F, Fanchette Y, Chabriat J. Spatial and Temporal Non-Linear Dynamics Analysis and Predictability of Solar Radiation Time Series for La Reunion Island (France). in Entropy. 2018;20(946).
doi:10.3390/e20120946
https://hdl.handle.net/21.15107/rcub_dais_13302 .

Bessafi, Miloud, Mihailović, Dragutin T., Malinović-Milićević, Slavica, Mihailović, Anja, Jumaux, Guillaume, Bonnardot, François, Fanchette, Yannick, Chabriat, Jean-Pierre, "Spatial and Temporal Non-Linear Dynamics Analysis and Predictability of Solar Radiation Time Series for La Reunion Island (France)" in Entropy, 20, no. 946 (2018),
https://doi.org/10.3390/e20120946 .,
https://hdl.handle.net/21.15107/rcub_dais_13302 .

TY  - JOUR
AU  - Mihailović, Dragutin T.
AU  - Bessafi, Miloud
AU  - Marković, Sara
AU  - Arsenić, Ilija
AU  - Malinović-Milićević, Slavica
AU  - Jeanty, Patrick
AU  - Delsaut, Mathieu
AU  - Chabriat, Jean-Pierre
AU  - Drešković, Nusret
AU  - Mihailović, Anja
PY  - 2018
UR  - https://dais.sanu.ac.rs/123456789/13301
AB  - Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural variability of solar irradiation is being complicated by atmospheric conditions (in particular cloudiness) and orography, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the years 2013, 2014 and 2015 at
11 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use a set of novel quantitative tools: Kolmogorov complexity (KC) with its derivative associated measures and Hamming distance (HAM) and their combination to assess complexity and corresponding predictability. We find that all half-day (from sunrise to sunset) solar irradiation series exhibit high complexity. However, all of them can be classified into three groups strongly influenced by trade winds that circulate in a “flow around” regime: the windward side (trade winds slow down), the leeward side (diurnal thermally-induced circulations dominate) and the coast parallel to trade winds (winds are accelerated due to Venturi effect). We introduce Kolmogorov time (KT) that quantifies the time span beyond which randomness significantly influences predictability.
PB  - Switzerland, Basel : MDPI
T2  - Entropy
T1  - Analysis of Solar Irradiation Time Series Complexity and Predictability by Combining Kolmogorov Measures and Hamming Distance for La Reunion (France)
VL  - 20
IS  - 570
DO  - 10.3390/e20080570
UR  - https://hdl.handle.net/21.15107/rcub_dais_13301
ER  - 

@article{
author = "Mihailović, Dragutin T. and Bessafi, Miloud and Marković, Sara and Arsenić, Ilija and Malinović-Milićević, Slavica and Jeanty, Patrick and Delsaut, Mathieu and Chabriat, Jean-Pierre and Drešković, Nusret and Mihailović, Anja",
year = "2018",
abstract = "Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural variability of solar irradiation is being complicated by atmospheric conditions (in particular cloudiness) and orography, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the years 2013, 2014 and 2015 at
11 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use a set of novel quantitative tools: Kolmogorov complexity (KC) with its derivative associated measures and Hamming distance (HAM) and their combination to assess complexity and corresponding predictability. We find that all half-day (from sunrise to sunset) solar irradiation series exhibit high complexity. However, all of them can be classified into three groups strongly influenced by trade winds that circulate in a “flow around” regime: the windward side (trade winds slow down), the leeward side (diurnal thermally-induced circulations dominate) and the coast parallel to trade winds (winds are accelerated due to Venturi effect). We introduce Kolmogorov time (KT) that quantifies the time span beyond which randomness significantly influences predictability.",
publisher = "Switzerland, Basel : MDPI",
journal = "Entropy",
title = "Analysis of Solar Irradiation Time Series Complexity and Predictability by Combining Kolmogorov Measures and Hamming Distance for La Reunion (France)",
volume = "20",
number = "570",
doi = "10.3390/e20080570",
url = "https://hdl.handle.net/21.15107/rcub_dais_13301"
}

Mihailović, D. T., Bessafi, M., Marković, S., Arsenić, I., Malinović-Milićević, S., Jeanty, P., Delsaut, M., Chabriat, J., Drešković, N.,& Mihailović, A.. (2018). Analysis of Solar Irradiation Time Series Complexity and Predictability by Combining Kolmogorov Measures and Hamming Distance for La Reunion (France). in Entropy
Switzerland, Basel : MDPI., 20(570).
https://doi.org/10.3390/e20080570
https://hdl.handle.net/21.15107/rcub_dais_13301

Mihailović DT, Bessafi M, Marković S, Arsenić I, Malinović-Milićević S, Jeanty P, Delsaut M, Chabriat J, Drešković N, Mihailović A. Analysis of Solar Irradiation Time Series Complexity and Predictability by Combining Kolmogorov Measures and Hamming Distance for La Reunion (France). in Entropy. 2018;20(570).
doi:10.3390/e20080570
https://hdl.handle.net/21.15107/rcub_dais_13301 .

Mihailović, Dragutin T., Bessafi, Miloud, Marković, Sara, Arsenić, Ilija, Malinović-Milićević, Slavica, Jeanty, Patrick, Delsaut, Mathieu, Chabriat, Jean-Pierre, Drešković, Nusret, Mihailović, Anja, "Analysis of Solar Irradiation Time Series Complexity and Predictability by Combining Kolmogorov Measures and Hamming Distance for La Reunion (France)" in Entropy, 20, no. 570 (2018),
https://doi.org/10.3390/e20080570 .,
https://hdl.handle.net/21.15107/rcub_dais_13301 .