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作者： Zhou, Zheng Tan, Bing Li, Songxiao College of Mathematics and Statistics Sichuan University of Science and Engineering Zigong China School of Sciences Southwest Petroleum University Chengdu China Department of Mathematics University of British Columbia Kelowna Canada Department of Mathematics Shantou University Shantou China

With the help of the Meir–Keeler contraction method and the Mann-type method, two adaptive inertial iterative schemes are introduced for finding solutions of the split variational inclusion problem in Hilbert spaces. The strong convergence of the suggested algorithms is guaranteed by a new stepsize criterion that does not require calculation of the bounded linear operator norm. Some numerical experiments and applications in signal recovery problems are given to demonstrate the efficiency of the proposed algorithms. © 2023 John Wiley & Sons, Ltd.

关键词： Variational techniques

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Stability of pairwise social dilemma games: Destructive agents, constructive agents, and their joint effects

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Physical Review E 2024年第3期110卷 034307页

作者： Khadija Khatun Chen Shen Lei Shi Jun Tanimoto Interdisciplinary Graduate School of Engineering Sciences Department of Applied Mathematics Faculty of Engineering Sciences School of Statistics and Mathematics

Destructive agents, who opt out of the game and indiscriminately harm others, paradoxically foster cooperation, representing an intriguing variant of the voluntary participation strategy. Yet, their impact on cooperation remains inadequately understood, particularly in the context of pairwise social dilemma games and in comparison to their counterparts, constructive agents, who opt out of the game but indiscriminately benefit others. Furthermore, little is known about the combined effects of both agent types on cooperation dynamics. Using replicator dynamics in infinite and well-mixed populations, we find that contrary to their role in facilitating cooperation in multiplayer games, destructive agents fail to encourage cooperation in pairwise social dilemmas. Instead, they replace defection in the prisoners' dilemma and stag-hunt games. Similarly, in the chicken game, they can destabilize or replace the mixed equilibrium of cooperation and defection, undermining cooperation in the harmony (trivial) game. Conversely, constructive agents, when their payoffs exceed their contributions to opponents, can exhibit effects similar to destructive agents. However, if their payoffs are lower, while they destabilize defection in prisoners' dilemma and stag-hunt games, they do not disrupt the cooperation equilibrium in harmony games and have a negligible impact on the coexistence of cooperation in chicken games. The combination of destructive and constructive agents does not facilitate cooperation, but instead generates complex evolutionary dynamics, including bistable, tristable, and quadstable states, with outcomes contingent on their relative payoffs and game types. These results, taken together, enhance our understanding of the impact of the voluntary participation mechanism on cooperation, contributing to a more comprehensive understanding of its influence.

关键词： Game theory models

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Enhancing drought monitoring with a multivariate hydrometeorological index and machine learning-based prediction in the south of Iran

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Environmental Science and Pollution Research 2025年第9期32卷 5605-5627页

作者： Zamani, Hossein Pakdaman, Zohreh Shakari, Marzieh Bazrafshan, Ommolbanin Jamshidi, Sajad Department of Statistics and Mathematics Faculty of Science University of Hormozgan Bandar Abbas Iran Department of Natural Resources Engineering Faculty of Agricultural and Natural Resources Engineering University of Hormozgan Bandar Abbas Iran Department of Agronomy Purdue University LafayetteIN47901 United States

Traditional drought indices, such as the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), often fail to capture the complexity of drought events, which involve multiple interacting variables. To address this gap, this study applies the Principle of Maximum Entropy (POME) copula to combine SPI and SRI into a Joint Deficit Index (JDI), offering a more complete assessment of hydrometeorological drought. We used machine learning models, including Random Forest (RF), Quantile Random Forest (QRF), Extreme Gradient Boosting (XGB), and Quantile Regression XGBoost (QXGB), to predict JDI, while also incorporating uncertainty analysis using the Uncertainty Estimation based on Local Errors and Clustering (UNEEC) method. This approach not only improves the accuracy of drought predictions but also quantifies the uncertainty of the models, enhancing reliability. Model performance, evaluated with R2, RMSE, and MAE, showed XGB as the best performer, achieving R2 = 0.93 and RMSE = 0.16. This integration of multivariate drought indices, machine learning, and uncertainty analysis provides a more robust tool for drought monitoring and water resource management in arid regions. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Adversarial machine learning

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Multi-attribute group decision-making with T-spherical fuzzy Dombi power Heronian mean-based aggregation operators

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Granular Computing 2024年第4期9卷 1-29页

作者： Javed, Mubashar Javeed, Shumaila Senapati, Tapan Department of Mathematics COMSATS University Islamabad Islamabad Campus Park Road Chak Shahzad Islamabad45550 Pakistan Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon School of Mathematics and Statistics Southwest University Beibei Chongqing400715 China Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Thandalam Tamil Nadu Chennai602105 India

In the realm of expressing fuzzy and vague information, T-spherical fuzzy sets (TSPFSs) emerge as a powerful extension of both picture fuzzy sets (PFSs) and spherical fuzzy sets (SFSs), offering decision-makers a broader spectrum of descriptive capabilities. Within the domain of multi-attribute group decision-making (MAGDM), the significance of T-spherical fuzzy aggregation operators (AOs) under T-spherical fuzzy conditions cannot be overstated. Hence, our manuscript contributes by introducing a collection of ground-breaking T-spherical fuzzy AOs. This paper establishes a set of innovative T-spherical fuzzy operational laws grounded in Dombi t-norm and Dombi t-conorm (DTNCN) principles. Utilizing the strengths of power aggregation operators, which effectively capture the implications of unfavorable information, and Heronian mean (HM) operators, which adeptly assess the collective association among the evaluated arguments. Some aggregation operators are examined, namely T-spherical fuzzy Dombi power Heronian mean (TSPFDPHM) operator, T-spherical fuzzy Dombi weighted power Heronian mean (TSPFDWPHM) operator, T-spherical fuzzy Dombi geometric power Heronian mean (TSPFDGPHM) operator, and T-spherical fuzzy Dombi weighted geometric power Heronian mean (TSPFDWGPHM) operator. Additionally, we present a host of properties exhibited by these proposed AOs, along with specific cases that allow for adjustable parameters. Subsequently, we develop a comprehensive algorithm for MAGDM based on the proposed AOs within the T-spherical fuzzy environment. In conclusion, we apply the devised algorithm to a real-world scenario involving selecting the best road construction company for a post-flood road rehabilitation project in Pakistan. Through comparative analysis with existing methodologies, we demonstrate the validity and superiority of our developed scheme, thereby reinforcing its practical applicability and effectiveness. © The Author(s), under exclusive licence to Springer Nature

关键词： Spheres

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THE OPTIMAL REINSURANCE-INVESTMENT PROBLEM CONSIDERING THE JOINT INTERESTS OF AN INSURER AND A REINSURER UNDER HARA UTILITY

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Acta Mathematica Scientia 2023年第1期43卷 97-124页

作者：张燕赵培标周华任 Department of General Education Army Engineering University of PLANanjing211101China School of Mathematics&Statistics Nanjing University of Science and TechnologyNanjing210094China

This paper focuses on an optimal reinsurance and investment problem for an insurance corporation which holds the shares of an insurer and a *** that the insurer can purchase reinsurance from the reinsurer,and that both the insurer and the reinsurer are allowed to invest in a risk-free asset and a risky asset which are governed by the Heston model and are distinct from one *** aim to find the optimal reinsuranceinvestment strategy by maximizing the expected Hyperbolic Absolute Risk Aversion(HARA)utility of the insurance corporation’s terminal wealth,which is the weighted sum of the insurer’s and the reinsurer’s terminal *** Hamilton-Jacobi-Bellman(HJB)equation is first ***,this equation is non-linear and is difficult to solve directly by any ordinary method found in the existing literature,because the structure of this HJB equation is more complex under HARA *** the present paper,the Legendre transform is applied to change this HJB equation into a linear dual one such that the explicit expressions of optimal investment-reinsurance strategies for-1≤ρi≤1 are *** also discuss some special cases in a little bit more ***,numerical analyses are provided.

关键词： reinsurance investment HARA utility Heston model Legendre transform

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Sparse identification-assisted exploration of the atomic-scale deformation mechanism in multiphase CoCrFeNi high-entropy alloys

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Science China(Technological Sciences) 2024年第4期67卷 1124-1132页

作者： XIAO Lu GUO XiaoXiang SUN YuTong WANG Gang LONG WeiMin LIAW Peter K. REN JingLi School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Institute of Materials Shanghai UniversityShanghai 200444China SKL of Advanced Brazing Metals&Technology Zhengzhou Research Institute of Mechanical EngineeringZhengzhou 450001China Department of Materials Science and Engineering The University of TennesseeKnoxvilleTN 37996USA

This study investigated the atomic-scale deformation mechanism of multiphase CoCrFeNi high-entropy alloys(HEAs)at liquid helium,liquid nitrogen,and room temperatures.A million-atom multiphase HEA was prepared using molecular dynamics simulation involving melt and quench *** HEA exhibited high-density dislocations and some twins,consistent with experimental *** analysis revealed an inconsistent evolution of the microstructure under tensile *** particular,the elastic and initial plastic stages exhibited an increase in the disordered structure at the expense of the face-centered cubic and hexagonal close-packed structures,followed by a subsequent transformation involving multiple structural ***,through sparse identification,a model depicting microstructural evolution during tension was extracted for the CoCrFeNi HEA at three typical temperatures and three tensile *** model highlighted the importance of the body-centered cubic structure in the evolutionary process.

关键词： high-entropy alloy data-driven method microstructure evolution multiphase structure molecular dynamics simulation

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An efficient computational procedure to solve the biological nonlinear Leptospirosis model using the genetic algorithms

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Soft Computing 2024年第1期28卷 607-625页

作者： Sabir, Zulqurnain Ali, Mohamed R. Raja, Muhammad Asif Zahoor Sadat, R. Department of Mathematics and Statistics Hazara University Mansehra Pakistan Faculty of Engineering and Technology Future University in Egypt New Cairo11835 Egypt Basic Engineering Science Department Benha Faculty of Engineering Benha University Banha Egypt Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Department of Mathematics Zagazig Faculty of Engineering Zagazig University Zagazig Egypt Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon

The purpose of this work is to present the numerical solutions of the nonlinear mathematical Leptospirosis disease (LD) model using the computational performances of the artificial neural networks (ANNs) along with the optimization procedures based on the global search genetic algorithm (GA) and local search active-set algorithm (ASA) scheme, i.e., ANNs-GA-ASA. LD is a zoonotic disease that is occurring in the whole world, obtained by rodents that become the reason of death in the people. The LD model based on the susceptible-infected-recovered, i.e., SIR, is used to solve the mechanisms of disease spread. The optimization of an error-based fitness function, which is constructed through the differential mathematical system using the hybrid computing proficiencies of the ANNs-GA-ASA for solving the LD model. The stochastic ANNs-GA-ASA procedures are applied to the LD model to authenticate the precision, exactness, reliability and competence of the ANNs-GA-ASA. The obtained results using the ANNs-GA-ASA of the LD model will be compared using the Runge–Kutta scheme, which authenticate the importance of the ANNs-GA-ASA. Furthermore, statistical analysis through different actions for the LD model approve the convergence and precision of the ANNs-GA-ASA. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Neural networks

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An Adaptive Multiresolution Ultra-weak Discontinuous Galerkin Method for Nonlinear Schrödinger Equations

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Communications on Applied mathematics and Computation 2022年第1期4卷 60-83页

作者： Zhanjing Tao Juntao Huang Yuan Liu Wei Guo Yingda Cheng School of Mathematics Jilin UniversityJilin 130012China Department of Mathematics Michigan State UniversityEast LansingMI 48824USA Department of Mathematics Statistics and PhysicsWichita State UniversityWichitaKS 67260USA Department of Mathematics and Statistics Texas Tech UniversityLubbockTX 70409USA Department of Mathematics Department of Computational MathematicsScience and EngineeringMichigan State UniversityEast LansingMI 48824USA

This paper develops a high-order adaptive scheme for solving nonlinear Schrödinger *** solutions to such equations often exhibit solitary wave and local structures,which make adaptivity essential in improving the simulation *** scheme uses the ultra-weak discontinuous Galerkin(DG)formulation and belongs to the framework of adaptive multiresolution *** numerical experiments are presented to demon-strate the excellent capability of capturing the soliton waves and the blow-up phenomenon.

关键词： Multiresolution Sparse grid Ultra-weak discontinuous Galerkin method Schrödinger equation Adaptivity

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Elastic wave insulation and propagation control based on the programmable curved-beam periodic structure

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Applied mathematics and Mechanics(English Edition) 2024年第10期45卷 1791-1806页

作者： Jiajia MAO Hong CHENG Tianxue MA Beijing Key Laboratory of Nonlinear Vibrations and Strength of Mechanical Structures Department of MechanicsSchool of MathematicsStatistics and MechanicsBeijing University of TechnologyBeijing 100124China Department of Mechanics School of Physical Science and EngineeringBeijing Jiaotong UniversityBeijing 100044China

Curved-beams can be used to design modular multistable metamaterials(MMMs)with reprogrammable material properties,i.e.,programmable curved-beam periodic structure(PCBPS),which is promising for controlling the elastic wave *** PCBPS is theoretically equivalent to a spring-oscillator system to investigate the mechanism of bandgap,analyze the wave propagation mechanisms,and further form its geometrical and physical criteria for tuning the elastic wave *** the equivalent model,we calculate the analytical solutions of the dispersion relations to demonstrate its adjustability,and investigate the wave propagation characteristics through the *** validate the equivalent system,the finite element method(FEM)is *** is revealed that the bandgaps of the PCBPS can be turned on-and-off and shifted by varying its physical and geometrical *** findings are highly promising for advancing the practical application of periodic structures in wave insulation and propagation control.

关键词： curved-beam based periodic structure equivalent stiffness spring-oscillator system dispersion relation wave propagation

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Modelling COVID-19 cases and deaths with climate variables using statistical and data science methods

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Soft Computing 2024年第21期28卷 12561-12574页

作者： Karimuzzaman, Md. Afroz, Sabrina Hossain, Md. Moyazzem Rahman, Azizur DREXEL Dornsife School of Public Health DREXEL University PhiladelphiaPA United States Department of Statistics Jahangirnagar University Savar Dhaka1342 Bangladesh School of Mathematics Statistics and Physics Newcastle University Newcastle Upon Tyne United Kingdom School of Computing Mathematics and Engineering Charles Sturt University Wagga WaggaNSW2678 Australia

The authors aimed to forecast the cumulative COVID-19 confirmed cases and deaths by the most appropriate model of the top five impacted countries and three South Asian countries incorporating the climate factors as covariates. Different statistical and data science methods are used in this study. The results of the model selection criteria depict that the ELM algorithm is adequate for France, Germany, and Spain, while the MLP algorithm tends to have a better forecast for India and Pakistan. In Sri Lanka, Italy, and the United States, the well-known ARIMAX model tends to be a good match for death predictions. The findings showed that the inclusion of the meteorological variables improves the accuracy of modeling both COVID-19 cases and deaths, for all the chosen countries’ cumulative confirmed cases except Italy and Sri Lanka. However, in the case of modeling deaths, it is observed that the inclusion of meteorological variables was not able to enhance the forecasting accuracy of the model in each of the selected countries. Though no single model was found to be suitable for all countries, the authors identify the most appropriate models for each country for forecasting and make the sixty-day-ahead forecast for each country. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： COVID-19

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