多组分间歇精馏工艺计算探讨

介绍用“微元时段”计算多组分间歇精馏的方法。     

Simulation-based sequential analysis of Markov switching stochastic volatility models

We propose a simulation-based algorithm for inference in stochastic volatility models with possible regime switching in which the regime state is governed by a first-order Markov process. Using auxiliary particle filters we developed a strategy to sequentially learn about states and parameters of the model. The methodology is tested against a synthetic time series and validated with a real financial time series: the IBOVESPA stock index (São Paulo Stock Exchange).     

RFID技术在电网资产全寿命周期管理应用模式探讨

为了配合电网企业建立RFID资产实物标识电子身份证系统,集成资产的实物流、信息流和价值流,实现账、卡、物相符一致,实现资产管理各阶段信息共享及开展资产全生命周期的跟踪管理,同时也为了提高电网设备的现代化管理水平,文章总结了多年来在电网设备RFID实物标识实施的切身体会,对RFID在国内外电力电网设备的应用方面进行了研究,重点对RFID技术在电网资产全寿命周期管理模式进行了探讨。     

高校资产管理系统的设计与研究

设计了适合衢州职业技术学院固定资产日常管理工作的资产管理系统.对该系统作了需求分析和详细设计,采用了ASP.NET框架技术和SQL Server后台数据库相结合的设计方法.系统基本实现了资产的登记、审核、查询、变更、统计、打印报表、上报数据等功能,有效地解决了资产管理工作的数据混乱、不准确、处理流程不规范等问题,有效地提高了管理人员的工作效率.     

Double auction mechanisms on Markovian networks

This paper studies the double auction (DA) mechanism in Ma and Li (2011) for a class of exchange economies. We extend their results to more general cases where sellers and buyers each form a complex time non-homogeneous Markovian chain, as specified in Ram et al. (2009), in the communication of their private information. A numerical example is also provided. Both bubbles and crashes are observed in the example, consistent with results of our theorems. Our example and theoretical results provide new evidence that a DA mechanism, widely utilized in real exchange markets, may contribute to the excess volatility identified in Shiller (1981) and LeRoy and Porter (1981).     

On a Mixture GARCH Time‐Series Model

Abstract. Recently, there has been a lot of interest in modelling real data with a heavy‐tailed distribution. A popular candidate is the so‐called generalized autoregressive conditional heteroscedastic (GARCH) model. Unfortunately, the tails of GARCH models are not thick enough in some applications. In this paper, we propose a mixture generalized autoregressive conditional heteroscedastic (MGARCH) model. The stationarity conditions and the tail behaviour of the MGARCH model are studied. It is shown that MGARCH models have tails thicker than those of the associated GARCH models. Therefore, the MGARCH models are more capable of capturing the heavy‐tailed features in real data. Some real examples illustrate the results.     

Volatility of Simulated High-Level Nuclear Waste Glass by Thermogravimetric Analysis

The volatilities of simulated, high-level nuclear waste glasses have been measured using thermogravimetric analysis (TGA). These volatilities were measured in the region of the glass transition temperature ( T _g) of the waste glasses, which is between 450° and 500°C. These data were obtained because the Waste Acceptance Preliminary Specifications require that no foreign materials be released into the canistered waste form upon heating of the canister to this glass transition temperature. In fact, all of the waste glass samples studied actually exhibited a net weight gain upon heating. This weight gain was shown to be due to oxygen uptake through oxidation of FeO. Powdered glass samples did show a small weight loss which was smaller in magnitude than the weight gain and was associated with water desorption. No true volatility was detected to the level of sensitivity (0.01 wt%) of the TGA instrument. This converts to a sensitivity of 330 μ g/m² of glass surface and a corresponding minimum value of 41 mg of volatiles for each Defense Waste Processing Facility conistered waste form. TGA experiments carried out at higher temperatures (800°C) revealed that organic concentrations in the waste glasses are less than 0.01 wt%. Thus, these results demonstrate that the Defense Waste Processing Facility will be able to comply with the Waste Acceptance Preliminary Specifications on the exclusion of foreign materials from the canistered waste forms, after exposure to T _g.     

基于R软件的金融资产收益波动率建模分析

金融资产收益波动率是金融计量分析的核心议题,该文考虑对其建模分析的计算机实现问题。利用R软件的强大计算与绘图功能,给出金融资产收益波动率各个模型的模拟实现以及对实际金融市场数据的各种建模分析。     

基于季节长记忆双自回归模型的日径流模拟

传统时间序列模型无法同时考虑径流序列的长记忆性和时变波动性,且模型参数限制严格,从而使日径流序列模拟受到限制,影响径流模拟预测精度。本文提出了同时考虑非平稳性、季节性、长记忆性和时变波动性的新型双自回归模型(WOA-SFIDAR),并与经典长记忆波动率模型(SFIAR-GARCH)进行对比,选取渭河流域4个水文站日径流序列进行模拟验证。结果表明：WOA-SFIDAR模型的模拟能力优于SFIAR-GARCH模型,模拟结果很好地保持了日径流过程的统计特性。7、8月份模拟均值误差相对较大,WOA-SFIDAR模型的误差范围(5.72～32.56)低于SFIAR-GARCH模型(7.42～48.02)。WOA-SFIDAR模拟逐月变差系数(C_v)和偏态系数(C_s)与实测序列统计值间偏差范围为0～0.51和0.02～1.31,优于SFIAR-GARCH模型(0.02～0.56和0.06～1.52);模拟结果能够保持日径流序列自相关系数(ACF)的变化趋势,且随滞时的增加,实测序列与模拟序列的ACF差距减小。文中模型扩展了水文随机模拟方法,可为日径流模拟...     

环保类上市公司流动资产结构的绩效贡献检验

以沪深交易所33家环境保护类上市公司为研究样本,检验上市公司流动资产结构与运营绩效的关系,分析企业经理人投资效率。研究发现:应收账款、存货均与加权平均净资产收益率存在显著正相关关系,货币资金与加权平均净资产收益率呈不显著负相关关系。实证结果与现有环保类上市公司BOT经营模式一致,且流动资产中应收账款和存货的运营管理是公司运作的关键因素。