基于线性回归的建模方法——最小量化法

应用线性回归进行预测时,最困难的问题是如何建立一个符合实际的回归模型。该文叙述了此方法的基本思想,以及最小量化法处理准则;在总结回归模型的建模方法基础上,论述了最小量化法建模方法;以某案例实证了本文方法。

有害废物管理最小量化和处理处置技术

一、前言有害废物管理问题已成为当今世界的重大环境问题之一,随着经济的发展,这个问题日趋严重。目前发达国家的做法是首先进行废物最小量化,即源减少,再循环,再利用,使产生的有害废物量达到最小程度;然后将经最小量化后产生的有害废物进行无害化处理和最终处置。这些管理技术对我国刚起步的有害废物管理有十分有益的借签作用。二、废物最小量化1.定义废物最小量化意味着对产生或要被处理、贮存或处置的有害废物减少到最低程度。废物最小量化的关键是源减少和再循环,这将减少产生的有害废物的体积和毒性。2.废物最小量化方法废物最小量化在大多数的工业生产中可分为几个步骤,需要仔细规划。

优化OBDD性能的变量量化调度算法研究

在目前VLSI设计流程中,采用模型检测技术来实现形式化验证对可靠的硬件设计具有重要的意义。在以有序二值决策图(OBDD)为基础的符号综合和验证过程中,需要对有限状态机各传输关系合取运算的先后顺序进行量化调度,从而降低求解过程中各临时OBDD所消耗的内存资源,也就降低了对某些验证的状态空间爆炸的风险。调度策略通过对各传输关系与量化变量构成的关联矩阵的分析,以不断降低变量的平均生存量化跨度为目标,提出了能减少变量参与合取运算次数的MSTA(Minimum Subsist-ence Traversal Algorithm)过程、关联矩阵的连接子图分解策略和考虑关联矩阵中前后行关联程度的串接过程。实验表明了此合取量化调度过程的有效性和鲁棒性。

城市垃圾污染防治对策探讨

从城市垃圾产生的机制入手,分析了城市垃圾污染产生的原因,并对目前所采取的主要处理方法作了简要评述。在此基础上提出了实现城市垃圾最小量化,推动垃圾资源化产业,提高垃圾无害化处理水平,强化监督管理等几点城市垃圾污染防治的对策。

基于不平衡样本的CF- SOM- MQE感应电机状态分析

为提高感应电机状态评估的精度,本研究提出了一种基于相关性算法(CF)和自组织映射最小量化误差(SOM-MQE)的模型来解决基波电流信号干扰和缺少故障数据的问题.首先简要介绍自相关算法与互相关算法理论,分析了定子电流中的特征谐波分量,将其作为性能退化指标输入SOM神经网络中,在此基础上计算其最小量化误差(MQE)值的大小,并将MQE作为感应电机状态监测的衡量指标.实例表明,所提模型能够准确地对感应电机健康状态进行估计,具有较强的工程应用价值及通用性.

一种新型深度自编码网络的滚动轴承健康评估方法

为了准确描述滚动轴承性能退化的动态过程,结合深度学习强大特征提取能力的优势,提出了一种新型深度自编码和最小量化误差方法相结合的滚动轴承全寿命健康评估方法.用深度自编码模型对原始特征进行压缩提取,将压缩特征按趋势进行排序,选取趋势大的特征运用最小量化误差方法构建健康指标.针对基于一个度量的评价准则常具有偏差的问题,提出基于遗传算法的融合评价准则. 2组实例分析结果表明,用该方法构建的健康指标的趋势值、单调性值、鲁棒性值、融合评价准则值都大于单层的自编码模型(AE)和传统的PCA降维方法,第1个实例中,该方法构建的健康指标融合评价准则值比PCA,AE方法分别增加了13. 30%,3. 17%;第2个实例中,该方法构建的健康指标融合评价准则值比PCA,AE方法分别增加了9. 68%,3. 85%.基于遗传算法的融合评价准则比单一的评价准则更具有说服力.

基于相位间隔DDS合成信号噪声分析

文章就直接数字频率合成器(以下简称DDS)合成技术产生正弦波信号的噪声进行分析,以合成信号可能产生的最大量化噪声功率为基础,定义最小量化信噪比;并研究最小量化信噪比和正弦波单周期样点数、数模转换器分辨率的关系,为设计DDS合成信号发生器提供了理论依据。

SOM-MQE的钻井泥浆泵健康状态评估

为了对钻井泥浆泵的运行状态进行分析与评估,提出了一种基于SOM-MQE的钻井泥浆泵健康状态评估方法,并通过实测数据验证了算法的可行性。首先,采用加速度传感器采集泥浆泵的振动信号,应用相关性滤波算法对原始振动信号进行滤波降噪,提高信噪比。其次,对滤波后的数据提取时域、频域和时频域特征;再对这些特征PCA降维处理,得到反映泥浆泵状态的主成分特征矢量。最后,将主成分特征矢量作为SOM-MQE评估模型的输入,构建SOM-MQE评价模型,并计算最小量化误差(MQE)值大小,利用钻井泥浆泵偏离其在无故障状态下的MQE值对其健康状态进行评估。现场试验结果表明,MQE值表征的运行状态与钻井泥浆泵实际运行状态相对应,准确率高达96.28%,MQE值可以用来评价钻井泥浆泵的健康状态。

基于核自适应滤波的无线传感网络定位算法研究

针对动态室内环境的变化及时变的接收信号强度(Received signal strength,RSS)对定位精度的影响,提出了一类基于核自适应滤波算法的农业无线传感器网络室内定位方法。核自适应滤波算法具体包括量化核最小均方(Quantized kernel least mean square,QKLMS)算法及固定预算(Fixed-budget,FB)核递推最小二乘(Kernel recursive least-squares,KRLS)算法。QKLMS算法基于一种简单在线矢量量化方法替代稀疏化,抑制核自适应滤波中径向基函数结构的增长。FB-KRLS算法是一种固定内存预算的在线学习方法,与以往的"滑窗"技术不同,每次时间更新时并不"修剪"最旧的数据,而是旨在"修剪"最无用的数据,从而抑制核矩阵的不断增长。通过构建RSS指纹信息与物理位置之间的非线性映射关系,核自适应滤波算法实现WSN的室内定位,将所提出的算法应用于仿真与物理环境下的不同实例中,在同等条件下,还与其他核学习算法、极限学习机(Extreme learning machine,ELM)等定位算法进行比较。仿真实验中2种算法在3种情形下的平均定位误差分别为0.746、0.443 m,物理实验中2种算法在2种情形下的平均定位误差分别为0.547、0.282 m。实验结果表明,所提出的核自适应滤波算法均能提高定位精度,其在线学习能力使得所提出的定位算法能自适应环境动态的变化。

NOVEL WEIGHTED LEAST SQUARES SUPPORT VECTOR REGRESSION FOR THRUST ESTIMATION ON PERFORMANCE DETERIORATION OF AERO-ENGINE

A thrust estimator with high precision and excellent real-time performance is needed to mitigate perfor- mance deterioration for future aero-engines. A weight least squares support vector regression is proposed using a novel weighting strategy. Then a thrust estimator based on the proposed regression is designed for the perfor- mance deterioration. Compared with the existing weighting strategy, the novel one not only satisfies the require- ment of precision but also enhances the real-time performance. Finally, numerical experiments demonstrate the effectiveness and feasibility of the proposed weighted least squares support vector regression for thrust estimator. Key words ： intelligent engine control; least squares ; support vector machine ; performance deterioration

清洁生产——改善劳动条件的必由之路

就清洁生产的概念、内容、实施途径和方法以及它已带来的成效等进行了分析，论证清洁生产是改善劳动条件的必由之路。

Crystal Growth,Structure and Morphology of Rifapentine Methanol Solvate

Rifapentine, an important antibiotic, was crystallized from methanol solvent in the form of its methanol solvate. The crystal structure of rifapentine methanol solvate belongs to monoclinic, space group P21, with the unit cell parameters of a = 1.2278（3） nm, b = 1.9768（4） rim, c = 1.2473（3） nm, Z= 2, and β = 112.35（3）. The parallelepiped.morphology was also predicted by Materials Studio simulation program.. The influence of intermolecular in-teraction was taken into account in the attachment energy model. The crystal shape fits the calculated morphology well, which was performed on the potential energy minimized model using a generic DREIDING 2.21 force fieldand developed minimization protocol with derived＇partial charges.

A new extension algorithm for cubic B-splines based on minimal strain energy

Extension of a B-spline curve or surface is a useful function in a CAD system. This paper presents an algorithm for extending cubic B-spline curves or surfaces to one or more target points. To keep the extension curve segment GC^2-continuous with the original one, a family of cubic polynomial interpolation curves can be constructed. One curve is chosen as the solution from a sub-class of such a family by setting one GC^2 parameter to be zero and determining the second GC^2 parameter by minimizing the strain energy. To simplify the final curve representation, the extension segment is reparameterized to achieve C-continuity with the given B-spline curve, and then knot removal from the curve is done. As a result, a sub-optimized solution subject to the given constraints and criteria is obtained. Additionally, new control points of the extension B-spline segment can be determined by solving lower triangular linear equations. Some computing examples for comparing our method and other methods are given.

Efficient multiuser detector based on box-constrained dichotomous coordinate descent and regularization

The presented iterative multiuser detection technique was based on joint deregularized and box-constrained solution to quadratic optimization with iterations similar to that used in the nonstationary Tikhonov iterated algorithm.The deregularization maximized the energy of the solution,which was opposite to the Tikhonov regularization where the energy was minimized.However,combined with box-constraints,the deregularization forced the solution to be close to the binary set.It further exploited the box-constrained dichotomous coordinate descent algorithm and adapted it to the nonstationary iterative Tikhonov regularization to present an efficient detector.As a result,the worst-case and average complexity are reduced down as K2.8 and K2.5 floating point operation per second,respectively.The development improves the "efficient frontier" in multiuser detection,which is illustrated by simulation results.In addition,most operations in the detector are additions and bit-shifts.This makes the proposed technique attractive for fixed-point hardware implementation.

Extreme value distributions of mixing two sequences with different MDA＇s

Suppose {Xi, i≥1} and {Yi, i≥1} are two independent sequences with distribution functions FX(x) and FY(x), respectively. Zi is the combination of Xi and Yi with a probability pn for each i with 1≤i≤n. The extreme value distribution ,n GZ(x) of this particular triangular array of the i.i.d. random variables Z1, , Z2, ,…, Zn n n ,nis discussed. We found a new form of the extreme value distribution ΛA(ρx)Λ(x)(0<ρ <1), which is not max-stable. It occurs if FX(x) and FY(x) belong to the same MDA(Λ). GZ(x) does not exist as mixture forms of the different types of extreme value distributions.

Optimal Structural Design of the Midship of a VLCC Based on the Strategy Integrating SVM and GA

In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier （VLCC） ship was carried out according to the direct strength assessment method in common structural rules （CSR）, which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.

A Discrete Artificial Bee Colony Algorithm for Minimizing the Total Flow Time in the Blocking Flow Shop Scheduling

A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.

Characteristics of non-magnetic nanoparticles in magnetically fluidized bed by adding coarse magnets

The fluidization behavior of SiO2, ZnO and TiO2 non-magnetic nanoparticles was investigated in a magnetically fluidized bed （MFB） by adding coarse magnets. The effects of both the amount of coarse magnets and the magnetic field intensity on the fluidization quality of these nanoparticles were investigated. The results show that the coarse magnets added to the bed lead to a reduction in the size of the aggregates formed naturally by the primary nanopartieles. As the macroscopic performances of improved fluidization quality, the bed expansion ratio increases whilst the minimum fluidization velocity decreases with increasing the magnetic field intensity, but for TiO2 nanoparticles there exists a suitable magnetic field intensity of 0.059 6 T. The optimal amounts of coarse magnets for SiO2, ZnO and TiO2 non-magnetic nanoparticles are 40%, 50% and 60% （mass fraction）, respectively. The bed expansion results analyzed by the Richardson-Zaki scaling law show that the exponents depend on both the amount of coarse magnets and the magnetic field intensity.

Nonlinear least square estimation using difference quotient instead of derivative containing different classes of measurements

Using difference quotient instead of derivative, the paper presents the solution method and procedure of the nonlinear least square estimation containing different classes of measurements. In the meantime, the paper shows several practical cases, which indicate the method is very valid and reliable.