Article
Physics, Multidisciplinary
Jorge Luis Morales Martinez, Ignacio Segovia-Dominguez, Israel Quiros Rodriguez, Francisco Antonio Horta-Rangel, Guillermo Sosa-Gomez
Summary: A new method called Multifractal Detrended Fluctuation Analysis with Polynomial and Trigonometric functions (MFDFAPT) is proposed in this study to better detect and model hidden local trends in time series. Through extensive numerical experiments, MFDFAPT shows superior performance in estimating Hurst index compared to traditional methods, and accurately determines scalar behavior in both stationary and non-stationary series.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Physics, Fluids & Plasmas
Rabindev Bishal, Gabriel B. Mindlin, Neelima Gupte
Summary: The time series recordings of typical songs of songbirds exhibit highly complex and structured behavior, which can be uncovered by Hurst exponents and multifractal analysis and supported by time series networks. Temporal correlations are responsible for the multifractal behavior and two-point correlations are important in the high-fluctuation regime. Higher-order correlations and intersyllabic gaps dominate the behavior in the low-fluctuation regime. Additionally, intersyllabic gaps contribute significantly to the complexity of birdsong.
Article
Physics, Multidisciplinary
Tatijana Stosic, Luciano Telesca, Borko Stosic
Summary: High frequency data from the city of Petrolina in Northeast Brazil is used to analyze wind speed projection series at different angles using statistical tools such as DFA, MFDFA, and FSA. The study found that wind speed characteristics vary at different projection angles, with lower angles showing higher heterogeneity, lower disorder, higher organization, and dominance of small fluctuations. Analyzing wind speed with varying direction can contribute to enriching the knowledge of wind speed dynamics.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Mathematics, Interdisciplinary Applications
Luciano Telesca, Nicodemo Abate, Farid Faridani, Michele Lovallo, Rosa Lasaponara
Summary: Xylella fastidiosa is a phytobacterium that causes severe diseases in various species. Its infection on olive trees leads to the olive quick decline syndrome, resulting in rapid tree desiccation and death. This study analyzes MODIS satellite evapotranspiration data using the Fisher-Shannon method and the multifractal detrended fluctuation analysis to detect the presence of Xylella fastidiosa. The results indicate that these methods can effectively differentiate between infected and healthy sites, with the maximum of the multifractal spectrum performing the best. These findings suggest the potential use of these methods for early detection of plant diseases.
FRACTAL AND FRACTIONAL
(2023)
Article
Mathematics, Applied
Katarzyna Maraj, Dawid Szarek, Grzegorz Sikora, Agnieszka Wylomanska
Summary: This study discusses a new method based on the TAMSD ratio statistic for testing Gaussian anomalous diffusion models, which outperforms the traditional TAMSD approach, especially for small sample sizes.
Article
Physics, Multidisciplinary
Pedro Carpena, Manuel Gomez-Extremera, Pedro A. Bernaola-Galvan
Summary: Detrended Fluctuation Analysis (DFA) is a method for quantifying correlations and scaling properties in real-world time series. However, when the scaling behavior differs at short and long scales, using alpha1 to describe the short-scale properties is problematic.
Article
Mathematics, Applied
A. N. Pavlov, O. N. Pavlova, O. V. Semyachkina-Glushkovskaya, J. Kurths
Summary: Multiresolution wavelet analysis is a powerful tool for characterizing complex signals at different time scales, and when combined with detrended fluctuation analysis, it can reveal more information about the complex organization of datasets.
Article
Physics, Multidisciplinary
Marco Biroli, Hernan Larralde, Satya N. Majumdar, Gregory Schehr
Summary: In this study, we investigate a one-dimensional gas of N Brownian particles that are reset simultaneously. Despite the presence of strong correlations, we find that several observables, such as the global average density and the distributions of particle positions and spacings, can be computed exactly. Our findings are confirmed by numerical simulations and we also discuss the potential experimental realization of this resetting gas using optical traps.
PHYSICAL REVIEW LETTERS
(2023)
Article
Mathematics, Interdisciplinary Applications
Antonio Samuel Alves da Silva, Tatijana Stosic, Ilija Arsenic, Romulo Simoes Cezar Menezes, Borko Stosic
Summary: Northeast Brazil is a densely populated dryland region vulnerable to climate change, with an increasing risk of water-related natural disasters. The study shows that the Standardized Precipitation Index (SPI) exhibits multifractal dynamics at different time scales, with stronger multifractality and complexity in long-term precipitation anomalies in the semiarid inland region. The coastal area displays stronger persistence of dry/wet conditions compared to the inland region.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Engineering, Chemical
Tao Wei, Shuo Yang, Lianze Wang
Summary: The objective of this study was to analyze the influences of operational parameters on the spatial and temporal distribution and multifractal characteristics of indoor suspended PM concentration under the sink effect. The results showed that with the increase of the applied voltage of the purification device, the concentrations of PM1 and PM2.5 decreased, while PM10 and TSP concentrations decreased significantly. The dynamic evolution processes of the PM concentration series showed strong persistence and followed scale-invariant power-law statistical distributions. The positive correlation between PM concentration series at five distances increased with the increase of applied voltage.
CHEMICAL ENGINEERING SCIENCE
(2023)
Article
Engineering, Chemical
Armin Bunde
Summary: Random processes can be categorized based on the correlation of consecutive data, which can be uncorrelated (white noise), short-range correlated (red noise), or long-range correlated (pink noise). This article explores the properties and applications of these different types of noise and discusses how they impact diffusion processes, occurrence of rare extreme events, and detection of external trends amidst the noise – the latter two being particularly relevant in the context of analyzing data to identify anthropogenic global warming.
CHEMIE INGENIEUR TECHNIK
(2023)
Article
Mathematics, Interdisciplinary Applications
Carlos Alberto Valentim, Claudio Marcio Cassela Inacio Jr, Sergio Adriani David
Summary: This study investigates EEG signals to differentiate mental tasks, finding stronger gamma brain waves during activity and alpha waves at rest. Subjects performing better in tasks showed less power density in high-frequency ranges, possibly indicating decreased brain activity. Time-domain analysis using fractal measures suggests better differentiation of signals between rest and activity datasets. The study recommends the combined use of frequency- and time-based methods in EEG analysis.
FRACTAL AND FRACTIONAL
(2021)
Article
Environmental Sciences
Chunqiong Liu, Li Zhang, Ye Wen, Kai Shi
Summary: The study uses the properties of nonlinear coupling detrended fluctuation analysis (CDFA) to reveal coupling correlations between O-3 and its precursors at different time scales, helping to quantify the contribution degree of NOx and NMHC to O-3 formation.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Engineering, Marine
Jianjun Feng, Yi Men, Guojun Zhu, Yunzhe Li, Xingqi Luo
Summary: A comprehensive test system was constructed in this study to obtain the vibration signals and cavitation images of a Kaplan turbine under different cavitation states. The multifractal detrended fluctuation analysis method was used to analyze the vibration signals and investigate the influence of runner blade cavitation on turbine vibration. The results showed that the multifractal characteristics of the vibration signals could effectively identify the cavitation states of the turbine.
Article
Physics, Multidisciplinary
O. N. Pavlova, G. A. Guyo, A. N. Pavlov
Summary: This study examines the possibility of distinguishing different types of complex oscillations in datasets contaminated with measurement noise using multiresolution wavelet analysis (MWA). By applying different measures to the decomposition coefficients, the study shows that MWA's ability in diagnosing dynamics can be enhanced, for example, by using detrended fluctuation analysis (DFA) or computing the excess of the probability density function of detail wavelet coefficients.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Neurosciences
Didier Delignieres, Zainy M. H. Almurad, Clement Roume, Vivien Marmelat
EXPERIMENTAL BRAIN RESEARCH
(2016)
Article
Neurosciences
Zainy M. H. Almurad, Clement Roume, Didier Delignieres
HUMAN MOVEMENT SCIENCE
(2017)
Article
Physics, Multidisciplinary
C. Roume, Z. M. H. Almurad, M. Scotti, S. Ezzina, H. Blain, D. Delignieres
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2018)
Article
Mathematical & Computational Biology
Clement Roume, Samar Ezzina, Hubert Blain, Didier Delignieres
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
(2019)
Article
Neurosciences
Samar Ezzina, Maxime Scotti, Clement Roume, Simon Pla, Hubert Blain, Didier Delignieres
Summary: Three frameworks have been proposed to explain interpersonal synchronization, but regardless of the task and nature of information, synchronization is primarily driven by discrete mutual adaptation. These results question the relevance of the coordination dynamics perspective in interpersonal coordination.
JOURNAL OF MOTOR BEHAVIOR
(2021)
Article
Physiology
Zainy M. H. Almurad, Clement Roume, Hubert Blain, Didier Delignieres
FRONTIERS IN PHYSIOLOGY
(2018)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)