An economic model for investing in sulfur oxide control technology development

The model estimates, subject to restrictions, the functional relationship between national sulfur dioxide discharges and investment in control technology development. Estimates may be made for different product demands, allowed cost increases, and clean fuel availabilities. Control technology development may be accelerated by increased investment. Both optimal and sub-optimal solutions are calculated for an example problem. A general computing method is provided.The model was presented at the Industrial Process Design for Pollution Control Workshop, Chicago, Illinois, Oct. 1973; copyright released by the American Institute of Chemical Engineers for publication for the first time in the monographNormative Analysis in Policy Decisions: Public and Private.     

中国碳排放的省域差异及影响因素的实证研究

参照IPCC(2006)以及国家气候变化对策协调小组办公室和国家发改委能源研究所)的方法,估算了我国30个省(直辖市、自治区)的1997—2011年期间的二氧化碳排放量.数据显示,我国各省(直辖市、自治区)的二氧化碳排放量从整体上基本都呈现出上升趋势,地区差异比较显著.总体上来讲,我国的二氧化碳排放量呈现出由东到西依次递减的规律特征,东部地区的二氧化碳排放量最多,中部地区次之,西部地区二氧化碳排放量最少,而且东部地区的二氧化碳排放在绝对量上大大超过中西两大区域.产业结构和经济发展是影响各地区二氧化碳排放量的主要因素,能源消费结构和出口贸易对各地区碳排放量的影响不显著.     

我国能源-环境-经济系统的区域间建模

本研究试图探讨用“自上而下”和“自下而上”相结合的建模方法,对我国二氧化硫和二氧化碳减排进行区域间建模.本研究以一个用于分析硫税的区域间波及影响、以及评价电力部门的脱硫技术的区域间可计算一般均衡模型为基础平台;从理论上探讨了如何对该模型进行扩展和改进.首先本研究对该模型的要点进行了阐述,强调了把能源技术模型融合在区域间可计算一般均衡模型中的建模方法.然后本研究对于实行环境税和排放权交易的环境经济效果进行了比较,用成本收益法分析了工业部门对减排技术的选择,并以前述模型为基础建立了区域间模型.本研究所提出的模型可以被用来从区域统筹的观点,对我国能源-环境-经济系统的可持续发展进行预测和分析.最后本研究提出应该从更新数据、研究环境政策和技术进步之间的关系等方面,进一步发展该模型.     

On an Efficient Use of Gradient Information for Accelerating Interval Global Optimization Algorithms

This paper analyzes and evaluates an efficient n-dimensional global optimization algorithm. It is a natural n-dimensional extension of the algorithm of Casado et al. [1]. This algorithm takes advantage of all available information to estimate better bounds of the function. Numerical comparison made on a wide set of multiextremal test functions has shown that on average the new algorithm works faster than a traditional interval analysis global optimization method.     

Censored multiple regression by the method of average derivatives

This paper proposes a technique [termed censored average derivative estimation (CADE)] for studying estimation of the unknown regression function in nonparametric censored regression models with randomly censored samples. The CADE procedure involves three stages: firstly-transform the censored data into synthetic data or pseudo-responses using the inverse probability censoring weighted (IPCW) technique, secondly estimate the average derivatives of the regression function, and finally approximate the unknown regression function by an estimator of univariate regression using techniques for one-dimensional nonparametric censored regression. The CADE provides an easily implemented methodology for modelling the association between the response and a set of predictor variables when data are randomly censored. It also provides a technique for “dimension reduction” in nonparametric censored regression models. The average derivative estimator is shown to be root-n consistent and asymptotically normal. The estimator of the unknown regression function is a local linear kernel regression estimator and is shown to converge at the optimal one-dimensional nonparametric rate. Monte Carlo experiments show that the proposed estimators work quite well.     

A closer look at the economic-environmental disparities for regional development in China

Although China has harvested the fruits of its rapid economic growth over a period of several decades, it has encountered serious environmental problems, an important one being air pollution in the form of soot, dust, and sulfur dioxide. In considering the concept of ‘green-GDP’, this paper analyzes China’s regional development by examining its economic performance while taking into account various environmental factors. In addition to computing technical efficiency for 31 regions in China, a cross-efficiency measure is applied to differentiate the genuine DMUs. ‘Overall’ efficient regions and ‘false positive’ ones are recognized by a false positive index (FPI). It is found that the coastal regions perform on average better than the inland regions both economically and environmentally. For inefficient regions, the benchmark should be those regions with high cross-efficiency mean scores (e.g., Guangdong) rather than those with high self-appraisal scores (e.g., Shanghai). A cross-tabulation illustrating the difference between GDP-oriented performance and Pollution-oriented performance shows that the coastal regions make up the dominant proportion in terms of the benchmarks for economic-environmental optimization.     

Explicit estimates of sums related to the Nyman–Beurling criterion for the Riemann Hypothesis

We give an estimate for sums appearing in the Nyman–Beurling criterion for the Riemann Hypothesis. These sums contain the Möbius function and are related to the imaginary part of the Estermann zeta function. The estimate is remarkably sharp in comparison to other sums containing the Möbius function. The bound is smaller than the trivial bound – essentially the number of terms – by a fixed power of that number. The exponent is made explicit. The methods intensively use tools from the theory of continued fractions and from the theory of Fourier series.     

On the Probability of Correct Selection in Ordinal Comparison over Dynamic Networks

We consider distributed ordinal comparison of selecting the best option which maximizes the average of local reward function values among available options in a dynamic network. Each node in the network knows only his reward function, and edge-connectivity across the nodes changes over time by Calafiore??s model. To estimate each option??s global reward function value, local samples for each option are generated at each node and those are iteratively mixed over the network by a weighted average of local estimates of instantaneous neighbors. Each node selects an option that achieves the maximum of the current global estimates as an estimate of the best option. We establish a lower bound on the probability of correct local-selection at any node, which uniformly converges over the nodes to a lower bound on the probability of correct global-selection by a virtual centralized node with the total available samples.     

Operation strategy optimization of desulfurization system based on data mining

Desulfurization systems in coal-fired power stations often suffer the problem of high operating costs caused by a rule-of-thumb control strategy, which implies great potential for optimization of the operation. Due to the complex desulfurization mechanism, frequently fluctuating unit load, and severe disturbance, it is challenging to determine the optimal operating parameters based on the traditional mechanistic models, and the operating parameters are closely related to the operational efficiency of the flue gas desulfurization system. In this paper, an operation strategy optimization method for the desulfurization process is proposed based on a data mining framework, which is able to determine online the optimal operating parameter settings from a large amount of historical data. First, Principal Component Analysis (PCA) is used to reduce data redundancy by mapping the data into a new vector space. Based on the new vector space, an enhanced fuzzy C-means clustering (Enhanced-FCM) is developed to cluster the historical data into groups sharing similar characteristics. Taking sulfur dioxide emission concentration as a constraint condition, the system is optimized with economic benefits and desulfurization efficiency as the objective function. When performing optimization, the group that current operating conditions belong to is determined first, then the operating parameters of the best performance are searched within the group and provided as the optimization results. The method is validated and tested based on the data from a wet flue gas desulfurization (WFGD) system of a 1000 MWe supercritical coal-fired power plant in China. The results indicate that the proposed operation strategy can appropriately obtain operating parameter settings at different conditions, and effectively reduce the desulfurization cost under the constraint of meeting emission requirements.     

同源密度函数方差估计值

本文提出同源密度函数方差估计值。它是依据每个随机变量函数方差的近似公式由条件死亡概率方差和同源生存率方差估计值推导出来的。其数值、置信限平均宽度和经验覆盖在各种极端临床条件下均与Greenwood密度函数方差估计值相等或相近 ,而计算大大简化。由此我们认为同源密度函数方差估计值可以取代Greenwood估计值     

Order selection for heteroscedastic autoregression: A study on concentration

We consider an autoregressive model where the variance is allowed to be a function of time, unconditional on the past. Pötscher (1989) has proven that, regardless of the shape of the variance function, order selection can be made consistently. However, this procedure does not account for the non-stationary behavior. We consider the concentration of the variance function and its effect on order selection. We show that an order free estimate of the variance function can be constructed and propose an order selection criterion based on this estimate. Consistency is established and simulation results verify a large increase in the probability of selecting the correct order for finite samples.     

A CUSUM test for detecting change in the transfer functions of open loop stochastic systems

A cumulative sum test for detecting change in the transfer function of open loop stochastic systems is proposed. The test is based on the logarithmic transformation of the “evolutionary gain-spectra” estimate. A design relation between the band width parameters of the evolutionary spectral density estimate and the average run length of the cumulative sum test is obtained. This cumulative sum technique has been applied to four simulated systems, one of which is completely time invariant and the other remaining three had change points at different time points.     

甲型H1N1流感的死亡率高吗——Bayes计量分析框架下的建模与估算

在全球甲型H1N1流感大流行背景下,本文在充分考虑各国甲流感死亡率可能存在个体混合效应、独立效应、相关效应及空间相关效应基础上,运用Bayes计量分析框架下的模型选择标准确定描述各国甲流感死亡率的最优模型,并基于该模型对不同国家甲流感死亡率进行估算。结果显示:个体独立、空间相关效应模型能很好拟合各国甲流感疫情统计数据,利用该模型估算的全球甲流感平均死亡率为0.577%。     

Mathematical model of copper corrosion

A new partial differential model for monitoring and detecting copper corrosion products (mainly brochantite and cuprite) is proposed to provide predictive tools suitable for describing the evolution of damage induced on bronze specimens by sulfur dioxide (SO₂) pollution. This model is characterized by the movement of a double free boundary. Numerical simulations show a nice agreement with experimental result.     

The structure of instantaneous frequencies of periodic analytic signals

In this paper, the structure of analytic signals is investigated by means of the relation between analytic signals and functions in the Hardy space. It is shown that an analytic signal is made up of two parts, one depending on the amplitude of the signal and another on the boundary value of an inner function. Based on this result, properties of the instantaneous frequencies of these two parts are studied, and it is found that negative instantaneous frequencies are caused by the amplitude of a signal. Finall...     

On the estimation of a monotone conditional variance in nonparametric regression

A monotone estimate of the conditional variance function in a heteroscedastic, nonparametric regression model is proposed. The method is based on the application of a kernel density estimate to an unconstrained estimate of the variance function and yields an estimate of the inverse variance function. The final monotone estimate of the variance function is obtained by an inversion of this function. The method is applicable to a broad class of nonparametric estimates of the conditional variance and particularly attractive to users of conventional kernel methods, because it does not require constrained optimization techniques. The approach is also illustrated by means of a simulation study.     

Pointwise error estimates for trigonometric interpolation and conjugation

An estimate due to Gaier [2] for the error committed in replacing a periodic function f by an interpolating trigonometric polynomial is sharpened in such a way that the estimate makes evident the interpolating property of the polynomial. A similar improvement is given for Gaier's estimate of the difference between the conjugate of f and the conjugate trigonometric polynomial.     

Jump-Preserving Regression and Smoothing using Local Linear Fitting: A Compromise

This paper deals with nonparametric estimation of a regression curve, where the estimation method should preserve possible jumps in the curve. At each point x at which one wants to estimate the regression function, the method chooses in an adaptive way among three estimates: a local linear estimate using only datapoints to the left of x, a local linear estimate based on only datapoints to the right of x, and finally a local linear estimate using data in a two-sided neighbourhood around x. The choice among these three estimates is made by looking at differences of the weighted residual mean squares of the three fits. The resulting estimate preserves the jumps well and in addition gives smooth estimates of the continuity parts of the curve. This property of compromise between local smoothing and jump-preserving is what distinguishes our method from most previously proposed methods, that mainly focused on local smoothing and consequently blurred possible jumps, or mainly focused on jump-preserving and hence led to rather noisy estimates in continuity regions of the underlying regression curve. Strong consistency of the estimator is established and its performance is tested via a simulation study. This study also compares the current method with some existing methods. The current method is illustrated in analyzing a real dataset.     

京津冀地区PM2.5污染特征的研究————-基于函数型数据分析的视角

近年来京津冀地区的雾霾重度污染事件频发, 引起国家和社会的普遍关注. 以京津冀地区68个监测站的数据为基础, 研究了京津冀地区PM2.5小时间隔的年度数据主要变异模式、时空变化类型等污染特征. 还研究了二氧化硫、氮氧化物年度累计排放量对PM2.5浓度变化的影响. 结果表明, 氮氧化物的排放对PM2.5浓度的贡献更显著, 削减氮氧化物等污染物的排放可有效降低PM2.5浓度, 改善空气质量. 采用函数型数据分析方法, 相对于传统的统计均值方法, 能够更有效的使用所采集到的不同的数据类型, 进行更细致的分析, 从而得到更可靠的结论.     

广义线性模型中一类推广的拟似然估计与异方差性诊断检验

本文考虑了随机设计情形下一类普通的异方差回归模型，在这个模型中，假定回归函数与方差函数之间的关系服从推广的广义非线性模型，该模型在实际中很常见，广义线性模型便是其特例，首先，我们导出了均值函数的局部加权拟似然估计，然后，用它来得到方差函数的估计，并且证明了这些估计有较好的性质，最后，建立了异方差检验统计量，文中的方法很吸引人。