检索结果-南通市图书馆

Optimal Model Average Prediction in Orthogonal Kriging Models

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2024年第3期37卷 1080-1099页

作者： WANG Jun HE Jiabei LIANG Hua LI Xinmin School of Mathematics and statistics Qingdao UniversityQingdao 266071China department of statistics George Washington UniversityWashington DC 20052USA

The main objective of this paper is to consider model averaging methods for kriging models.This paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optimality of the model averaging estimators in terms of mean square error.Simulation studies are conducted to evaluate the performance of the proposed method and compare it with the competitors to demonstrate its superiority.The authors also analyse a real dataset for an illustration.

关键词： Asymptotic optimality Mallows criterion optimal model averaging orthogonal kriging model

Double Moving Extremes Ranked Set Sampling Design

在线全文

学校读者我要写书评

暂无评论

Acta Mathematicae Applicatae Sinica 2024年第1期40卷 75-90页

作者： Meng Chen Wang-xue Chen Rui Yang department of Mathematics and statistics Jishou UniversityJishou416000China

The traditional simple random sampling(SRS)design method is inefficient in many cases.Statisticians proposed some new designs to increase efficiency.In this paper,as a variation of moving extremes ranked set sampling(MERSS),double MERSS(DMERSS)is proposed and its properties for estimating the population mean are considered.It turns out that,when the underlying distribution is symmetric,DMERSS gives unbiased estimators of the population mean.Also,it is found that DMERSS is more efficient than the SRS and MERSS methods for usual symmetric distributions(normal and uniform).For asymmetric distributions considered in this study,the DMERSS has a small bias and it is more efficient than SRS for usual asymmetric distribution(exponential)for small sample sizes.

关键词： double moving extremes ranked set sampling symmetric distribution efficiency

Sparse-Grid Implementation of Fixed-Point Fast Sweeping WENO Schemes for Eikonal Equations

在线全文

学校读者我要写书评

暂无评论

Communications on Applied Mathematics and Computation 2024年第1期6卷 3-29页

作者： Zachary M.Miksis Yong-Tao Zhang department of Applied and Computational Mathematics and statistics University of Notre DameNotre DameIN46556USA

Fixed-point fast sweeping methods are a class of explicit iterative methods developed in the literature to efficiently solve steady-state solutions of hyperbolic partial differential equations(PDEs).As other types of fast sweeping schemes,fixed-point fast sweeping methods use the Gauss-Seidel iterations and alternating sweeping strategy to cover characteristics of hyperbolic PDEs in a certain direction simultaneously in each sweeping order.The resulting iterative schemes have a fast convergence rate to steady-state solutions.Moreover,an advantage of fixed-point fast sweeping methods over other types of fast sweeping methods is that they are explicit and do not involve the inverse operation of any nonlinear local system.Hence,they are robust and flexible,and have been combined with high-order accurate weighted essentially non-oscillatory(WENO)schemes to solve various hyperbolic PDEs in the literature.For multidimensional nonlinear problems,high-order fixed-point fast sweeping WENO methods still require quite a large amount of computational costs.In this technical note,we apply sparse-grid techniques,an effective approximation tool for multidimensional problems,to fixed-point fast sweeping WENO methods for reducing their computational costs.Here,we focus on fixed-point fast sweeping WENO schemes with third-order accuracy(Zhang et al.2006[41]),for solving Eikonal equations,an important class of static Hamilton-Jacobi(H-J)equations.Numerical experiments on solving multidimensional Eikonal equations and a more general static H-J equation are performed to show that the sparse-grid computations of the fixed-point fast sweeping WENO schemes achieve large savings of CPU times on refined meshes,and at the same time maintain comparable accuracy and resolution with those on corresponding regular single grids.

关键词： Fixed-point fast sweeping methods Weighted essentially non-oscillatory(WENO)schemes Sparse grids Static Hamilton-Jacobi(H-J)equations Eikonal equations

Sustainable food waste management using modified fuzzy improved analytic hierarchy process:a study of Malaysia

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Waste Disposal and Sustainable Energy 2024年第1期6卷 63-84页

作者： Chun Yuan Choo Syariza Abdul-Rahman Abdul Malek Yaakob Emy E.A-Jalil department of Decision Science School of Quantitative SciencesUniversiti Utara Malaysia06010SintokKedahMalaysia Institute of Strategic Industrial Decision Modeling School of Quantitative SciencesCollege of Arts and SciencesUniversiti Utara Malaysia06010SintokKedahMalaysia Technology and Supply Chain Excellence Institute School of Technology Management and LogisticsUniversiti Utara Malaysia06010SintokKedahMalaysia

Food waste generation is a pressing issue that requires urgent attention and concerted efforts worldwide.The staggering amount of food wasted each year not only wastes valuable resources but also exacerbates environmental,economic,and social challenges.Food Waste Management(FWM)consists of a complex array of criteria and sub-criteria,and treatments which seems interdependent.There is a need to evaluate the FWM with the help of important criteria and sub-criteria and treatments to address this challenge.In this study,we identified four important criteria,21 sub-criteria,and four alternatives of FWM for the case of Malaysia using the integrated approach of literature review and expert opinions.Further,we employed the approach of Modified Fuzzy Improved Analytical Hierarchy Process(IAHP)to corroborate the interrelationships among the identified criteria and sub-criteria,and their associated treatments.This study undertakes linear normalization methods to transform data into comparable numerical values and the Geometric Mean method to handle uncertainty in human judgments.Moreover,the Centroid method is employed to convert fuzzy weights into crisp sets for ease of interpretation.The results indicate that environmental is the most essential criterion,followed by social,economic,and technical.In addition,air and water pollution is identified as the most critical sub-criteria.Black Soldier Fly is discovered as the most sustainable FWM treatment,since it performs the best while meeting all the criteria and sub-criteria assessed.Sensitivity analysis demonstrates that the outputs from the proposed method are robust and reliable.The finding suggests a proper and robust approach to help decision-makers select suitable FWM treatments to tackle various criteria and alternatives especially when handling inconsistent and uncertain judgments during evaluation.

关键词： Multi-criteria decision-making Sustainable food waste management Improved Analytical Hierarchy Process Fuzzy method Sensitivity analysis

Data-driven slicing for dimension reduction in regressions:A likelihood-ratio approach

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China Mathematics 2024年第3期67卷 647-664页

作者： Peirong Xu Tao Wang Lixing Zhu department of statistics Shanghai Jiao Tong UniversityShanghai 200240China Center for statistics and Data Science Beijing Normal University at ZhuhaiZhuhai 519087China

To efficiently estimate the central subspace in sufficient dimension reduction,response discretization via slicing its range is one of the most used methodologies when inverse regression-based methods are applied.However,existing slicing schemes are almost all ad hoc and not widely accepted.Thus,how to define datadriven schemes with certain optimal properties is a longstanding problem in this field.The research described here is then twofold.First,we introduce a likelihood-ratio-based framework for dimension reduction,subsuming the popularly used methods including the sliced inverse regression,the sliced average variance estimation and the likelihood acquired direction.Second,we propose a regularized log likelihood-ratio criterion to obtain a data-driven slicing scheme and derive the asymptotic properties of the estimators.A simulation study is carried out to examine the performance of the proposed method and that of existing methods.A data set concerning concrete compressive strength is also analyzed for illustration and comparison.

关键词： full-likelihood approach adaptive slicing regularization second-order method

A Local Macroscopic Conservative(LoMaC)Low Rank Tensor Method with the Discontinuous Galerkin Method for the Vlasov Dynamics

在线全文

学校读者我要写书评

暂无评论

Communications on Applied Mathematics and Computation 2024年第1期6卷 550-575页

作者： Wei Guo Jannatul Ferdous Ema Jing-Mei Qiu department of Mathematics and statistics Texas Tech UniversityLubbockTX70409USA department of Mathematical Sciences University of DelawareNewarkDE19716USA

In this paper,we propose a novel Local Macroscopic Conservative(LoMaC)low rank tensor method with discontinuous Galerkin(DG)discretization for the physical and phase spaces for simulating the Vlasov-Poisson(VP)system.The LoMaC property refers to the exact local conservation of macroscopic mass,momentum,and energy at the discrete level.The recently developed LoMaC low rank tensor algorithm(arXiv:2207.00518)simultaneously evolves the macroscopic conservation laws of mass,momentum,and energy using the kinetic flux vector splitting;then the LoMaC property is realized by projecting the low rank kinetic solution onto a subspace that shares the same macroscopic observables.This paper is a generalization of our previous work,but with DG discretization to take advantage of its compactness and flexibility in handling boundary conditions and its superior accuracy in the long term.The algorithm is developed in a similar fashion as that for a finite difference scheme,by observing that the DG method can be viewed equivalently in a nodal fashion.With the nodal DG method,assuming a tensorized computational grid,one will be able to(i)derive differentiation matrices for different nodal points based on a DG upwind discretization of transport terms,and(ii)define a weighted inner product space based on the nodal DG grid points.The algorithm can be extended to the high dimensional problems by hierarchical Tucker(HT)decomposition of solution tensors and a corresponding conservative projection algorithm.In a similar spirit,the algorithm can be extended to DG methods on nodal points of an unstructured mesh,or to other types of discretization,e.g.,the spectral method in velocity direction.Extensive numerical results are performed to showcase the efficacy of the method.

关键词： Hierarchical Tucker(HT)decomposition Conservative SVD Energy conservation Discontinuous Galerkin(DG)method

Sequential good lattice point sets for computer experiments

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China Mathematics 2024年

作者： Xue-Ru Zhang Yong-Dao Zhou Min-Qian Liu Dennis K.J.Lin NITFID LPMC & KLMDASR School of Statistics and Data Science Nankai University department of statistics Purdue University

Sequential Latin hypercube designs (SLHDs) have recently received great attention for computer experiments, with much of the research restricted to invariant spaces. The related systematic construction methods are inflexible, and algorithmic methods are ineffective for large designs. For designs in contracting spaces, systematic construction methods have not been investigated yet. This paper proposes a new method for constructing SLHDs via good lattice point sets in various experimental spaces. These designs are called sequential good lattice point (SGLP) sets. Moreover, we provide efficient approaches for identifying the (nearly)optimal SGLP sets under a given criterion. Combining the linear level permutation technique, we obtain a class of asymptotically optimal SLHDs in invariant spaces, where the L1-distance in each stage is either optimal or asymptotically optimal. Numerical results demonstrate that the SGLP set has a better space-filling property than the existing SLHDs in invariant spaces. It is also shown that SGLP sets have less computational complexity and more adaptability.

关键词：

Optimal investment and consumption with forward preferences and uncertain parameters

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Probability, Uncertainty and quantitative Risk 2024年第1期9卷 65-84页

作者： Wing Fung Chong Gechun Liang Marwell Institute for Mathematical Sciences and department of Actuarial Mathematics and statistics Heriot-Watt UniversityEdinburgh EH144ASUK department of statistics The University of WarwickCoventry CV47ALUK

We introduce and analyze a class of forward performance criteria in incomplete markets in the presence of model ambiguity.Incompleteness stems from general investment constraints,while model uncertainty is represented by a convex and compact set of plausible model parameter processes.Following the max-min criteria in traditional(backward)robust control,we formulate similar criteria for the robust forward performance processes and focus on the rich class of time-monotone processes.We provide a novel PDE characterization and a semi-explicit saddle-point construction of the robust forward performance criteria and their optimal policies.Furthermore,we present additional results within the class of homothetic constant relative risk aversion(CRRA)processes.Within this class,we investigate the relationship between forward performance processes on wealth and those on consumption,establishing an interesting dominance through time.

关键词： Robust forward performance criteria Portfolio constraints Consumption Saddle points Constant relative risk aversion

Bound-Preserving Discontinuous Galerkin methods with Modified Patankar Time Integrations for Chemical Reacting Flows

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Communications on Applied Mathematics and Computation 2024年第1期6卷 190-217页

作者： Fangyao Zhu Juntao Huang Yang Yang department of Mathematical Sciences Michigan Technological UniversityHoughtonMI49931USA department of Mathematics and statistics Texas Tech UniversityLubbockTX79409USA

In this paper,we develop bound-preserving discontinuous Galerkin(DG)methods for chemical reactive flows.There are several difficulties in constructing suitable numerical schemes.First of all,the density and internal energy are positive,and the mass fraction of each species is between 0 and 1.Second,due to the rapid reaction rate,the system may contain stiff sources,and the strong-stability-preserving explicit Runge-Kutta method may result in limited time-step sizes.To obtain physically relevant numerical approximations,we apply the bound-preserving technique to the DG methods.Though traditional positivity-preserving techniques can successfully yield positive density,internal energy,and mass fractions,they may not enforce the upper bound 1 of the mass fractions.To solve this problem,we need to(i)make sure the numerical fluxes in the equations of the mass fractions are consistent with that in the equation of the density;(ii)choose conservative time integrations,such that the summation of the mass fractions is preserved.With the above two conditions,the positive mass fractions have summation 1,and then,they are all between 0 and 1.For time discretization,we apply the modified Runge-Kutta/multi-step Patankar methods,which are explicit for the flux while implicit for the source.Such methods can handle stiff sources with relatively large time steps,preserve the positivity of the target variables,and keep the summation of the mass fractions to be 1.Finally,it is not straightforward to combine the bound-preserving DG methods and the Patankar time integrations.The positivity-preserving technique for DG methods requires positive numerical approximations at the cell interfaces,while Patankar methods can keep the positivity of the pre-selected point values of the target variables.To match the degree of freedom,we use polynomials on rectangular meshes for problems in two space dimensions.To evolve in time,we first read the polynomials at the Gaussian points.Then,suitable slope limiters can be applied to enforce the positivity

关键词： Compressible Euler equations Chemical reacting flows Bound-preserving Discontinuous Galerkin(DG)method Modified Patankar method