动态测量数据的合理性检验方法研究

采样数据合理性检验,是数据处理中重要的一环,它的主要功能是鉴别采样数据中可能含有的异常值,并进行相应的机理分析与修复工作.本文从飞行器外测系统工程应用的角度出发,给出了两种简单易行的判断方法.     

INTERNATIONAL BIODIVERSITY CONSERVATION AGREEMENTS

ABSTRACT. A public goods model of global biodiversity conservation is exposited. Distinguishing features of global biodiversityconservation tasks are identified. Global efficiencyof biodiversityconservation is discussed and some comparative statics of efficient programs provided. The transfers required from high‐existence‐value, low‐conservation‐productivitynations to low‐existence‐value, high‐conservation‐productivitynations, to realize global efficiencyin conservation effort, are analyzed.     

Frame theory in directional statistics

Distinguishing between uniform and non-uniform sample distributions is a common problem in directional data analysis; however for many tests, non-uniform distributions exist that fail uniformity rejection. To predict these distributions, we merge directional statistics with frame theory and find that probabilistic tight frames yield non-uniform distributions that minimize directional potentials, leading to failure of uniformity rejection for the Bingham test. Finally, we apply our results to model patterns found in granular rod experiments.     

Detecting low-dimensional chaos by the “noise titration” technique: Possible problems and remedies

Distinguishing low-dimensional chaos from noise is an important issue in time series analysis. Among the many methods proposed for this purpose is the noise titration technique, which quantifies the amount of noise that needs to be added to the signal to fully destroy its nonlinearity. Two groups of researchers recently have questioned the validity of the technique. In this paper, we report a broad range of situations where the noise titration technique fails, and offer solutions to fix the problems identified.     

Selection principles in hyperspaces with generalized Vietoris topologies

We continue investigations of ?ech closure spaces and their hyperspaces started in [M. Mrševi?, M. Jeli?, Selection principles and hyperspace topologies in closure spaces, J. Korean Math. Soc. 43 (2006) 1099-1114] and [M. Mrševi?, M. Jeli?, Selection principles, γ-sets and αi-properties in ?ech closure spaces, Topology Appl., in press], focusing on generalized upper and lower Vietoris topologies.     

Solving feature subset selection problem by a Parallel Scatter Search

The aim of this paper is to develop a Parallel Scatter Search metaheuristic for solving the Feature Subset Selection Problem in classification. Given a set of instances characterized by several features, the classification problem consists of assigning a class to each instance. Feature Subset Selection Problem selects a relevant subset of features from the initial set in order to classify future instances. We propose two methods for combining solutions in the Scatter Search metaheuristic. These methods provide two sequential algorithms that are compared with a recent Genetic Algorithm and with a parallelization of the Scatter Search. This parallelization is obtained by running simultaneously the two combination methods. Parallel Scatter Search presents better performance than the sequential algorithms.     

A counterexample to the Bartle-Graves selection theorem for multilinear maps

We present an example showing that the multilinear version of the Bartle-Graves Selection Theorem is false, even on finite dimensional spaces.

     

Kinna-Wagner selection principles, axioms of choice and multiple choice

We study the relationships between weakened forms of the Kinna-Wagner Selection Principle (KW), the Axiom of Choice (AC), and the Axiom of Multiple Choice (MC).     

Single cut and multicut stochastic dual dynamic programming with cut selection for multistage stochastic linear programs: convergence proof and numerical experiments

Computational Management Science - We introduce a variant of Multicut Decomposition Algorithms, called CuSMuDA (Cut Selection for Multicut Decomposition Algorithms), for solving multistage...     

基于模糊优选决策的炮兵火力分配模型研究

将模糊优选决策方法应用于炮兵战场火力分配,综合考虑影响火力分配的各种因素,建立模糊优选决策矩阵,等到优化分配的模型.     

Constrained optimization of the randomized iterative method

Selection of conditionally optimal parameters of the randomized iterative method for solving large-scale linear systems of equations is considered. The error of this method is analyzed by analogy with the functional Monte Carlo algorithms. For the simple iteration method, the “column” randomization of the matrix is thoroughly analyzed.     

Fuzzy Application to the Analytic Hierarchy Process for Robot Selection

The problem of Robot Selection is of great relevance in the present times of automation. Traditionally such problems were addressed using conventional techniques of Multi Criteria Decision Making such as The Analytic Hierarchy Process (AHP) and The Multi Attribute Utility Theory (MAUT). This paper proposes a methodology for solving common Robot Selection problems using a modification of the conventional AHP by incorporating ‘Fuzzy Linguistic Variables’ in place of numbers. The methodology encapsulates creation of Fuzzy Interface for conversion of input and output variables into suitable linguistic variables. Further, employing the fuzzification process by assigning the linguistic variables to numerical values of the membership functions and formulating suitable decision rules, the procedure culminates into the defuzzification process for converting fuzzy output into crisp value and obtaining the result in the form of Fuzzy Score. The proposed model is explained using a numerical example. The paper also presents a validation of the proposed methodology over real world problems and provides directions for future research towards the end.Additional support was provided by the National Science Foundation.     

Microplane modeling of cyclic behavior of concrete: a gradient plasticity-damage formulation

A microplane model is developed to simulate the behavior of concrete under cyclic loading conditions. Pure damage mechanics or pure plasticity models yield satisfactory results for concrete under monotonic loading but cannot capture correctly the unloading and reloading response. Therefore, coupling damage and plasticity is necessary for accurate constitutive modeling of concrete. The microplane model offers a straightforward approach to simulate induced anisotropy by formulating the material laws on many randomly oriented planes. Distinguishing between compression and tension response using the proper plastic yield function and damage laws is considered. Furthermore, gradient enhancement is employed to handle the pathological mesh sensitivity related to strain softening. The new formulation is implemented within a 3D finite element code and a numerical example is simulated and compared to experiments in order to evaluate the capabilities of the model. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Reconstruction of periodic sceneries seen along a random walk

This article was motivated by a question of Kesten. Kesten asked for which random walks periodic sceneries can be reconstructed. Among others, he asked the question for random walks which at each step can move by one or two units to the right. Previously, Howard [C.D. Howard, Distinguishing certain random sceneries on Z$\mathbb{Z}$ via random walks, Statist. Probab. Lett. 34 (2) (1997) 123–132] proved that all periodic sceneries can be reconstructed provided they are observed along the path of a simple random walk.     

Exact and heuristic algorithms for the Travelling Salesman Problem with Multiple Time Windows and Hotel Selection

We introduce and study the Travelling Salesman Problem with Multiple Time Windows and Hotel Selection (TSP-MTWHS), which generalises the well-known Travelling Salesman Problem with Time Windows and the recently introduced Travelling Salesman Problem with Hotel Selection. The TSP-MTWHS consists in determining a route for a salesman (eg, an employee of a services company) who visits various customers at different locations and different time windows. The salesman may require a several-day tour during which he may need to stay in hotels. The goal is to minimise the tour costs consisting of wage, hotel costs, travelling expenses and penalty fees for possibly omitted customers. We present a mixed integer linear programming (MILP) model for this practical problem and a heuristic combining cheapest insert, 2-OPT and randomised restarting. We show on random instances and on real world instances from industry that the MILP model can be solved to optimality in reasonable time with a standard MILP solver for several small instances. We also show that the heuristic gives the same solutions for most of the small instances, and is also fast, efficient and practical for large instances.     

Rival approaches to mathematical modelling in immunology

In order to formulate quantitatively correct mathematical models of the immune system, one requires an understanding of immune processes and familiarity with a range of mathematical techniques. Selection of an appropriate model requires a number of decisions to be made, including a choice of the modelling objectives, strategies and techniques and the types of model considered as candidate models. The authors adopt a multidisciplinary perspective.     

Selection bias in credit scorecard evaluation

Selection bias is a perennial problem when constructing and evaluating scorecards. It is familiar in the context of reject inference, but crops up in many other situations as well. In this paper, we examine the impact of how accepting or rejecting customers using one scorecard leads to biased comparisons of performance between that scorecard and others. This has important implications for organisations seeking to improve or replace scorecards.     

On parallel Branch and Bound frameworks for Global Optimization

Branch and Bound (B&B) algorithms are known to exhibit an irregularity of the search tree. Therefore, developing a parallel approach for this kind of algorithms is a challenge. The efficiency of a B&B algorithm depends on the chosen Branching, Bounding, Selection, Rejection, and Termination rules. The question we investigate is how the chosen platform consisting of programming language, used libraries, or skeletons influences programming effort and algorithm performance. Selection rule and data management structures are usually hidden to programmers for frameworks with a high level of abstraction, as well as the load balancing strategy, when the algorithm is run in parallel. We investigate the question by implementing a multidimensional Global Optimization B&B algorithm with the help of three frameworks with a different level of abstraction (from more to less): Bobpp, Threading Building Blocks (TBB), and a customized Pthread implementation. The following has been found. The Bobpp implementation is easy to code, but exhibits the poorest scalability. On the contrast, the TBB and Pthread implementations scale almost linearly on the used platform. The TBB approach shows a slightly better productivity.