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S. Porshnev,E. Solomaha,O. Ponomareva
Pág. 45 - 50
The features of Hurst exponent H of the classical Brownian motion trajectory calculated by the R/S-analysis has been studied, where R is a range of a cumulative deviations of the chosen fragment of the trajectory within the time interval (from the ...
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Dzhema Melkonyan and Sherin Sugathan
Increasing groundwater levels (GWLs) may become one of the most serious issues for the city of Odessa, Ukraine. This study investigated the spatial distribution characteristics and multifractal scaling behaviour of the groundwater-level/-depth fluctuatio...
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Monica Alexiadou, Emmanouil Sofianos, Periklis Gogas and Theophilos Papadimitriou
In this study we investigate possible long-range trends in the cryptocurrency market. We employed the Hurst exponent in a sample covering the period from 1 January 2016 to 26 March 2021. We calculated the Hurst exponent in three non-overlapping consecuti...
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João Sequeira, Jorge Louçã, António M. Mendes and Pedro G. Lind
We analyze the empirical series of malaria incidence, using the concepts of autocorrelation, Hurst exponent and Shannon entropy with the aim of uncovering hidden variables in those series. From the simulations of an agent model for malaria spreading, we ...
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Fan Liu, Fang Wang, Guiping Liao, Xin Lu and Jiayi Yang
In order to detect the oleic acid content of rapeseed quickly and accurately, we propose, in this paper, an artificial BP neural networks based model for predicting oleic acid content by using rapeseed?s hyperspectral information. Four types of spectral ...
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Tomasz Blachowicz, Krzysztof Domino, Michal Koruszowic, Jacek Grzybowski, Tobias Böhm and Andrea Ehrmann
Two-dimensional structures, either periodic or random, can be classified by diverse mathematical methods. Quantitative descriptions of such surfaces, however, are scarce since bijective definitions must be found to measure unique dependency between descr...
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Stanislaw Drozdz, Ludovico Minati, Pawel Oswi?cimka, Marek Stanuszek and Marcin Wa¸torek
Based on the high-frequency recordings from Kraken, a cryptocurrency exchange and professional trading platform that aims to bring Bitcoin and other cryptocurrencies into the mainstream, the multiscale cross-correlations involving the Bitcoin (BTC), Ethe...
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Bo Liu, Liangwen Yao, Xiaofei Fu, Bo He and Longhui Bai
The first member of the Qingshankou Formation, in the Gulong Sag in the northern part of the Songliao Basin, has become an important target for unconventional hydrocarbon exploration. The organic-rich shale within this formation not only provides favorab...
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Li Na, Risu Na, Jiquan Zhang, Siqin Tong, Yin Shan, Hong Ying, Xiangqian Li and Yulong Bao
As the global climate has changed, studies on the relationship between vegetation and climate have become crucial. We analyzed the long-term vegetation dynamics and diverse responses to extreme climate changes in Inner Mongolia, based on long-term Global...
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Alvaro Alberto López-Lambraño,Carlos Fuentes,Alvaro Alberto López-Ramos,Jorge Mata Ramírez,Mariangela López-Lambraño
Pág. 199 - 219
A fractal analysis from rainfall events registered in a semiarid region was carried out. The analysis was executed for Baja California, Mexico, a region that presents a high climatological variability. Rainfall data from 92 climate stations distributed a...
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Liliya A. Demidova, Dmitry O. Zhukov, Elena G. Andrianova and Alexander S. Sigov
This paper explores the social dynamics of processes in complex systems involving humans by focusing on user activity in online media outlets. The R/S analysis showed that the time series of the processes under consideration are fractal and anti-persiste...
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Ioannis Tsantilis, Thomas K. Dasaklis, Christos Douligeris and Constantinos Patsakis
Cybersecurity is a never-ending battle against attackers, who try to identify and exploit misconfigurations and software vulnerabilities before being patched. In this ongoing conflict, it is important to analyse the properties of the vulnerability time s...
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Pawel Dymora and Miroslaw Mazurek
Fractal and multifractal analysis can help to discover the structure of the communication system, and in particular the pattern and characteristics of traffic, in order to understand the threats better and detect anomalies in network operation. The massi...
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Derick Quintino, Jessica Campoli, Heloisa Burnquist and Paulo Ferreira
Bitcoin?s evolution has attracted the attention of investors and researchers looking for a better understanding of the efficiency of cryptocurrency markets, considering their prices and volatility. The purpose of this paper is to contribute to this under...
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Zhenzhen Zhu, Zhidong Bai, João Paulo Vieito, Wing-Keung Wong
Pág. 5 - 30
We analyze the impact of the most recent global financial crisis (GFC) on the seven most important Latin American stock markets. Our mean-variance analysis shows that the markets are significantly less volatile and, in general, investors prefer to invest...
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Mishelle Doorasamy,Prince Kwasi Sarpong
Pág. 93 - 100
Peters (1994) proposed the fractal market hypothesis (FMH) as an alternative to the efficient market hypothesis, following his criticism of the EMH. In this study, we analyse whether the fractal nature of a financial market determines its riskiness and d...
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Erhui Li, Xingmin Mu, Guangju Zhao and Peng Gao
Multifractal detrended fluctuation analysis (MFDFA) can provide information about inner regularity, randomness and long-range correlation of time series, promoting the knowledge of their evolution regularity. The MFDFA are applied to detect long-range co...
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Dengpan Li, Lei Tian, Mingyang Li, Tao Li, Fang Ren, Chunhong Tian and Ce Yang
Exploring the temporal and spatial changes, as well as driving factors, of net primary productivity (NPP) of terrestrial ecosystems is essential for maintaining regional carbon balance. This work focuses on the spatiotemporal variation and future trends ...
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Anis Malekzadeh, Assef Zare, Mahdi Yaghoobi and Roohallah Alizadehsani
This paper proposes a new method for epileptic seizure detection in electroencephalography (EEG) signals using nonlinear features based on fractal dimension (FD) and a deep learning (DL) model. Firstly, Bonn and Freiburg datasets were used to perform exp...
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Miaomiao Yu, Hongyong Yuan, Kaiyuan Li and Lizheng Deng
To separate the noise and important signal features of the indoor carbon dioxide (CO2) concentration signal, we proposed a noise cancellation method, based on time-varying, filtering-based empirical mode decomposition (TVF-EMD) with Bayesian optimization...
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