基于消费者语义感性信息的新产品方案评价研究

针对新产品设计方案评价问题,给出了一种面向消费者特殊需求偏好的感性评价方法.在该方法中,首先通过语义差分法和语义变量设计问卷获得待估新产品方案的感性信息数据以及在消费者不同偏好关系下的感性目标可能性分布;然后在此基础上,提出了以消费者感性需求为导向的评价函数,并运用混合加权平均算子对各方案评价信息集结计算;最后,依据评价函数值大小对各方案进行排序.尤其针对消费者特殊需求给定时,该模型评价函数可以计算出新产品与消费者特殊偏好的匹配程度.实例计算表明,本研究给出的方法具有可行性和实用性.     

应用于贴片机贴装顺序优化的遗传算法的比较和改进

元件贴装顺序优化是决定贴片机生产效率的关键问题,传统的解决贴装顺序优化问题的方法有遗传算法,蚁群算法,SS(伞布搜索法)等。使用较多的还是遗传算法。遗传算法中包含选择算子、交叉算子、变异算子,且编程思想简单,但容易出现局部最优,过早收敛等情况。在此,通过对遗传算法在贴装顺序优化应用的结果比较找到一种更适合的遗传算法,使之拥有较快的收敛速度和全局优化性。     

基于SUSAN算子的嘴部轮廓特征提取方法

针对人脸识别中的嘴部定位部分轮廓缺失问题,提出了一种由粗到精的快速准确的嘴部轮廓特征提取方法。该方法是在人脸检测的基础上采用改进的SUSAN算子提取嘴部边缘轮廓信息,通过几何特征和搜索区域相结合的方法实现了嘴唇轮廓的精确定位。仿真结果表明,该定位方法快速有效,正确率较高。     

基于特征融合的粒子滤波目标跟踪新方法

针对传统粒子滤波(PF)算法采用单一颜色特征建模 跟踪目标性能差的缺陷,提出一种颜色特征与纹理特 征相融合的PF目标跟踪新算法。首先,采用一种具有抗噪声和保护纹理边缘的全局中值二值 模式 (GMBP)纹理算子,对模板图像进行局部差绝对值处理,得到幅 值序列模板,将幅值序列模板内的中值作为模板的阈值,与模板邻域比较获得新的纹理图像 ;然后,与 具有光照不变特性的局部二值模式(LBP)纹理算子结合,形成一种(GMLBP)新的纹理描述算子 。最后,分别计算GMLBP纹理特征粒子权值和HSV颜色特征粒子权 值,并依据权值大小确定融合系数,对纹理特征粒子权值和颜色特征粒子权值进行线 性融合,再对融合后粒子权值进行归一化处理,从而得到目标位置状态的最终估计值。对比 实验结果表明, 相对于单一颜色特征的目标跟踪算法,所提算法捕捉目标位置准确且具有更低的平均跟踪误 差,其平均误差降低了近2倍。     

Hybrid adaptive evolutionary algorithm based on decomposition

The performance of search operators varies across the different stages of the search/optimization process of evolutionary algorithms (EAs). In general, a single search operator may not do well in all these stages when dealing with different optimization and search problems. To mitigate this, adaptive search operator schemes have been introduced. The idea is that when a search operator hits a difficult patch (under-performs) in the search space, the EA scheme “reacts” to that by potentially calling upon a different search operator. Hence, several multiple-search operator schemes have been proposed and employed within EA. In this paper, a hybrid adaptive evolutionary algorithm based on decomposition (HAEA/D) that employs four different crossover operators is suggested. Its performance has been evaluated on the well-known IEEE CEC’09 test instances. HAEA/D has generated promising results which compare well against several well-known algorithms including MOEA/D, on a number of metrics such as the inverted generational distance (IGD), the hyper-volume, the Gamma and Delta functions. These results are included and discussed in this paper.     

A fuzzy hierarchical operator in the grey wolf optimizer algorithm

The main goal of this paper is to study the performance of the Grey Wolf Optimizer (GWO) algorithm when a new hierarchical operator is introduced in the algorithm. This new operator is basically a hierarchical transformation that is inspired in the hierarchical social pyramid of the grey wolf. This proposed operator is applied to the simulation of the hunting process in the algorithm and has 5 variants that are explained in more detail in this paper (centroid, weighted, based on the fitness and two variants using fuzzy logic). Notably the variants having the greatest impact in the GWO performance are based on the use of fuzzy logic. We also present the motivation and results of experiments, as well as the benchmark functions that were used for the tests that are presented. In addition we are presenting a comparison among all methods for 30, 64 and 128 dimensions and we conclude that the performance of the Hierarchical GWO algorithm is better when using a fuzzy variant of the hierarchical operator.     

Adaptive and optimal difference operators in image processing

Differential operators are essential in many image processing applications. Previous work has shown how to compute derivatives more accurately by examining the image locally, and by applying a difference operator which is optimal for each pixel neighborhood. The proposed technique avoids the explicit computation of fitting functions, and replaces the function fitting process by a function classification process using a filter bank of feature detection templates. Both the feature detectors and the optimal difference operators have a specific shape and an associated cost, defined by a rigid mathematical structure, which can be described by Gröbner bases. This paper introduces a cost criterion to select the operator of the best approximating function class and the most appropriate template size so that the difference operator can be locally adapted to the digitized function. We describe how to obtain discrete approximates for commonly used differential operators, and illustrate how image processing applications can benefit from the adaptive selection procedure for the operators by means of two example applications: tangent computation for digitized object boundaries and the Laplacian of Gaussian edge detector.     

A note to the integrable discretization of the mKdV and Schrödinger equations

An approach has been proposed to the integrable discretization of nonlinear evolution equations. Based on the bilinear formalism, we choose appropriate substitution from hyperbolic operator into continuous Hirota operators and obtain several new kinds of integrable system through seeking their 3-soliton solutions, such as the mKdV equation, the nonlinear Schrödinger equation and so on. By applying Adomian decompose method, we discuss the numerical analysis property to the discrete mKdV equation. In addition, we also point out the relations between the above discreted equations and some well-known equations.     

Next-generation tools for evolutionary invasion analyses

Evolutionary invasion analysis is a powerful technique for modelling in evolutionary biology. The general approach is to derive an expression for the growth rate of a mutant allele encoding some novel phenotype, and then to use this expression to predict long-term evolutionary outcomes. Mathematically, such ‘invasion fitness’ expressions are most often derived using standard linear stability analyses from dynamical systems theory. Interestingly, there is a mathematically equivalent approach to such stability analyses that is often employed in mathematical epidemiology, and that is based on so-called ‘next-generation’ matrices. Although this next-generation matrix approach has sometimes also been used in evolutionary invasion analyses, it is not yet common in this area despite the fact that it can sometimes greatly simplify calculations. The aim of this article is to bring the approach to a wider evolutionary audience in two ways. First, we review the next-generation matrix approach and provide a novel, and easily intuited, interpretation of how this approach relates to more standard techniques. Second, we illustrate next-generation methods in evolutionary invasion analysis through a series of informative examples. Although focusing primarily on evolutionary invasion analysis, we provide several insights that apply to biological modelling in general.     

伯努利卷积下正交基的推广

考虑了伯努利卷积下λ=p/（2n）的情形,应用转移算子证明了对于某些正整数k0,E（pk0Γ）是L2（pμ/（2n））的正交基,那么对于任意的正整数k,E（pkΓ）也是正交基.