Article
Computer Science, Information Systems
Yangxue Li, Danilo Pelusi, Yong Deng, Kang Hao Cheong
Summary: Real-world information is uncertain and partially reliable, leading to the introduction of Z-numbers by Zadeh for modeling such information. Handling Z-number-based information has been challenging, similar to probability theory. In this work, a method for developing the concept of relative entropy of Z-numbers is proposed, leading to the construction of a novel Technique for Order of Preference by Similarity to Ideal Solution based on Z-numbers (ZTOPSIS) which directly calculates Z-numbers. A case study on supplier selection demonstrates the effectiveness of the proposed Z-TOPSIS method.
INFORMATION SCIENCES
(2021)
Article
Engineering, Multidisciplinary
Shuang He, Jun Xu, Yu Zhang
Summary: A new method based on the maximum entropy method is proposed for deriving the probability density function of the limit state function in reliability calculation. The method utilizes a transformed mixed-degree cubature rule to enhance numerical evaluation. The approach is verified through numerical examples, demonstrating its effectiveness.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Management
Nathan Lassance, Frederic Vrins
Summary: We present a new framework for portfolio selection that allows investors to target a specific return distribution, with the objective of designing an optimal portfolio that closely matches the target distribution. This framework is applicable to various investment objectives. Here, we focus on improving the higher moments of mean-variance-efficient portfolios by designing the target distribution to have desirable higher moments while matching the first two moments of the efficient portfolio. Theoretical analysis shows that the optimal portfolio, in general, differs from the mean-variance portfolio, but remains mean-variance efficient when asset returns follow a Gaussian distribution. Otherwise, it may deviate from the efficient frontier to better match the higher moments of the target distribution. Extensive empirical analysis using different datasets demonstrates that the proposed framework achieves a satisfactory compromise between mean-variance efficiency and improved higher moments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Mathematics, Applied
Gabriel Rioux, Rustum Choksi, Tim Hoheisel, Pierre Marechal, Christopher Scarvelis
Summary: This article introduces the application of maximum entropy on the mean (MEM) to image deblurring and point spread function estimation, shifting the paradigm towards regularization at the level of the probability distribution on the space of images. The method is simple, capable of handling large blurs, and has potential for generalization and modifications.
Article
Physics, Multidisciplinary
A. Alexopoulos
Summary: The Kullback-Leibler divergence is generalized into its fractional form in this study, showing that the fractional divergence can capture different relative entropy states through manipulation of the fractional order. It serves as the evolution equation for relative entropy and establishes mathematical dualities with other divergences or distance metrics. The fractional order can be characterized as a distance metric between divergences or relative entropy states, leading to the derivation of generalized asymptotic divergences and densities that are mixtures of known approaches.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2021)
Article
Agriculture, Multidisciplinary
Jing Zhang, Shuqin Yang, Shenrong Hu, Jifeng Ning, Xianyong Lan, Yongsheng Wang
Summary: Accurately tracking dairy goats is crucial for disease prediction and abnormal behavior recognition. We developed an innovative tracking algorithm that utilizes an asymmetric fusion architecture and Kullback Leibler loss to improve accuracy and reduce noise. By incorporating high-dimensional timing information and an asymmetric attention mechanism, our model achieved significant performance improvement.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Chemistry, Physical
Yu Yamamori, Kentaro Tomii
Summary: In this study, a new post-processing method was proposed to optimize the weighting factors of MD simulation snapshots for better agreement with experimental data without altering the distribution generated by the simulation. The method focuses on minimizing Kullback-Leibler divergence between optimized and original probability distribution, as long as the error between experimental and calculated values is within a certain threshold. This reweighting method was applied to ethane in a vacuum and lysozyme in a solvent as examples.
CHEMICAL PHYSICS LETTERS
(2021)
Article
Physics, Multidisciplinary
Mauricio A. Valle, Jaime F. Lavin, Nicolas S. Magner
Summary: Using the Maximum Entropy Principle approach, interactions between a selected set of stock assets and equity indices under different high and low return volatility episodes were analyzed. Second-order interactions were found to play a significant role in explaining the system entropy during the Subprime Crisis and the COVID-19 outbreak, with slight changes in these interactions leading to large changes in assets correlations. Despite some changes in interactions, the proportion of positive and negative interactions remained largely unchanged, maintaining the system in a ferromagnetic state.
Article
Physics, Multidisciplinary
Iddo Eliazar, Shlomi Reuveni
Summary: This paper is the first study to address the impact of restart on the Shannon entropy of completion time. It analyzes the effects of sharp restart on completion time with different timers and establishes closed-form results. The study also uses an information-geometric approach to determine the existence of timers that decrease or increase completion time entropy.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2023)
Article
Engineering, Chemical
M. Arjun, Nabil Magbool Jan
Summary: Accurate and precise estimation of process variables is crucial for effective process monitoring. This article proposes a method based on information-theoretic measures and convex optimization for designing optimal sensor networks, and demonstrates its efficacy through case studies.
Article
Automation & Control Systems
Chi Wei, Shaobin Huang, Rongsheng Li, Ye Liu, Naiyu Yan
Summary: This paper proposes a fusion scheme to correct spelling errors in sentences, which utilizes a detection module, original input, and masked input to acquire comprehensive sentence semantic information, achieving superior performance on two benchmarks.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Chemistry, Analytical
Tulay Ercan, Costas Papadimitriou
Summary: A framework for optimal sensor placement for virtual sensing is proposed based on modal expansion technique and information theory. The framework maximizes a utility function to reduce uncertainty in predicted quantities of interest at virtual sensing locations, considering uncertainties in structural model and modeling error parameters. The Gaussian nature of the response is utilized to derive analytical expressions for the utility function, highlighting the importance of robustness to errors and uncertainties.
Article
Mathematics, Applied
Przemyslaw Zielinski, Hannes Vandecasteele, Giovanni Samaey
Summary: The study examines the convergence and stability of a micro-macro acceleration algorithm for Monte Carlo simulations of linear stiff stochastic differential equations with time scale separation. The method involves short simulations of individual fast paths, extrapolation of macroscopic state variables, and constructing a new probability distribution to minimize Kullback-Leibler divergence. The convergence to microscopic dynamics and stability results for Gaussian and non-Gaussian initial laws are discussed in the context of linear stochastic differential equations with additive noise.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2021)
Article
Physics, Multidisciplinary
M. Ashok Kumar, Albert Sunny, Ashish Thakre, Ashisha Kumar, G. Dinesh Manohar
Summary: This paper establishes a close relationship among four information theoretic problems and proposes a unified framework to solve these problems. The framework not only finds asymptotically optimal solutions, but also enables the study of more appealing problem variations.
Article
Engineering, Mechanical
Binbin Shang, Pengjian Shang
Summary: The paper introduces a new visibility algorithm for time series, which combines with Kullback-Leibler divergence to measure the irreversibility of multivariable time series. This method is simple and effective, accurately distinguishing reversible and irreversible time series, with successful application in analyzing financial time series irreversibility.
NONLINEAR DYNAMICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Tian Liang, Lin Fu
Summary: In this work, a new shock-capturing framework is proposed based on a new candidate stencil arrangement and the combination of infinitely differentiable non-polynomial RBF-based reconstruction in smooth regions with jump-like non-polynomial interpolation for genuine discontinuities. The resulting scheme achieves high order accuracy and resolves genuine discontinuities with sub-cell resolution.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Lukas Lundgren, Murtazo Nazarov
Summary: In this paper, a high-order accurate finite element method for incompressible variable density flow is introduced. The method addresses the issues of saddle point system and stability problem through Schur complement preconditioning and artificial compressibility approaches, and it is validated to have high-order accuracy for smooth problems and accurately resolve discontinuities.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Gabriele Ciaramella, Laurence Halpern, Luca Mechelli
Summary: This paper presents a novel convergence analysis of the optimized Schwarz waveform relaxation method for solving optimal control problems governed by periodic parabolic PDEs. The analysis is based on a Fourier-type technique applied to a semidiscrete-in-time form of the optimality condition, which enables a precise characterization of the convergence factor at the semidiscrete level. The behavior of the optimal transmission condition parameter is also analyzed in detail as the time discretization approaches zero.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jonas A. Actor, Xiaozhe Hu, Andy Huang, Scott A. Roberts, Nathaniel Trask
Summary: This article introduces a scientific machine learning framework that uses a partition of unity architecture to model physics through control volume analysis. The framework can extract reduced models from full field data while preserving the physics. It is applicable to manifolds in arbitrary dimension and has been demonstrated effective in specific problems.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Nozomi Magome, Naoki Morita, Shigeki Kaneko, Naoto Mitsume
Summary: This paper proposes a novel strategy called B-spline based SFEM to fundamentally solve the problems of the conventional SFEM. It uses different basis functions and cubic B-spline basis functions with C-2-continuity to improve the accuracy of numerical integration and avoid matrix singularity. Numerical results show that the proposed method is superior to conventional methods in terms of accuracy and convergence.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Timothy R. Law, Philip T. Barton
Summary: This paper presents a practical cell-centred volume-of-fluid method for simulating compressible solid-fluid problems within a pure Eulerian setting. The method incorporates a mixed-cell update to maintain sharp interfaces, and can be easily extended to include other coupled physics. Various challenging test problems are used to validate the method, and its robustness and application in a multi-physics context are demonstrated.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Xing Ji, Fengxiang Zhao, Wei Shyy, Kun Xu
Summary: This paper presents the development of a third-order compact gas-kinetic scheme for compressible Euler and Navier-Stokes solutions, constructed particularly for an unstructured tetrahedral mesh. The scheme demonstrates robustness in high-speed flow computation and exhibits excellent adaptability to meshes with complex geometrical configurations.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Alsadig Ali, Abdullah Al-Mamun, Felipe Pereira, Arunasalam Rahunanthan
Summary: This paper presents a novel Bayesian statistical framework for the characterization of natural subsurface formations, and introduces the concept of multiscale sampling to localize the search in the stochastic space. The results show that the proposed framework performs well in solving inverse problems related to porous media flows.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jacob Rains, Yi Wang, Alec House, Andrew L. Kaminsky, Nathan A. Tison, Vamshi M. Korivi
Summary: This paper presents a novel method called constrained optimized DMD with Control (cOptDMDc), which extends the optimized DMD method to systems with exogenous inputs and can enforce the stability of the resulting reduced order model (ROM). The proposed method optimally places eigenvalues within the stable region, thus mitigating spurious eigenvalue issues. Comparative studies show that cOptDMDc achieves high accuracy and robustness.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Andrea La Spina, Jacob Fish
Summary: This work introduces a hybridizable discontinuous Galerkin formulation for simulating ideal plasmas. The proposed method couples the fluid and electromagnetic subproblems monolithically based on source and employs a fully implicit time integration scheme. The approach also utilizes a projection-based divergence correction method to enforce the Gauss laws in challenging scenarios. Numerical examples demonstrate the high-order accuracy, efficiency, and robustness of the proposed formulation.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Junhong Yue, Peijun Li
Summary: This paper proposes two numerical methods (IP-FEM and BP-FEM) to study the flexural wave scattering problem of an arbitrary-shaped cavity on an infinite thin plate. These methods successfully decompose the fourth-order plate wave equation into the Helmholtz and modified Helmholtz equations with coupled conditions on the cavity boundary, providing an effective solution to this challenging problem.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
William Anderson, Mohammad Farazmand
Summary: We develop fast and scalable methods, called RONS, for computing reduced-order nonlinear solutions. These methods have been proven to be highly effective in tackling challenging problems, but become computationally prohibitive as the number of parameters grows. To address this issue, three separate methods are proposed and their efficacy is demonstrated through examples. The application of RONS to neural networks is also discussed.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Marco Caliari, Fabio Cassini
Summary: In this paper, a second order exponential scheme for stiff evolutionary advection-diffusion-reaction equations is proposed. The scheme is based on a directional splitting approach and uses computation of small sized exponential-like functions and tensor-matrix products for efficient implementation. Numerical examples demonstrate the advantage of the proposed approach over state-of-the-art techniques.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Sebastiano Boscarino, Seung Yeon Cho, Giovanni Russo
Summary: This work proposes a high order conservative semi-Lagrangian method for the inhomogeneous Boltzmann equation of rarefied gas dynamics. The method combines a semi-Lagrangian scheme for the convection term, a fast spectral method for computation of the collision operator, and a high order conservative reconstruction and a weighted optimization technique to preserve conservative quantities. Numerical tests demonstrate the accuracy and efficiency of the proposed method.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jialei Li, Xiaodong Liu, Qingxiang Shi
Summary: This study shows that the number, centers, scattering strengths, inner and outer diameters of spherical shell-structured sources can be uniquely determined from the far field patterns. A numerical scheme is proposed for reconstructing the spherical shell-structured sources, which includes a migration series method for locating the centers and an iterative method for computing the inner and outer diameters without computing derivatives.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)