Quadratic distances for capacity and bi-capacity approximation and identification

The application of multi-attribute utility theory based on the Choquet integral requires the prior identification of a capacity if the utility scale is unipolar, or of a bi-capacity if the utility scale is bipolar. In order to implement a minimum distance principle for capacity or bi-capacity approximation or identification, quadratic distances between capacities and bi-capacities are studied. The proposed approach, consisting in solving a strictly convex quadratic program, has been implemented within the GNU R kappalab package for capacity and nonadditive integral manipulation. Its application is illustrated on two examples.      

Performance evaluation of a distributed application

Analysing the performance of an application performed on a distributed system is discussed in this paper. An analogy between a distributed system and a production process is portrayed, particularly for an application running on several computers. Consequently, theories of management of production processes are employed to help analyse and manage distributed systems, specifically, the Theory of Constraints (TOC). Using TOC combined with the cost/utilization model, which was initially developed to evaluate the utilization of a single processor and is extended here to handle a distributed system, it is demonstrated how the performance of a distributed system can be examined. The methodology presented here is based on a simple graphic display aimed to allow managers of information systems to locate constrained resources, to optimize the distribution of the computer application, and to examine and pinpoint improper imbalances and fluctuations in the system workload. The model develops into a management decision support tool that may be applied in areas such as buffer policy, assessment of protective capacity, investment in computer resources, and identification of areas for improvement.     

Benchmark optimization and attribute identification for improvement of container terminals

The aim of this paper is to optimize the benchmarks and prioritize the variables of decision-making units (DMUs) in data envelopment analysis (DEA) model. In DEA, there is no scope to differentiate and identify threats for efficient DMUs from the inefficient set. Although benchmarks in DEA allow for identification of targets for improvement, it does not prioritize targets or prescribe level-wise improvement path for inefficient units. This paper presents a decision tree based DEA model to enhance the capability and flexibility of classical DEA. The approach is illustrated through its application to container port industry. The method proceeds by construction of multiple efficient frontiers to identify threats for efficient/inefficient DMUs, provide level-wise reference set for inefficient terminals and diagnose the factors that differentiate the performance of inefficient DMUs. It is followed by identification of significant attributes crucial for improvement in different performance levels. The application of this approach will enable decision makers to identify threats and opportunities facing their business and to improve inefficient units relative to their maximum capacity. In addition, it will help them to make intelligent investment on target factors that can improve their firms’ productivity.     

Modelling and identification of rigid‐body dynamics of parallel kinematic structures

A new approach for modelling the dynamics of parallel kinematic (PKM) structures is presented in this paper. It leads to a formulation of the dynamic equations which is linear with respect to a dynamic parameter vector of minimal dimension. Thus, the equations can be directly used for parameter identi.cation by linear estimation techniques. The algorithm utilises Jourdain 's principle of virtual power which leads to very efficient resulting code. The parameter reduction is based on opening the kinematic loops so that analytic rules known from serial robots can be implemented. Additionally, a new approach for dynamic parameter identification is suggested. The application to modelling the PKM PaLiDa and identifying its gravitational parameters proves the capacity of the presented approaches.     

Identification of Parameters of Nonlinear Dynamical Systems Simulated by Volterra Polynomials

We study the identification methods for the nonlinear dynamical systems described by Volterra series. One of the main problems in the dynamical system simulation is the problem of the choice of the parameters allowing the realization of a desired behavior of the system. If the structure of the model is identified in advance, then the solution to this problem closely resembles the identification problem of the system parameters. We also investigate the parameter identification of continuous and discrete nonlinear dynamical systems. The identification methods in the continuous case are based on application of the generalized Borel Theorem in combination with integral transformations. To investigate discrete systems, we use a discrete analog of the generalized Borel Theorem in conjunction with discrete transformations. Using model examples, we illustrate the application of the developed methods for simulation of systems with specified characteristics.     

基于替代数据法和MF-DFA的合意工业产能利用率区间估计方法及应用

为实现工业产能过剩的精准判别与调控，提出了一种基于替代数据法与多重分形去趋势波动分析的合意工业产能利用率区间估计方法。首先判断原始时序的长程相关性和多重分形特征；然后采用替代数据法与多重分形去趋势波动分析计算出所有重排序列的Hurst指数，据此确定指数序列收敛情况和合意产能利用率区间；最后以煤炭行业为例验证了模型的有效性。结果表明：该方法能够从数据自身演化规律中自适应确定阈值，有效克服了传统统计与经验方法的主观性和缺乏理论依据的局限性；我国煤炭行业的合意产能利用率区间为73.73%～86.23%。该研究为工业产能过剩风险监测与判别提供了量化分析工具，为深化煤炭产能过剩治理提供了决策依据。     

组织学习能力的个性优势识别与评价研究

组织学习能力是个多维概念,定期识别在哪个维度上具备个性优势并在此基础上对组织学习能力状况做出评价将有利于促进组织绩效的提升。本文按照目标规划的思想,依据2-范数距离,提出一种组织学习能力的个性优势识别方法,该方法从尊重每一位被评价者的意见出发识别其个性优势特征,并在此基础上给出综合评价结论。在此基础上以国内某大型软件企业的20个事业部为例进行了应用研究,组织学习能力由发现能力、发明能力、选择能力、执行能力、推广能力、反思能力、获取知识能力、输出知识能力、建立知识库能力九个维度组成。研究结果表明,基于个性优势识别的组织学习能力评价方法符合“人本管理”思想,易于被评价主体接受,且具有客观性的特点,同时可以产生标杆效应。     

A data analysis of residential demand for natural gas using step-down multiple comparison tests

Multiple comparison tests are not ordinarily employed in econometric analysis. An example of the application of a step-down approach to a much studied problem is set forth. Comments on the estimated results and on the relevance of these tests to the present and other economic analyses are also presented. The application of the multiple comparison tests aids in the identification of a relatively simple regression equation of residential natural gas demand.     

A generalized cubic spline technique for identification of multivariable systems

The application of cubic splines to the identification of time-invariant systems is considered. The use of splines, initially proposed by Bellman in 1971, has been extended to the multidimensional case. In addition, the effects of noise on the identification procedure are considered and techniques are presented for improving the identification accuracy. A general spline technique, used in conjunction with a Kalman estimation procedure, has been developed for identifying physical systems described by a set of first-order differential equations. This method has been found to be superior to the exponential fitting technique proposed by Prony and to other finite-difference methods.     

The risk and information sharing of application services supply chain

We study an application services supply chain consisting of one application service provider (ASP) and one application infrastructure provider (AIP). The AIP supplies the computer capacity to the ASP that in turn sells the value-added application services to the market. The market is characterized by a price-sensitive random demand. The ASP’s objective is to determine the optimal price of its service to the market and the optimal capacity to purchase from the AIP. The AIP’s goal on the other hand is to maximize its profit from selling the capacity to the ASP.     

A Decision Making Method for the Quality Identification of Wines Based on Fuzzy Soft Sets

Quality identification of wines is a crucial one for wine industry. The paper aims to give a decision making approach based on soft fuzzy sets for it. First, based on fuzzy soft sets, calculation steps are given to solve decision making problems. The grey relative coefficient between each alternative with the ideal alternative is calculated by grey relational analysis (GRA). Then, a relative relational degree is defined to determine ranking orders of all alternatives. Finally, an application of our proposed approach demonstrates its practicality and effectiveness in the quality identification of red wines.     

结构系统识别不确定性分析的Bayes方法及其进展

受测试误差、建模误差、数值离散化以及环境变异等因素的影响,结构系统识别过程不可避免地存在不确定性,因此有必要引入概率统计方法来提高其鲁棒性,为工程结构安全监测提供更为可靠的结果.近年来,Bayes(贝叶斯)方法因为其诸多优势在系统识别领域受到了广泛关注.该文梳理了Bayes系统识别的历史脉络和研究进展.从Bayes系统识别的理论框架出发,分析了量化系统识别不确定性两类方法的适用条件与局限性.此外,文章综述了Bayes方法在模态参数识别、有限元模型修正以及结构损伤识别方面进行不确定性分析的理论、实现及其应用.最后对基于Bayes方法进行系统识别研究的发展趋势做出了展望.     

A receding horizon D-optimization approach for model identification–oriented input design and application in combustion engines

In this paper, a receding horizon D-optimization approach for model identification–oriented input design is proposed, and a practical application is demonstrated for internal combustion engines. The proposed approach consists of a recursive parameter identification algorithm and an input signal design algorithm; where the latter provides D-optimal excitation signal for the adaptation of the parameter estimation in the following identification phase. The D-optimization algorithm is constructed with the Continuation/GMRES method, which provides an approximate solution according to the current parameter of the model. To validate effectiveness and feasibility of the proposed approach, testing results applying the proposed approach to an internal combustion engine are demonstrated and conducted on a full-scale engine test bench.     

The aggregate capacity of virtual resources – linear models

This article addresses resource modelling with a specific interest on capacity aggregation. The capacity of a resource with regard to d types of tasks is modelled by a simplex and by a cube in the d-dimensional space. The aggregate capacity model of a virtual resource, that is, of a pool of r resources, is the d-polytope provided by the Minkowski sum of the simplices and cubes modelling the resources. The parametric identification of the d-planes supporting the facets of the polytope is established for r?=?2 and linear simplifications are provided in the (r,?d) general case. Formulated as linear inequalities, the aggregate capacity models fit in with linear programming and quadratic programming optimization techniques.     

Cubic-spline identification of distributed-parameter systems

The use of doubly cubic splines is presented for the identification of a general second-order distributed-parameter system. The application of doubly cubic splines is shown to result in a system of linear algebraic equations that may be solved for the unknown process parameters in an on-line recursive manner. Due to the advantageous properties of splines, the approximation of partial derivatives is shown to incorporate temporal and spatial smoothing, an important feature when process data is subject to random disturbances. Coefficients of extraneous terms in the assumed model are also correctly identified. A comparison of the spline technique with other identification schemes in current use indicates that the spline application is consistently superior with regard to accuracy of estimation and rate of convergence.     

一类决策模型及其在石油开采中的应用

介绍一类决策评判模型,分析了其建模方法,将它应用于石油油井开发中,对油井进行评估与识别,取得好的效果.     

Gradient based iterative parameter identification for Wiener nonlinear systems

This paper focuses on the identification problem of Wiener nonlinear output error systems. The application of the key-term decomposition technique provides a special form of the Wiener model with polynomials, where all the model parameters to be estimated are separated. To solve the identification problem of Wiener nonlinear output error systems with the unmeasurable variables in the information vector, an auxiliary model-based gradient iterative algorithm is presented by replacing the unmeasurable variables with their corresponding iterative estimates. The performances of the proposed algorithm are analyzed and compared by using numerical examples.     

The generalized Leontief input-output model and its application to the choice of new technology

The Leontief input-output model is generalized and formulated as a generalized linear complementarity problem. Conditions for existence of solutions are given, and solution techniques are reviewed. An application of the model to choosing new technologies is suggested.     

Based on Walsh packet parametric identification technique for dynamic systems

The article presents an application of wavelet packet analysis in the parametric identification of discrete dynamic systems. The Walsh packet basis and their operational matrixes enables reduction of row derivatives, which are necessary in the procedure of identification of signal derivatives for systems, which are analyzed, and also enable algebraization their mathematical describe, what in combination with wavelet packet analysis with Haar filter properties decided on a great efficiency of parametric identification of linear systems procedure, which is built on wavelet packet analysis. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)