Complexity analysis of the air temperature and the precipitation time series in Serbia

Mimić, Gordan; Mihailoviĉ, Dragutin T.; Kapor, D.

doi:10.1007/s00704-015-1677-6

Cited by 8 publications

(4 citation statements)

References 32 publications

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“…The annual quantity of rainfall is often insufficient, and droughts are evident in eastern and south-eastern parts of Serbia [28]. Scenarios where the monthly quantity of precipitation falls in only a few days of the month are expected to become more frequent, which will lead to more extreme weather events such as floods and droughts [29]. Serbia has two peaks in its fire season [30].…”

Section: Study Areamentioning

confidence: 99%

Forest Fire Probability Mapping in Eastern Serbia: Logistic Regression versus Random Forest Method

Milanović

Marković

Pamučar

et al. 2020

Forests

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Forest fire risk has increased globally during the previous decades. The Mediterranean region is traditionally the most at risk in Europe, but continental countries like Serbia have experienced significant economic and ecological losses due to forest fires. To prevent damage to forests and infrastructure, alongside other societal losses, it is necessary to create an effective protection system against fire, which minimizes the harmful effects. Forest fire probability mapping, as one of the basic tools in risk management, allows the allocation of resources for fire suppression, within a fire season, from zones with a lower risk to those under higher threat. Logistic regression (LR) has been used as a standard procedure in forest fire probability mapping, but in the last decade, machine learning methods such as fandom forest (RF) have become more frequent. The main goals in this study were to (i) determine the main explanatory variables for forest fire occurrence for both models, LR and RF, and (ii) map the probability of forest fire occurrence in Eastern Serbia based on LR and RF. The most important variable was drought code, followed by different anthropogenic features depending on the type of the model. The RF models demonstrated better overall predictive ability than LR models. The map produced may increase firefighting efficiency due to the early detection of forest fire and enable resources to be allocated in the eastern part of Serbia, which covers more than one-third of the country’s area.

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Section: Study Areamentioning

confidence: 99%

Forest Fire Probability Mapping in Eastern Serbia: Logistic Regression versus Random Forest Method

Milanović

Marković

Pamučar

et al. 2020

Forests

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“…In the meanwhile, in the theory of nonlinear dynamical systems an interesting and easily applicable tool known as complexity measure or Kolmogorov complexity (KC) [19,20] has been proposed. Today it is closely related to the information theory [19][20][21][22], and applied in many other fields such as hydrology [23], climatology [24,25], etc. The complexity measure represents a useful quantity, which characterizes spatiotemporal patterns and provides fine measure of order, i.e., periodic motion and chaotic behavior.…”

mentioning

confidence: 99%

Complexity of Shapiro steps

et al. 2020

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We demonstrate on the example of the dc+ac driven overdamped Frenkel-Kontorova model that an easily calculable measure of complexity can be used for the examination of Shapiro steps in presence of thermal noise. In real systems, thermal noise causes melting or even disappearance of Shapiro steps, which makes their analysis in the standard way from the response function difficult. Unlike in the conventional approach, here, by calculating the Kolmogorov complexity of certain areas in the response function we were able to detect Shapiro steps, measure their size with desired precision and examine their temperature dependence. The aim of this work is to provide scientists, particularly experimentalists, an unconventional but a practical and easy tool for examination of Shapiro steps in real systems.

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“…Considering that a signal with a high value of α 0 , a wide range W of fractal exponents (higher degree of multifractality), and a right-skewed shape (r > 0) may be considered more complex than those with opposite characteristics [52], the observed changes of multifractal parameters (Figure 4) indicated that in the second period overall complexity of temperature series increased in northern part of country, and decreased in southern part. Mimić et al [57] analyzed the complexity of daily maximum and minimum temperature and daily precipitation from seven station on Serbia (recorded during the period 1951-2010) using information theory measures Kolmogorov complexity and Sample entropy. They found that for all stations both measures (calculated for 1year periods) exhibit positive trend for maximum temperature indicating the increase in complexity.…”

Section: Multifractal Analysismentioning

confidence: 99%

Climate Change Effects through MFDFA Study of Temperature in Serbia

Stosic,

Tošić

et al. 2023

Atmosphere

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We investigate multifractal properties of daily means of air temperature over the territory of Serbia, by using Multifractal detrended fluctuation analysis. Temperature anomalies in two periods 1961–1990 and 1991–2020 are calculated from the E-OBSv26.0e gridded dataset with 0.10° (~12 km) resolution, totaling 1278 daily temperature series for each period. The MFDFA parameters: position of the maximum of the spectrum α0, width of the spectrum W and asymmetry r, obtained from the total of 2556 MFDFA runs are interpolated to yield their spatial distribution across Serbia in the two periods. We found several patterns in both the spatial distribution, and changes from first to second period. All series showed multifractal properties with overall persistent long-term correlations (α0 > 0.5) and the dominance of small fluctuations (r > 0). The persistence is weaker (smaller α0 values) and multifractality is stronger (larger width W) in southern mountainous regions. In the second period the values of α0 increased indicating stronger persistence of temperature dynamics, while multifractality became stronger (larger W) in northern region and weaker (smaller W) in southern region. In both periods the contribution to multifractality was dominated by small fluctuations (r > 0) that become stronger in the second period, indicated by the increase of the values of r over most of the country’s area. These changes in the values of multifractal parameters indicate the increase of complexity of temperature dynamics in the second 30 years period which could be related to climate change.

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Complexity analysis of the air temperature and the precipitation time series in Serbia

Cited by 8 publications

References 32 publications

Forest Fire Probability Mapping in Eastern Serbia: Logistic Regression versus Random Forest Method

Forest Fire Probability Mapping in Eastern Serbia: Logistic Regression versus Random Forest Method

Complexity of Shapiro steps

Climate Change Effects through MFDFA Study of Temperature in Serbia

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