双特征参数基因识别算法实现

基因识别问题首要的工作是对数字化后的基因序列利用离散傅里叶变换(DFT)进行频谱分析.对于很长的DNA序列,功率谱或信噪比计算量很大,推导出了DNA序列在Voss映射、Z-curve映射和实数映射下的信噪比快速算法,以及在Voss映射与Z-curve映射下的信噪比的关系.针对阈值确定的问题提出了基于滑动窗口的局部阈值的算法,在分类时达到了很好的效果.另外,实现了基于移动序列信噪比曲线的基因识别方法.最后,由于DNA序列的3-周期性实际上反映了核苷酸在基因序列的三个子序列上分布的"非均衡性",因此引入"方差均值"特征来衡量该非均衡性,提出了基于方差均值的单因素基因识别方法及以信噪比和方差均值作为特征向量,并设计多项式分类器的基因识别算法.     

动态特性的参数设计在差示光度法测金中的应用

本文提出对动态特性参数设计使用相关系数与信噪比作为内表指标进行分析 ,并使用该分析方法优化了差示光度法测较高浓度金矿样的试验条件。     

关于参数设计的一个注记

本文提出了参数设计中方差估计的一种新方法 -非参数估计方法 ,用以代替田口的信噪比中的方差估计。实例表明 ,该方法不但可以对因子进行分类 ,而且可以进行模型拟合的检查     

基于参数设计的信噪比交叉效率评价方法

针对DEA交叉效率评价过程中没有考虑自评与互评效率的作用而主观赋予相同权重导致交叉效率评价值不准确的问题.文章基于参数设计的思想,依据试验设计中可控与不可控因素的作用机理区分自评权重和互评权重对所评价决策单元交叉效率的影响与作用,将其界定为可控与不可控因素的管理学属性,明确不同权重作用机理;引入信噪比作为衡量决策单元交叉效率评价时的性能指标,实施DEA交叉效率评价方法的改进,设计出DEA信噪比交叉效率集结方法,从而实现交叉效率的集结方式由单一考虑交叉效率波动的均值转化为综合考虑交叉效率波动情况(均值与方差),交叉效率评价值用信噪比交叉效率替代交叉效率平均值更具有统计学意义并可从管理学角度解释,评价结果也具有更高的可区分性;最后通过算例分析验证了交叉效率评价理论上的必要性和该方法的合理性与可行性,同时发现了交叉效率评价中存在CCR有效DMU序位超出了有效DMU范围现象,建议应实施同质DMU检验和评价值归一化.文章的研究也为提高DEA交叉效率测算的准确性提供一种新思路.     

基于周期混合信号和时滞项的非对称双稳系统的随机共振

研究了具有周期混合信号的带时滞项和non-Gaussian噪声项的非对称双稳系统的随机共振.首先应用统一色噪声理论近似了non-Gaussian噪声项,然后用小时滞近似理论简化了时滞项,进而根据两态理论得到了系统的输出信噪比的表达式.并讨论了系统的非对称性r,时滞量τ和噪声相关时间τ_0对信噪比的影响,发现信噪比曲线上出现了随机多振现象,这种现象与不考虑时滞影响时系统中的随机共振现象是不同的.且数值模拟表明,系统的非对称性r,时滞量τ和周期混合信号的影响使得信噪比曲线上出现了多个峰值.     

信号与同频色噪声驱动的双稳系统的随机共振实验研究

设计了将线性滤波器与随机共振装置串联处理信号、噪声的装置。这一装置模拟了在周期信号与单色同频噪声作用下的随机共振系统。实验表明,这一设计十分有利于在强噪声弱信号输入下提高输出信噪比,是将弱信号从强噪声背景下分离出来的新的强有力的工具。对上述非线性系统产生随机共振的物理机制也进行了定性的说明。     

参数设计思想与方法的研究

田口玄一的参数设计引起质量工作人员和统计学家的兴趣。也引起很多争论，近十年来人们对此作了大量的研究。这些研究涉及参数设计的各个方面。本文试图把田口的参数设计作一简要概括后，把这些争论与研究分几个小题目进行综述，这些小题目是：关于减少试验次数的讨论；关于交互作用的讨论；关于信噪比的讨论；为参数设计建模的研究。在最后结束语中列出田口在参数设计方面的主要贡献。     

关于综合噪声因子的注释

本文就特性值服从正态分布N（μ,σ~2）,使用综合噪声因子进行参数设计的场合,给出了μ~2与σ~2的无偏估计,并指出提高σ~2估计精度的可能性,随机模拟结果表明,此时信噪比η的估计也会更接近于真值。     

零件的参数设计

本文对零件的参数设计问题进行了分析,提出了质量特性的全微分形式,从而根据零件参数的分布函数求得质量特性的分布函数,并求出了总质量损失,这种方法也适用于质量损失函数为不连续分段函数形式的情况.本文对零件参数的设计方法做了进一步探讨,本模型为望目特性的参数设计,对于模型的求解首先进行改善信噪比的设计,然后进行目标值的修正,最后进行容差设计,使总费用达到最小。对题中的分离器参数进行的再设计,使总费用从原设计的3,085,700元降低到468,800元.所用方法基于数理统计理论,得到的结果合理.本文还讨论了模型的优缺点,并给出了一般的零件参数设计方法。     

二阶过程的最大信噪比滤波

<正> 最大信噪比滤波是工程技术中经常采用的一种滤波方法.谢衷洁、程乾生讨论了这种滤波方法.但考虑的过程都是协方差平稳的随机过程,所用的方法也是宽平稳过程中的 Hilbert 空间方法.本文将对最一般的二阶过程(包括场与多维过程,离散参数与连续参数)在一定的信噪比准则下来讨论最大信噪比滤波存在条件与其一般形式.     

多变量、多约束连续或离散的非线性规划的一个通用算法

利用目标函数对约束函数关于设计变量的一阶微分或差分之比,给出了一个求解非线性规划的通用算法．不论变量和约束有多少,也不论变量是连续的还是离散的,这一算法都比较有效,尤其对离散非线性规划更有效．该方法是一种搜索法,勿需解任何数学方程,只需要计算函数值以及函数对变量的偏微分或差分值．许多数值例题和运筹学中一些经典问题,如1) 一、二维的背包问题;2) 一、二维资源分配问题;3) 复合系统工作可靠性问题;4) 机器负荷问题等,经用此法求解验证均较传统方法更有效和可靠．该方法的主要优点是:1) 不受问题的规模限制;2) 只要在可行域（集）内存在目标函数和约束函数及其一阶导数或差分的值,肯定可以搜索到最优的解,没有不收敛和不稳定的问题．     

Quantile-based robust optimization of a supersonic nozzle for organic rankine cycle turbines

Organic Rankine Cycle (ORC) turbines usually operate in thermodynamic regions characterized by high-pressure ratios and strong non-ideal gas effects, complicating the aerodynamic design significantly. Systematic optimization methods accounting for multiple uncertainties due to variable operating conditions, referred to as Robust Optimization may benefit to ORC turbines aerodynamic design. This study presents an original and fast robust shape optimization approach to overcome the limitation of a deterministic optimization that neglects operating conditions variability, applied to a well-known supersonic turbine nozzle for ORC applications. The flow around the blade is assumed inviscid and adiabatic and it is reconstructed using the open-source SU2 code. The non-ideal gasdynamics is modeled through the Peng-Robinson-Stryjek-Vera equation of state. We propose here a mono-objective formulation which consists in minimizing the α-quantile of the targeted Quantity of Interest (QoI) under a probabilistic constraint, at a low computational cost. This problem is solved by using an efficient robust optimization approach, coupling a state-of-the-art quantile estimation and a classical Bayesian optimization method. First, the advantages of a quantile-based formulation are illustrated with respect to a conventional mean-based robust optimization. Secondly, we demonstrate the effectiveness of applying this robust optimization framework with a low-fidelity inviscid solver by comparing the resulting optimal design with the ones obtained with a deterministic optimization using a fully turbulent solver.     

An Efficient Algorithm for Rare-event Probability Estimation,Combinatorial Optimization,and Counting

Although importance sampling is an established and effective sampling and estimation technique, it becomes unstable and unreliable for high-dimensional problems. The main reason is that the likelihood ratio in the importance sampling estimator degenerates when the dimension of the problem becomes large. Various remedies to this problem have been suggested, including heuristics such as resampling. Even so, the consensus is that for large-dimensional problems, likelihood ratios (and hence importance sampling) should be avoided. In this paper we introduce a new adaptive simulation approach that does away with likelihood ratios, while retaining the multi-level approach of the cross-entropy method. Like the latter, the method can be used for rare-event probability estimation, optimization, and counting. Moreover, the method allows one to sample exactly from the target distribution rather than asymptotically as in Markov chain Monte Carlo. Numerical examples demonstrate the effectiveness of the method for a variety of applications.      

Anti-control of continuous-time dynamical systems

Based on two basic characteristics of continuous-time autonomous chaotic systems, namely being globally bounded while having a positive Lyapunov exponent, this paper develops a universal and practical anti-control approach to design a general continuous-time autonomous chaotic system via Lyapunov exponent placement. This self-unified approach is verified by mathematical analysis and validated by several typical systems designs with simulations. Compared to the common trial-and-error methods, this approach is semi-analytical with feasible guidelines for design and implementation. Finally, using the Shilnikov criteria, it is proved that the new approach yields a heteroclinic orbit in a three-dimensional autonomous system, therefore the resulting system is indeed chaotic in the sense of Shilnikov.     

CFD modeling and multi-objective optimization of cyclone geometry using desirability function,artificial neural networks and genetic algorithms

The low-mass loading gas cyclone separator has two performance parameters, the pressure drop and the collection efficiency (cut-off diameter). In this paper, a multi-objective optimization study of a gas cyclone separator has been performed using the response surface methodology (RSM) and CFD data. The effects of the inlet height, the inlet width, the vortex finder diameter and the cyclone total height on the cyclone performance have been investigated. The analysis of design of experiment shows a strong interaction between the inlet dimensions and the vortex finder diameter. No interaction between the cyclone height and the other three factors was observed. The desirability function approach has been used for the multi-objective optimization. A new set of geometrical ratios (design) has been obtained to achieve the best performance. A numerical comparison between the new design and the Stairmand design confirms the superior performance of the new design. As an alternative approach for applying RSM as a meta-model, two radial basis function neural networks (RBFNNs) have been used. Furthermore, the genetic algorithms technique has been used instead of the desirability function approach. A multi-objective optimization study using NSGA-II technique has been performed to obtain the Pareto front for the best performance cyclone separator.     

Application of fuzzy decision making to the fuzzy finite element method

In this paper we present a new approach to handle uncertainty in the Finite Element Method. As this technique is widely used to tackle real-life design problems, it is also very prone to parameter-uncertainty. It is hard to make a good decision regarding design optimization if no claim can be made with respect to the outcome of the simulation. We propose an approach that combines several techniques in order to offer a total order on the possible design choices, taking the inherent fuzziness into account. Additionally we propose a more efficient ordering procedure to build a total order on fuzzy numbers.     

The speed of adjustment of financial ratios: A hierarchical Bayesian approach using mixtures

This paper presents a hierarchical Bayesian analysis of the partial adjustment model of financial ratios using mixture models, an approach that allows us to estimate the distribution of the adjustment coefficients. More particularly, it enables us to analyse speed of reaction in the presence of shocks affecting financial ratios objectives as a basis to establish homogenous groups of firms. The proposed methodology is illustrated by examining a set of ratios for a sample of firms operating in the U.S. manufacturing sector. Copyright © 2007 John Wiley & Sons, Ltd.     

A novel approach for considering layout problem in cellular manufacturing systems with alternative processing routings and subcontracting approach

In this paper a new integrated approach is presented for designing cellular manufacturing system and its inter- and intra-cell layouts. Various production factors such as part demands, alternative processing routings, operation sequences, processing times, capacity of machines, etc. are incorporated in the problem in order to extend its applicability. To increase the accuracy of the inter- and intra-cell layout design, the material handling cost is calculated in terms of the actual position of machines within the cells and regarding the dimensions of the machines and aisle distances. Also, a subcontracting approach is proposed to determine the production volume of parts within the CF and layout design process regarding the production, material handling and outsourcing costs and under demand and machine capacity constraints. To the best of our knowledge, this is the first study that addresses all these design features simultaneously. As the proposed problem is NP-hard, an efficient GA is employed to solve it. Finally, numerical examples adopted from the literature are used to verify the proposed approach.     

A generic design methodology for sliding mode control of switched systems

The aim of this paper is to present a generic methodology to design sliding mode controllers for multivariable switched systems affine in control such as dc–dc power converters. An original formulation of the so-called reachability condition, suitable for this class of systems, is established. Based on the choice of a Lyapunov-like function and parameterized by a single weighting matrix, it allows several kinds of control strategies to be derived, namely conventional piecewise continuous strategies as well as discrete (Boolean) strategies. Its application to the important subclass of linear time invariant systems is investigated more specifically. In the Boolean case, the present approach is also compared to another hybrid one called the stabilizing approach. Eventually, its efficiency as a design methodology, as well as the performance of the resulting control, are shown by simulating it on non-trivial examples of power converters.     

Robust dynamical compensator design for discrete-time linear periodic systems

This paper considers dynamical compensators design for purpose of pole assignment for discrete-time linear periodic systems. Similar to linear time-invariant systems, it is pointed out that the design of a periodic dynamical compensator can be converted into the design of a periodic output feedback controller for an augmented system. Utilizing the recent result on output feedback pole assignment, parametric solutions for this problem are obtained. The design approach can be used as a basis for the robust dynamical compensator design for this type of systems. Combined with a robustness index presented in this paper, robust dynamical compensator design problem is converted into a constrainted optimization problem. A numerical example is employed to illustrate the validity and feasibility of the methods.