Article
Computer Science, Artificial Intelligence
Qian He, Fusheng Yu, Jiaqi Chang, Chenxi Ouyang
Summary: Recently, recurrence plot (RP) and its quantification techniques have become an important research tool in nonlinear analysis. However, the existing research directly establishes an RP on a time series, ignoring the influence of noise on data, which affects the judgement on the dynamic properties of a system. To address this issue, this paper proposes a novel recurrence plot called fuzzy granular recurrence plot (FGRP). FGRP is built on a corresponding granular time series composed of fuzzy information granules, acting as high-level, compact, and understandable signal models for noise reduction and improved classification performance.
PATTERN RECOGNITION
(2023)
Article
Engineering, Mechanical
Tobias Braun, Vishnu R. Unni, R. I. Sujith, Juergen Kurths, Norbert Marwan
Summary: Lacunarity is proposed as a novel recurrence quantification measure that can effectively detect various dynamical transitions, including those exhibited by complex real-world systems. It is capable of distinguishing different states of dynamical complexity in the presence of noise and non-stationarity without the need for specifying minimal line lengths, making it more broadly applicable. The method demonstrates potential when applied to empirical data, capturing rich variability in dynamical complexity and shifting time scales.
NONLINEAR DYNAMICS
(2021)
Article
Engineering, Biomedical
Jing Liu, Huibin Lu, Yuanyuan Guo, Guanghua Gu, Xiaoli Li, Dong Cui
Summary: This study proposed a novel method, multiscale dispersion recurrence plot (MDRP), for analyzing the nonlinear characteristics of EEG signals in mild cognitive impairment (MCI). The MDRP algorithm showed less sensitivity to data length, embedding dimension, and noise, and was able to accurately reflect the nonlinear characteristics of the chaotic model. The DET values based on MDRP were found to be significantly lower in MCI patients compared to the control group, indicating its potential as an EEG marker for cognitive impairment.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Engineering, Multidisciplinary
Krzysztof Kecik, Arkadiusz Smagala, Krzysztof Ciecielag
Summary: The objective of this study was to evaluate the effectiveness of the recurrence method for detecting defects in angular contact ball bearings. A defect-free bearing was tested to determine recurrence reference values, and defects of different sizes were introduced into each component of the bearing. The study found that the recurrence approach was extremely promising and could detect defects in a very short time series (0.04s), with determinism and laminarity being the most promising indicators for defect detection.
Article
Mathematics, Interdisciplinary Applications
Sanjay K. Palit, Sayan Mukherjee
Summary: In this study, we explore the chaotic dynamics and complexity of a neuro-system with variable synaptic weights in both noise free and noisy conditions. The chaotic dynamics are investigated using bifurcation analysis and 0-1 test, while a multiscale complexity measure based on recurrence plot density entropy is proposed. The inclusion of white noise is found to increase the complexity of neuro dynamics, while music signal has a minimal impact on the system.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Physics, Multidisciplinary
Yuan Chen, Aijing Lin
Summary: In this paper, the order pattern recurrence plot (OPRP) and order pattern recurrence quantification analysis (OPRQA) are proposed to quantify recurrence characteristics of complex systems. The method demonstrates robustness to non-stationary data and low requirements for time series length. It effectively distinguishes chaotic systems from random noise, quantifies bifurcation transition scenarios, and analyzes performance differences in time series before, during, and after financial crises. The approach also reflects and quantifies differences in stocks between developing and developed countries.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Mathematics, Applied
Yoshito Hirata
Summary: The study demonstrates that recurrence plots can be used to analyze time series generated from random dynamical systems and proposes three theorems to explain the correspondence between recurrence plots, initial conditions, and stochastic inputs. A stochasticity test based on recurrence plots is also introduced in the study.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Economics
Xiaotian Sun, Wei Fang, Xiangyun Gao, Sufang An, Tao Wu, Shuai Ren
Summary: This study explores the nonstationary and complex behaviors of metal futures markets by analyzing their price fluctuations. The research findings indicate that the complexity of these markets has increased after 2013, and significant price changes are likely to occur when the entropy indicator is high.
Article
Mathematics, Interdisciplinary Applications
A. Jingjing Huang, B. Danlei Gu, C. Qian He
Summary: In this paper, a multiscale cross-recurrence quantification analysis (MSCRQA) method was proposed to analyze the dynamic states of two time series at different time scales. The study showed that MSCRQA can provide richer and more recognizable information compared to single time scale analysis, offering a new perspective for exploring hidden internal dynamic information of time series.
FLUCTUATION AND NOISE LETTERS
(2021)
Article
Engineering, Chemical
Hooman Ziaei-Halimejani, Sanaa Kouzbour, Reza Zarghami, Rahmat Sotudeh-Gharebagh, Bouchaib Gourich, Navid Mostoufi, Youssef Stiriba
Summary: The hydrodynamics of bubble column in the presence of different collectors were investigated using recurrence quantification analysis (RQA), which revealed determinism and entropy as sensitive parameters for detecting flow regime changes. Entropy was found to be much more effective than determinism in detecting changes in the hydrodynamics of the bubble column, making it a suitable recurrence parameter for such investigations.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2021)
Article
Physics, Multidisciplinary
Hanhuai Zhu, Jingjing Huang
Summary: This letter introduces a new method based on Manhattan distance and recurrence quantification analysis for determining the embedding dimension of financial time series dynamics. The method has the advantages of stability, accuracy, and rigor, and performs well on high-dimensional chaotic time series.
Article
Energy & Fuels
Remi Delage, Toshihiko Nakata
Summary: In the new energy systems' modeling paradigm, the complexity of renewable resources and demand dynamics is a major obstacle for scenario analysis and sustainable solution design. This study introduces noise-assisted multivariate empirical mode decomposition and recurrence quantification analysis to study electricity demand data in Japan, identifying relations with temperature variations, demand sector shares, life style and local culture.
Article
Computer Science, Interdisciplinary Applications
Hooman Ziaei-Halimejani, Nima Nazemzadeh, Reza Zarghami, Krist V. Gernaey, Martin Peter Andersson, Seyed Soheil Mansouri, Navid Mostoufi
Summary: An unsupervised learning method was developed for fault detection and diagnosis in chemical processes, with JRQA method showing the best performance in fault diagnosis of the complete dataset. The sensitivity of the results in the case of missing data can be adjusted by changing the length of the sub-series.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Mathematics, Interdisciplinary Applications
Xiang Wu, Xujun Yang, Qiankun Song, Xiaofeng Chen
Summary: This paper addresses the stability problems of a nabla discrete distributed-order dynamical system (NDDS), proposing definitions and inequalities to establish conditions for the asymptotic stability of the system.
FRACTAL AND FRACTIONAL
(2022)
Article
Mathematics, Interdisciplinary Applications
Baki Unal, Guray Kucukkocaoglu, Eyup Kadioglu
Summary: The Recurrence Quantification Analysis (RQA) is a pattern recognition-based time series analysis method that is suitable for short, nonstationary, nonlinear, and chaotic time series. RQA measures quantify various properties of time series, including predictability, regularity, stability, randomness, and complexity. By analyzing the intraday seasonality and volatility using RQA measures on a dataset from Borsa Istanbul Equity Market, we found relationships between RQA measures and intraday patterns.
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
(2023)
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)