中国工业环境规制强度的行业差异及收敛性研究

针对不同行业环境规制强度的差异性,本文运用收敛理论研究了行业环境规制强度的敛散性。传统上利用单位成本或产出的污染治理费用表示的行业环境规制强度可能存在有偏性,本文基于单位污染排放的污染治理费用测算行业环境规制强度,利用Theil指数和收敛检验模型,分析了2001—2015年中国35个工业行业环境规制强度差异、收敛性质及收敛机制。研究发现:(1)一些行业的环境规制强度与其污染强度未表现出相应的强关联性。(2)中国工业行业环境规制强度差异呈现"M"型变化趋势,污染行业与清洁行业之间的环境规制强度差异呈现先发散后收敛的倒"U"型趋势。(3)泰尔指数及其分解还表明,污染行业内部的子行业间环境规制强度差异很大,且是造成工业行业环境规制强度差异的最主要来源。(4)工业行业环境规制强度存在较长时段的σ收敛和较短时长的俱乐部收敛的同时,还存在绝对β收敛和条件β收敛,即低规制行业向高规制行业看齐,不同行业环境规制强度向各自的稳态水平靠近,此外,污染行业环境规制强度收敛速度慢于清洁行业。(5)企业规模成长和市场化水平提升有利于促进企业提高环境规制水平。(6)对收敛机制的进一步研究表明,出口学习效应和进口技术溢出对行业环境规制强度变化的提升效应随着环境规制强度的提高而扩大,即两者对行业环境规制强度变化具有提升效应,但无促进其收敛的作用。扩大企业规模、提升市场化和对外开放水平,有利于提升企业应对环境规制的能力,并为下一阶段实施更为合理有效的环境规制政策提供支撑。

Complete Convergenceand Complete Moment Convergence for Weighted Sums of ANA Random Variables

In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.

On the Local Convergence and Dynamics of New Iterative Method with Sixth Order Convergence

In this paper,we construct a new sixth order iterative method for solving nonlinear equations.The local convergence and order of convergence of the new iterative method is demonstrated.In order to check the validity of the new iterative method,we employ several chemical engineering applications and academic test problems.Numerical results show the good numerical performance of the new iterative method.Moreover,the dynamical study of the new method also supports the theoretical results.

An Adaptive Spectral Conjugate Gradient Method with Restart Strategy

As a generalization of the two-term conjugate gradient method(CGM),the spectral CGM is one of the effective methods for solving unconstrained optimization.In this paper,we enhance the JJSL conjugate parameter,initially proposed by Jiang et al.(Computational and Applied Mathematics,2021,40:174),through the utilization of a convex combination technique.And this improvement allows for an adaptive search direction by integrating a newly constructed spectral gradient-type restart strategy.Then,we develop a new spectral CGM by employing an inexact line search to determine the step size.With the application of the weak Wolfe line search,we establish the sufficient descent property of the proposed search direction.Moreover,under general assumptions,including the employment of the strong Wolfe line search for step size calculation,we demonstrate the global convergence of our new algorithm.Finally,the given unconstrained optimization test results show that the new algorithm is effective.

Adaptive genetic algorithm with the criterion of premature convergence

To counter the defect of traditional genetic algorithms, an improved adaptivegenetic algorithm with the criterion of premature convergence is provided. The occurrence ofpremature convergence is forecasted using colony entropy and colony variance. When prematureconvergence occurs, new individuals are generated in proper scale randomly based on superiorindividuals in the colony. We use these new individuals to replace some individuals in the oldcolony. The updated individuals account for 30 percent - 40 percent of all individuals and the sizeof scale is related to the distribution of the extreme value of the target function. Simulationtests show that there is much improvement in the speed of convergence and the probability of globalconvergence.

Numerical simulation of LWD resistivity response of carbonate formation using self-adaptive hp-FEM

Most of the carbonate formation are highly heterogeneous with cavities of different sizes, which makes the prediction of cavity-filled reservoir in carbonate rocks difficult. Large cavities in carbonate formations pose serious threat to drilling operations. Logging-whiledrilling （LWD） is currently used to accurately identify and evaluate cavities in reservoirs during drilling. In this study, we use the self-adaptive hp-FEM algorithm simulate and calculate the LWD resistivity responses of fracture-cavity reservoir cavities. Compared with the traditional h-FEM method, the self-adaptive hp-FEM algorithm has the characteristics of the self-adaptive mesh refinement and the calculations exponentially converge to highly accurate solutions. Using numerical simulations, we investigated the effect of the cavity size, distance between cavity and borehole, and transmitted frequency on the LWD resistivity response. Based on the results, a method for recognizing cavities is proposed. This research can provide the theoretical basis for the accurate identification and quantitative evaluation of various carbonate reservoirs with cavities encountered in practice.

CONSERVATIVE DIFFERENCE SCHEME BASED ON NUMERICAL ANALYSIS FOR NONLINEAR SCHRDINGER EQUATION WITH WAVE OPERATOR

A new conservative finite difference scheme is presented based on the numerical analysis for an initialboundary value problem of a class of Schroedinger equation with the wave operator. The scheme can be linear and implicit or explicit based on the parameter choice. The initial value after discretization has second-order accuracy that is consistent with the scheme accuracy. The existence and the uniqueness of the difference solution are proved. Based on the priori estimates and an inequality about norms, the stability and the convergence of difference solutions with the second-order are proved in the energy norm. Experimental results demonstrate the efficiency of the new scheme.

On Triangle Interpolation Approximation of the Double Function

本文以两组不同的节点构造了一个组合型的二元三角插值多项式算子Lmn(f;x,y)，并且研究了二元连续周期函数对这个算子的收敛性及收敛阶的估计等问题。

Empirical Bayes Estimation for the Parameter of Two-dimen sional One-side Truncated Distribution Families with Linex Loss

In this paper, we construct the EB estim ation for the parameter of the two-dimensional one side truncat ed distribution fam ilies using Linex loss. The convergence rate of EB estimation is given and it is shown that the proposed empirical Bayes estimaiton can be arbitrarily close to 1 under certain conditions.

EFFECTIVE METHOD OF PREVENTING PREMATURE OF GENETIC ALGORITHM

The genetic algorithm is a prol,able search method based on Darwin's natural selection and survival of the fittest, which is presented by John Holland. In theory the genetic algorithm can form a more complete algorithm by using bilogical evolution and genetic theory,but there are many I3roblemsneeded to be solved in practice,and premature,which is a serious problem,is one of them. In this paperwe analyze its causes from the hand of diversity of population,and give two theorems about it,and present an effective method of preventing the premature of genetic algorithm,which adopts the concepl ofdiversity of population and adaptive crossover and mutation rate. At last we make a simulation of four function by using the method as stated above,and the result of experiments shows that the Inethod isvery effective.

GLOBAL CONVERGENCE OF A CLASS OF OPTIMALLY CONDITIONED SSVM METHODS

This paper explores the convergence of a class of optimally conditioned self scaling variable metric (OCSSVM) methods for unconstrained optimization. We show that this class of methods with Wolfe line search are globally convergent for general convex functions.

Optimal state and branch sequence based parameter estimation of continuous hidden Markov model

A parameter estimation algorithm of the continuous hidden Markov model isintroduced and the rigorous proof of its convergence is also included. The algorithm uses theViterbi algorithm instead of K-means clustering used in the segmental K-means algorithm to determineoptimal state and branch sequences. Based on the optimal sequence, parameters are estimated withmaximum-likelihood as objective functions. Comparisons with the traditional Baum-Welch and segmentalK-means algorithms on various aspects, such as optimal objectives and fundamentals, are made. Allthree algorithms are applied to face recognition. Results indicate that the proposed algorithm canreduce training time with comparable recognition rate and it is least sensitive to the training set.So its average performance exceeds the other two.

Parallel EOI algorithm with different insertion schemes

A parallel embedding overlapped iterative (EOI) algorithm about classicimplicit equations with asymmetric Saul'yev schemes (CIS-EOI) to solve one-dimensional diffusionequations is discussed to improve the properties of the segment classic implicit iterative (SCII)algorithm. The structure of CIS-EOI method is given and the stability of scheme and convergence ofiteration are proved by matrix method. The property of gradual-approach convergence is alsodiscussed. It has been shown that the convergent rate is faster and the property of gradual-approachconvergence also becomes better with the increasing of the net point in subsystems than with theSCII algorithm. The simulation examples show that the parallel iterative algorithm with a differentinsertion scheme CIS-EOI is more effective.

A Class of Second-Order Characteristic Difference Schemes for a Model of Population Dynamics

In this paper, a three level characteristic difference scheme is proposed for the model of age structured population with history dependent mortality and natality. It is proved that the scheme is second order convergent in the discrete l ∞ norm.

Improvement of CORDIC Algorithm

Aim To discuss the basic CORDIC algorithm that can be applied to digital signal processing and its applying condition called convergence range.Methods In addition to the original basic equation, another group iterative equation was used to evaluate the correspondent values of input data that did not lie within the convergence range. Results and Conclusion The improved CORDIC algorithm removes the limits of the range of convergence and can adapt itself to the variations of input values. The correctness of improved CORDIC algorithms has been proved by calculating examples.

The Order of Approximation by(0,1,…,q) Hermite-Fejer Interpolation Polynomials at Nearly Fejer's Points

Suppose that the outer mapping function of domain D has its second continuous derivatives. In this paper, the order proximation by (0,1,…,q) Hermite-Fejer interpolating polynomials at nearly Fejer's points of function of class A(D) are presented. Moreover in general the order of approximation is sharp.

The σ-duals of Sequence Spaces

In this paper, the σ_duals of two classes important sequence spaces l 1(X) and l ∞(X) are investigated, and shows that some topology properties of locally convex space (X,τ) can be characterized by the σ _duals. The criterions of bounded sets in l 1(X) and l ∞(X ) with respect to the weak topologies generated by the σ _duals are obtained. Furthermore, a Schur type result and an automatic continuity theorem of matrix transformation are established.

Pseudometric Generating Property of Fuzzy Measures Convergence in Fuzzy Measure

The relations among three kinds of structural characteristics of fuzzy measure: (1) pseudometric generating property; (2) pseudometric generating property of type p; (3) null null additivity, and the convergence for sequence of measurable function on semi continuous fuzzy measure space are discussed. A set of equivalent conditions for each of these structural characteristics are presented, respectively. It is proved that null null additivity is equivalent to pseudometric generating property for a finite fuzzy measure on S compact space.

Empirical Bayes Absolute Error Loss Estimation for Parameter of One-Side Truncation Distribution Families

In this paper we propose an absolute error loss EB estimator for parameter of one-side truncation distribution families. Under some conditions we have proved that the convergence rates of its Bayes risk is o, where 0<λ,r≤1,Mn≤lnln n (for large n),Mn→∞ as n→∞.

CONVERGENCERATESIN THESTRONG LAWSOFASYMPTOTICALLY NEGATIVELY ASSOCIATEDRANDOM FIELDS

In this paper, a notion of negative side ρ \|mixing ( ρ\+- \|mixing) which can be regarded as asymptotic negative association is defined, and some Rosenthal type inequalities for ρ\+- \|mixing random fields are established. The complete convergence and almost sure summability on the convergence rates with respect to the strong law of large numbers are also discussed for ρ\+-\| mixing random fields. The results obtained extend those for negatively associated sequences and ρ\+*\| mixing random fields.