熵在大件物流运作指标量化研究中的应用

在分析了大件物流运作特点,归纳大件物流技术评价关键指标因素的基础上,将熵的评价方法运用到大件物流技术评定中来。将大件物流技术指标量化处理,建立了基于熵的大件物流运作模型。通过对模型的分析处理,可用来评定大件物流整体运营效益,评定大件物流技术发展水平,找到制约大件物流发展的技术短板,对大件物流技术的发展具有现实的指导意义。

多特征加权指数熵在光斑中心定位中的应用

激光光斑中心检测是视觉测量中常用的关键技术,检测算法的优劣直接影响了测量的精度。针对现有光斑定位算法存在定位精度低、抗干扰能力差等问题,提出一种改进的激光光斑中心定位算法。该算法在Shannon熵的基础上引入指数熵,并根据光斑图像特征选取类内离散度最小和灰度对比度最大对指数熵进行加权处理,将使加权指数熵值最大时的灰度值作为阈值对光斑图像进行阈值分割,由此消除噪声干扰,最后由质心法进行光斑中心定位。实验表明,在兼顾稳定性的同时,与传统阈值分割方法相比,光斑中心定位误差降低了22%以上。

关于大学物理中熵的教学探讨与思考

熵是热学中的一个重要物理概念,也是近年来人们特别感兴趣的一个概念,它已经远远超出物理学的范畴,在自然和社会科学的许多领域中得到广泛应用。本文从教材内容、教学过程与方法等方面分析了熵的教学现状及存在的不足,并结合我们的教学实践,就如何进行熵的教学进行了一些探讨。

信息检索系统运行的熵流模式

根据耗散结构热力学理论的分析指出,信息检索系统的运行是向系统输入的熵流对系统状态函数即服务参数作用的非线性过程,其中,负熵流的作用有一个周期.这个非线性过程尚不能表达成数学关系式,而是用图解定性描述了系统运行的模式,案例中3家文献检索系统作了验证.

熵的物理化学意义

高中化学新课标选修4中引入了熵的概念并利用熵判据判断化学反应过程的方向，化学中的熵又如何理解呢？本文介绍了熵的起源与发展，并叭物理化学角度介绍熵的概念和熵增原理，包括波尔兹曼熵和克劳修斯熵，并由波尔兹曼熵推出克劳修斯熵、从物理化学的角度考察了熵，为中学教学提供参考。

运输枢纽与物流活动的相容性研究

运输枢纽与物流业在发展过程中既有密切的关联,又存在一定的不协调性。运用数量分析的方法,对运输枢纽与物流活动的相容性进行评价分析,以寻求一种合理且实用的方法对两者间在发展过程中的相容与不容进行客观地评价和判断。

信息服务系统运作的热力学研究

信息服务系统是由馆藏资源、基础设施、业务与服务、人员（职工和用户）和管理等5部分组成的开放的人工系统，在一定的假设条件下，可以看成是具有耗散结构特征的热力学系统，按照普里戈津（I．Prigogine）创立的耗散结构热力学理论，分析阐述了它的运作，并结合案例进行了讨论。指出，整合、共建共享信息资源、提高员工素质、改善基础设施、改进服务和方便用户等是向系统输入负熵流，促使系统呈“螺旋式上升进程”模式向结构优化和运作有序的方向发展。

熵的物理内涵及其应用

对熵和熵变进行一个较为系统的研究。详细阐述了熵的概念、克劳修斯熵公式、熵的微观本质、熵增加原理和熵的应用等，在熵的应用中重点论述了熵与能量、熵与环境保护以及熵与信息的关系。对熵概念的深刻理解将有助于加深对自然科学和社会科学的认识和了解。

An Improved Markov Chain Model Based on Autocorrelation and Entropy Techniques and Its Application to State Prediction of Water Resources

According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.

Fuzzy entropy design for non convex fuzzy set and application to mutual information

Fuzzy entropy was designed for non convex fuzzy membership function using well known Hamming distance measure.The proposed fuzzy entropy had the same structure as that of convex fuzzy membership case.Design procedure of fuzzy entropy was proposed by considering fuzzy membership through distance measure,and the obtained results contained more flexibility than the general fuzzy membership function.Furthermore,characteristic analyses for non convex function were also illustrated.Analyses on the mutual information were carried out through the proposed fuzzy entropy and similarity measure,which was also dual structure of fuzzy entropy.By the illustrative example,mutual information was discussed.

Multi-factors decision-making entropy method and its application in engineering management

In order to meet the strict requirements for information in engineering management, the positive interval （0, 1 ] in Shannon information entropy is extended to the real number interval [ - 1, 1 ]. The information theory and the decision theory are combined effectively, and the deficiencies that the traditional Bayes decision-making methods only consider a single factor are made up for. The multi-factors engineering decision-making methods are proposed, and some critical problems are solved in the practical engineering management decision-making process.

Optimization model of unascertained measurement for underground mining method selection and its application

An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.

The intrinsic depth of horizontal convection

The mainstream depth of a return flow can be viewed as an intrinsic depth of horizontal convection. By using a theoretical tube model combined with the application of the Maximum Entropy Production Principle (MaxEPP) in thermodynamics, the following statements can be made. Under fixed external forcing, the system chooses a particular depth as the mainstream depth of its return flow, the depth of which not only satisfies the maximum circulation rate and the maximum heat transport, but also satisfies the maximum entropy production rate. A comparison between this intrinsic depth and the container height leads to the definition of a relative partial and full-penetration pattern of the circulation. Moreover, this intrinsic depth is found to vary with the external forcing; the regulation of this variation is related to the Modified Rayleigh number.

Quantification of Blur and Its Applications

Human visual sense has two aspects in our feeling for blurred image, that is, one is the amount of blur depending on object size, the other is the amount of blur independent of the object size. In the former for example, when the image size becomes larger, the author feels smaller amount blur. The quantitative evaluation based on entropy for blurred images is proposed in this paper. The author calls this metric ＂variation entropy＂. This metric has two kinds of aspects that coincide with the human visual sense. The first is the absolute evaluation of blur, and the second is the relative evaluation of blur. The former can be quantified by variation entropy for a unit boundary length （or L-type variation entropy： HL ）, which is dependent on resolution, and the latter can be quantified by variation entropy for a unit area （or A-type variation entropy： H^A ）, which is independent of resolution. These two metrics have complementary properties. At last, two variation entropies are applied to the standard kanji character database, and then the strong relation between variation entropy and accuracy of recognition is discussed. The tendency of writing skills for grades is evaluated by applying the metric to a database collected from school children.

Investigation on Multi-objective Performance Optimization Algorithm Application of Fan Based on Response Surface Method and Entropy Method

A multi-objective performance optimization method is proposed, and the problem that single structural parame- ters of small fan balance the optimization between the static characteristics and the aerodynamic noise is solved. In this method, three structural parameters are selected as the optimization variables. Besides, the static pressure efficiency and the aerodynamic noise of the fan are regarded as the multi-objective performance. Furthermore, the response surface method and the entropy method are used to establish the optimization function between the op- timization variables and the multi-objective performances. Finally, the optimized model is found when the opti- mization function reaches its maximttm value. Experimental data shows that the optimized model not only en- hances the static characteristics of the fan but also obviously reduces the noise. The results of the study will provide some reference for the optimization of multi-objective performance of other types of rotating machinery.

Enhanced oxidation resistance of MoTaTiCrAl high entropy alloys by removal of Al

Refractory high-entropy alloys(HEAs) exhibit remarkable mechanical properties desired for high-temperature applications. However, their oxidation resistance at high temperatures received less attention. Recent work indicates that MoTaTiCrAl alloy exhibits excellent oxidation resistance,but the effects of Al and Cr remain unclear. In this work, we demonstrate that the addition of Al is unnecessary for preventing oxidation of the MoTaTiCrAl alloy and the removal of Al leads to a more oxidation resistant MoTaTiCr medium entropy alloy. Structural and chemical analyses indicate that the excellent oxidation resistance of MoTaTiCr is mainly associated with the formation of continuous CrTaO4 oxide layer.The results indicate that complex oxides can be adopted as effective candidates for enhancement of oxidation resistance,in addition to typical strategy of forming Al2O3, Cr2O3 or SiO2 barrier layer.

Sharp heat kernel bounds and entropy in metric measure spaces

We establish the sharp upper and lower bounds of Gaussian type for the heat kernel in the metric measure space satisfying the RCD(0, N)(equivalently, RCD~*(0, N), condition with N∈N\ {1} and having the maximum volume growth, and then show its application on the large-time asymptotics of the heat kernel, sharp bounds on the(minimal) Green function, and above all, the large-time asymptotics of the Perelman entropy and the Nash entropy, where for the former the monotonicity of the Perelman entropy is proved. The results generalize the corresponding ones in the Riemannian manifolds, and some of them appear more explicit and sharper than the ones in metric measure spaces obtained recently by Jiang et al.(2016).

Simultaneously enhanced oxidation resistance and mechanical properties in a novel lightweight Ti_(2)VZrNb_(0.5)-Al_(0.5)high-entropy alloy

Enhanced oxidation resistance is a primary demand for the application of refractory high-entropy alloys(RHEAs)at elevated temperatures.In this study,Al was added to a Ti_(2)VZrNb RHEA to partially substitute Nb to improve its oxidation resistance and mechanical properties.The alloy was found to have an increased oxidation resistance by forming a continuous Al_(2)O_(3)+ZrO_(2)oxide protective surface.At the same time,the room-temperature yield strength was also increased by 66%to 1273 MPa via solid solution strengthening.The low atomic mass of Al also helped to reduce the density of the alloy by 8.2%to 5.44 g cm^(−3).This resulted in a high specific yield strength of 234 MPa cm3 g^(−1) for the alloy.Meanwhile,the Ti_(2)VZrNb_(0.5)-Al_(0.5)alloy also exhibited a high compressive plasticity of>50%.These values are among the best reported so far for RHEAs.

Information theory in nonlinear error growth dynamics and its application to predictability:Taking the Lorenz system as an example

In nonlinear error growth dynamics,the initial error cannot be accurately determined,and the forecast error,which is also uncertain,can be considered to be a random variable.Entropy in information theory is a natural measure of the uncertainty of a random variable associated with a probability distribution.This paper effectively combines statistical information theory and nonlinear error growth dynamics,and introduces some fundamental concepts of entropy in information theory for nonlinear error growth dynamics.Entropy based on nonlinear error can be divided into time entropy and space entropy,which are used to estimate the predictabilities of the whole dynamical system and each of its variables.This is not only applicable for investigating the dependence between any two variables of a multivariable system,but also for measuring the influence of each variable on the predictability of the whole system.Taking the Lorenz system as an example,the entropy of nonlinear error is applied to estimate predictability.The time and space entropies are used to investigate the spatial distribution of predictability of the whole Lorenz system.The results show that when moving around two chaotic attractors or near the edge of system space,a Lorenz system with lower sensitivity to the initial field behaves with higher predictability and a longer predictability limit.The example analysis of predictability of the Lorenz system demonstrates that the predictability estimated by the entropy of nonlinear error is feasible and effective,especially for estimation of predictability of the whole system.This provides a theoretical foundation for further work in estimating real atmospheric multivariable joint predictability.