Simplex-based screening designs for estimating metamodels

The screening method proposed by Morris in 1991 allows to identify the important factors of a model, including those involved in interactions. This method, known as the elementary effects method, relies on a “one-factor-at-a-time” (OAT) design of experiments, i.e. two successive points differ only by one factor. In this article, we introduce a non-OAT simplex-based design for the elementary effects method. Its main advantage, compared to Morris's OAT design, is that the sample size does not collapse when the design is projected on sub-spaces spanned by groups of factors. The use of this design to estimate a metamodel depending only on the (screened) important factors is discussed.     

Graph analysis of non-uniform rational B-spline-based metamodels

Over the past decade metamodels, also known as surrogate models, based on non-uniform rational B-splines (NURBs) have been developed. These metamodels exhibit unique properties that enable a wide range of computationally efficient analyses. Thus far, the analysis of these metamodels has been of a geometric nature, but in this article an approach based on graph theory is used. The properties of NURBs enable the interpretation of NURBs-based metamodels as graphs, and enable the demonstration of several analyses based on this structure. The general case of an analytically defined continuous-variable problem is given in the first example. A specific application in the field of robotic path planning constitutes the second example. Finally, an observation on the current state of this research, its merits and drawbacks, and an outline of future efforts that may increase its utility is provided.     

Research on high-dimensional model representation with various metamodels

Constructing approximation models with surrogate modelling is often carried out in engineering design to save computational cost. However, the problem of the ‘curse of dimensionality’ still exists, and high-dimensional model representation (HDMR) has been proven to be very efficient in solving high-dimensional, computationally expensive black-box problems. This article proposes a new HDMR by combining separate stand-alone metamodels to form an ensemble based on cut-HDMR. It can improve prediction accuracy and alleviate prediction uncertainty for different problems compared with previous HDMRs. In this article, 10 representative mathematical examples and two engineering examples are used to illustrate the proposed technique and previous HDMRs. Furthermore, a comprehensive comparison of four metrics between the ensemble HDMR and other single HDMRs is presented, with a wide scope of dimensionalities. The results show that the single HDMRs perform well on specified examples but the ensemble HDMR provides more accurate predictions for all the test problems.     

Extending grammars and metamodels for reuse: the Reuseware approach

The trend towards domain-specific languages leads to an ever-growing plethora of highly specialised languages. Developers of such languages focus on their specific domains rather than on the technical challenges of language design. The generic features of languages are rarely included in special-purpose languages. One very important feature is the ability to formulate partial programs in separate encapsulated entities, which can be composed into complete programs in a well-defined manner. A language-independent approach is presented that adds useful constructs for defining components. The authors discuss the underlying concepts and describe a composition environment and tool supporting these ideas-the reuseware composition framework. To evaluate this approach, the authors enrich the (Semantic) Web query language Xcerpt with an additional useful reuse concept - modules.     

A pseudo-random number assignment strategy for the estimation of quadratic metamodels

Whereas an optimal Pseudo-Random Number (PRN) assignment strategy for simulation experiments involving the estimation of linear metamodels currently exists, no such optimal assignment strategy for quadratic metamodels has been proposed. This situation is now rectified by the introduction of a PRN assignment strategy for a quadratic metamodel for 3^k factorial designs. In addition to extending the theory from linear to quadratic metamodels, the proposed PRN strategy is shown to be superior to a number of existing and competing strategies in terms of various variance measures.     

A new sampling scheme for developing metamodels with the zeros of Chebyshev polynomials

The accuracy of metamodelling is determined by both the sampling and approximation. This article proposes a new sampling method based on the zeros of Chebyshev polynomials to capture the sampling information effectively. First, the zeros of one-dimensional Chebyshev polynomials are applied to construct Chebyshev tensor product (CTP) sampling, and the CTP is then used to construct high-order multi-dimensional metamodels using the ‘hypercube’ polynomials. Secondly, the CTP sampling is further enhanced to develop Chebyshev collocation method (CCM) sampling, to construct the ‘simplex’ polynomials. The samples of CCM are randomly and directly chosen from the CTP samples. Two widely studied sampling methods, namely the Smolyak sparse grid and Hammersley, are used to demonstrate the effectiveness of the proposed sampling method. Several numerical examples are utilized to validate the approximation accuracy of the proposed metamodel under different dimensions.     

Analyzing the behavior and reliability of voting systems comprising tri-state units using enumerated simulation

Voting is a common technique used in combining results from peer experts, for multiple purposes, and in a variety of domains. In distributed decision making systems, voting mechanisms are used to obtain a decision by incorporating the opinion of multiple units. Voting systems have many applications in fault tolerant systems, mutual exclusion in distributed systems, and replicated databases. We are specifically interested in voting systems as used in decision-making applications.In this paper, we describe a synthetic experimental procedure to study the behavior of a variety of voting system configurations using a simulator to: analyze the state of each expert, apply a voting mechanism, and analyze the voting results. We introduce an enumerated-simulation approach and compare it to existing mathematical approaches. The paper studies the following behaviors of a voting system: (1) the reliability of the voting system, R; (2) the probability of reaching a consensus, P_c; (3) certainty index, T; and (4) the confidence index, C. The configuration parameters controlling the analysis are: (1) the number of participating experts, N, (2) the possible output states of an expert, and (3) the probability distribution of each expert states. We illustrate the application of this approach to a voting system that consists of N units, each has three states: correct (success), wrong (failed), and abstain (did not produce an output). The final output of the decision-making (voting) system is correct if a consensus is reached on a correct unit output, abstain if all units abstain from voting, and wrong otherwise. We will show that using the proposed approach, we can easily conduct studies to unleash several behaviors of a decision-making system with tri-state experts.     

计量分析软件的测试

部分实验室在计量检定、校准、检验、测试工作中,为了提高工作效率,自主研发一些数据处理等分析软件,而软件在投入使用时由于对测试方法欠缺和对测试缺乏有效管理,未进行严格的测试就投入使用,有可能导致不可预测后果的毛病或者缺陷.本文介绍软件测试基本概念和测试方法,目的是提高软件产品质量.     

试析战略创新的复杂性

指明了战略创新研究属于复杂性科学,依据系统学原理诠释创新概念;论述了战略创新的复杂性在 于它自身内含的对立统一;论证了国家战略创新是开放复杂巨系统,并指出驾驭这种复杂性需要建设创新型 国家。     

工业设计的符号学审视

从符号学的视点来审视工业设计的认识论与方法论的问题。并从符号类别、符号规则、符号功能、信文编码、信道特性等方面论述工业设计与造型艺术及工艺美术间的异同。