一种弱小目标的自适应搜索方法

针对成像跟踪系统中弱小目标搜索定位的难题,提出了一种新的自适应搜索算法,即利用全局寻优的自适应遗传算法搜索目标,以目标的多特征融合信息作为最佳定位的判断准则和适应度函数。实验结果表明,该方法不仅提高了检测精度,也改善了跟踪算法的稳定性和智能策略。     

An adaptive dynamic relaxation method for static problems

The present paper re-defines the parameters of the dynamic relaxation method for static problems and examines how they affect the rate of convergence of the method. A new adaptive scheme is proposed to improve the efficiency and accuracy of the method. The scheme involves using the current residual vector to update the lower frequency limit during integration and to improve the accuracy of the converged solution. The new approach compares favorably with the results of a previously proposed adaptive method.This work was initiated in 1984 while the author was visiting the Southwestern Jiaotong University, Sichuan, China. The author wishes to express his appreciation to Professors R. Greif and D. P. Chan for their many useful comments     

An adaptive path selection method for delay testing

For verifying the correctness of a circuit, not only its logic function, but also its timing behavior must be considered. Although the path delay fault model can handle part of the weakness of the gate delay fault model, it also has inherent deficiencies. Since the number of paths in a logic circuit is tremendous, exhaustively testing each signal propagation path is prohibitive. To deal with the weakness of traditional delay test techniques, based on the path delay fault model, a new delay test approach including a new delay test output observation method and an adaptive path selection method is proposed in this work. The basic idea of the approach is to measure the signal transition time for each delay test, and more paths are selected for a second-stage test (if necessary) to ensure the timing behavior of the circuit under test. Experimental results obtained by computer simulation demonstrate that a more thorough test is really a need if many significantly late signal transitions are observed     

An adaptive response surface method for crashworthiness optimization

Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.     

An adaptive statistical method for power quality analysis

Digital fault recorders installed for monitoring current and/or voltage waveforms acquire and store vast amount of waveform data for post processing. Because of this, effective offline automated event detection from acquired data is necessary. In this work, we propose a new automatic event detection method which takes the acquired data and produces event flags at instances of events. The method is based on the statistical analysis of adaptive decomposition signals. The combination of an adaptive prediction filter-based subband decomposition structure with a rule-based histogram analysis block produced successful detection and localization results on our real-life power system transient data.     

An adaptive window function method for power measurement

An adaptive window function for distorted power measurement is introduced in this paper. It can automatically provide the optimal window function according to the measured signal. Thus, the applied window function is always optimal in the sense of the zeros of its frequency response corresponding to the undesired measured signal spectrum components which will result in the harmful truncation errors. As a result, the harmful truncation errors of asynchronous sampling and the influence of interharmonics in the measured signal spectrum can be totally eliminated. The correctness, accuracy, and applicability of the proposed method have been verified both theoretically and by extensive simulations     

An adaptive sphere-fitting method for sequential tolerance control

The machining of complex parts typically involves a logical and chronological sequence of n operations on m machine tools. Because manufacturing datums cannot always match design constraints, some of the design specifications imposed on the part are usually satisfied by distinct subsets of the n operations prescribed in the process plan. Conventional tolerance control specifies a fixed set point for each operation and a permissible variation about this set point to insure compliance with the specifications, whereas sequential tolerance control (STC) uses real-time measurement information at the completion of one stage to reposition the set point for subsequent operations. However, it has been shown that earlier sphere-fitting methods for STC can lead to inferior solutions when the process distributions are skewed. This paper introduces an extension of STC that uses an adaptive sphere-fitting method that significantly improves the yield in the presence of skewed distributions as well as significantly reducing the computational effort required by earlier probabilistic search methods.     

An adaptive multiscale method for quasi-static crack growth

This paper proposes an adaptive atomistic- continuum numerical method for quasi-static crack growth. The phantom node method is used to model the crack in the continuum region and a molecular statics model is used near the crack tip. To ensure self-consistency in the bulk, a virtual atom cluster is used to model the material of the coarse scale. The coupling between the coarse scale and fine scale is realized through ghost atoms. The ghost atom positions are interpolated from the coarse scale solution and enforced as boundary conditions on the fine scale. The fine scale region is adaptively enlarged as the crack propagates and the region behind the crack tip is adaptively coarsened. An energy criterion is used to detect the crack tip location. The triangular lattice in the fine scale region corresponds to the lattice structure of the (111) plane of an FCC crystal. The Lennard-Jones potential is used to model the atom–atom interactions. The method is implemented in two dimensions. The results are compared to pure atomistic simulations; they show excellent agreement.     

一种自适应的图像双边滤波方法

提出一种利用双边滤波的图像平滑滤波方法,即在滤除图像中高频噪声的同时,按照图像亮度变化保持图像中处于高频部分的边缘信息的自适应滤波过程。该滤波方法将传统的Gauss滤波器的权系数优化成Gauss函数和图像的亮度信息乘积的形式,优化后的权系数再与图像作卷积运算。这样,滤波时就可以考虑到图像的亮度信息,在滤除图像噪声的同时尽量保持了图像的边缘。由于双边滤波的方法可以使滤波器的权系数随着图像的亮度变化而改变,所以在滤波过程中能达到自适应滤波的目的。     

An adaptive boundary element method

This paper explores the concept of moving singularities in the boundary element analysis. The singularities are placed on an auxiliary boundary which is located outside the domain of the problem and are allowed to move as part of the solution process. This results in a highly adaptive but non-linear method. Examples involving the two- and three-dimensional Laplace's equations are solved. Excellent agreement with exact solutions is obtained using a minimal number of singularities. Also, the trajectories of the singularity motion are plotted. The behaviour seen here is that, as the solution approaches convergence, the singularities exhibit a general trend of moving away from the domain of the problem.     

An Implicit integration scheme for generalized viscoplasticity with dynamic recovery

This paper is concerned with the development of a general implicit time-stepping integrator for the flow and evolution equations in a recent representative class of generalized viscoplastic models, involving both hardening and dynamic recovery mechanisms. To this end, the computational framework is developed on the basis of the unconditionally stable, backward Euler difference scheme. Its mathematical structure is of sufficient generality to allow a systematic treatment of several internal variables of the tensorial and scalar types. The matrix forms developed are directly applicable in general (three-dimensional) situations as well as subspace applications (i.e., plane stress/strain, axisymmetric, generalized plane stress in shells). The closed-form expressions for residual vectors and the algorithmic, (consistent) material tangent stiffness array are given explicitly, with the maximum matrix sizes “optimized” to depend only on the number of independent stress components, but not the number of internal state variables involved. Several numerical simulations are given to assess the performance of the developed schemes.     

An adjoint variable method for sensitivity analysis of non-linear elastic systems

An adjoint variable method for design sensitivity analysis of non-linear elastic systems is presented. The method uses domain parameterization and a mutual form of the Hu-Washizu energy principle, and extends results reported in a recent work for linear elastic systems to non-linear elasticity. Non-linearities due to finite deformations and non-linear, hyperelastic constitutive models are considered. In contrast to other methods for non-linear sensitivity analysis, the present formulation can be applied with force, displacement or mixed approximate solution methods. The mutual energy expression used in the adjoint sensitivity derivation is developed from a non-linear extension of the Hu-Washizu energy functional and yields a linear governing equation for the adjoint system. This has important ramifications for the computational cost of a sensitivity analyses of non-linear systems: excluding the cost of determining the response of the system, the cost of a sensitivity analysis for a non-linear system is essentially the same as that for a linear system. Finite element implementation of the resulting sensitivity expressions is discussed, and two numerical examples are presented. The first example involves large deformations of a Mooney-Rivlin body, while the second involves design sensitivity analysis for mixed solution methods.     

Work-increment-control method for non-linear analysis

To perform non-linear structural analysis including large displacements and rotations requires evaluation of the non-linear equilibrium equations. A quadratically converging, fixed-point iteration scheme, referred to as the work-increment-control solution method, is presented to iteratively evaluate the non-linear algebraic equations. The work-increment-control method is superior, in many respects, to other published solution strategies.     

An adaptive finite element method for transient compressible flows

An adaptive finite element method for the solution of time dependent strongly compressible flows in two dimensions is described. The computational domain is represented by an unstructured assembly of linear triangular elements and the mesh adaptation is achieved by local regeneration of the grid, using an error estimation procedure coupled to an automatic triangular mesh generator. Problems involving shock propagation are solved to illustrate the numerical performance of the proposed approach.     

An adaptive direct multisearch method for black-box multi-objective optimization

Optimization and Engineering - At present, black-box and simulation-based optimization problems with multiple objective functions are becoming increasingly common in the engineering context. In...     

An adaptive directional importance sampling method for structural reliability

In this paper, an adaptive directional importance sampling (ADIS) method is presented. The algorithm is based on a directional simulation scheme in which the most important directions are sampled exact and the others by means of a response surface approach. These most important directions are determined by a β-sphere enclosing the most important part(s) of the limit state. The β-sphere and response surface are constantly updated during sampling with information that becomes available from the exact evaluations making the scheme adaptive.Various widely used test problems, representing a broad range of complex limit states that can occur in practice, of which several that pose potential problems to stochastic methods in general, demonstrate the high efficiency, accuracy and robustness of the method. As such, the ADIS method is of particular interest in applications with a low probability of failure and medium number (up to about 40) of stochastic variables, for instance in aircraft and nuclear industry.     

An adaptive cracking particle method for 2D crack propagation

Computational modelling of fracture has been attempted in the past with a range of numerical approaches including finite element, extended finite element and meshless methods. The cracking particle method (CPM) of Rabczuk is a pragmatic alternative to explicit modelling of crack surfaces in which a crack is represented by a set of cracking particles that can be easily updated when the crack propagates. The change of cracking angle is recorded in discrete segments of broken lines, which makes this methodology suitable to model discontinuous cracks. In this paper, a new CPM is presented that improves on two counts: firstly, crack path curvature modelling is improved by the use of bilinear segments centred at each particle and secondly, efficiency for larger problems is improved via an adaptive process of both refinement and recovery. The system stiffness is calculated and stored in local matrices, so only a small influenced domain should be recalculated for each step while the remainder can be read directly from storage, which greatly reduces the computational expense. The methodology is applied to several 2D crack problems, and good agreement to analytical solutions and previous work is obtained. Copyright © 2016 John Wiley & Sons, Ltd.     

An adaptive finite point method for the shallow water equations

An adaptive Finite Point Method (FPM) for solving shallow water problems is presented. The numerical methodology we propose, which is based on weighted‐least squares approximations on clouds of points, adopts an upwind‐biased discretization for dealing with the convective terms in the governing equations. The viscous and source terms are discretized in a pointwise manner and the semi‐discrete equations are integrated explicitly in time by means of a multi‐stage scheme. Moreover, with the aim of exploiting meshless capabilities, an adaptive h‐refinement technique is coupled to the described flow solver. The success of this approach in solving typical shallow water flows is illustrated by means of several numerical examples and special emphasis is placed on the adaptive technique performance. This has been assessed by carrying out a numerical simulation of the 26th December 2004 Indian Ocean tsunami with highly encouraging results. Overall, the adaptive FPM is presented as an accurate enough, cost‐effective tool for solving practical shallow water problems. Copyright © 2011 John Wiley & Sons, Ltd.     

稀疏表示图像超分辨率重建的自适应方法

提出了一种参数自适应的图像超分辨率重建方法.在基于稀疏表示的图像超分辨率重建的经典算法模型框架下,正则化参数可以根据每个图像补丁本身情况自适应地确定,从而克服了人为选择参数且所有补丁参数需一致的缺点,因此使图像重建效果得到提升.实验结果表明,我们所提方法在不同尺寸扩大因子和噪声环境下都优于人工确定参数的情形,三种评价指标均表明所提方法是有效的.     

An adaptive quadrature-based factorization method for inverse acoustic scattering problems

We propose a novel adaptive algorithm, which generates nonuniform sampling points that automatically concentrate near the boundary of an unknown scatterer, to dramatically speed up Kirsch’s factorization method for inverse acoustic scattering problems. Built upon the widely used adaptive Simpson quadrature method, our proposed adaptive algorithm approximates the integral of an indicator function over the search domain and yields reliable and accurate reconstructions significantly faster than the standard factorization method. Numerical experiments are performed to validate the effectiveness of our proposed algorithm and make comparisons with the established multilevel linear sampling method.