基于主成分分析的多元线性回归用水量模型研究——以安徽省为例

用水量的准确预测对水资源规划具有重要意义。根据统计资料,选取了八项主要影响用水量变化的指标。按照主成分分析法原理,运用少数综合因子对影响用水量变化的原有八项指标进行了综合和简化,并研究其贡献率及综合效应;分析了用水量增长的特点,选用Logistic方程对综合因子进行回归分析;结合多元线性回归方法,建立了安徽省用水量模型;拟合结果表明,模型具有较高的精度;运用该模型,对安徽省2010年的用水量进行了预测;为水资源规划与管理提供参考依据。     

ML– and semiparametric estimation in logistic models with incomplete covariate data

ML–estimation of regression parameters with incomplete covariate information usually requires a distributional assumption regarding the concerned covariates that implies a source of misspecification. Semiparametric procedures avoid such assumptions at the expense of efficiency. In this paper a simulation study with small sample size is carried out to get an idea of the performance of the ML–estimator under misspecification and to compare it with the semiparametric procedures when the former is based on a correct assumption. The results show that there is only a little gain by correct parametric assumptions, which does not justify the possibly large bias when the assumptions are not met. Additionally, a simple modification of the complete case estimator appears to be nearly semiparametric efficient.     

论以粮换林换草与河西地区的可持续发展--以武威地区为例

分析了武威地区可持续发展的主要生态环境问题,讨论了生态恢复与重建面临的困境,论证了以粮换林换草对促进区域可持续发展的必要性和有效性,指出了以粮换林换草中应进一步研究的问题,提出生态重建要坚持多措施并举。     

An effective going concern prediction model for the sustainability of enterprises and capital market development

The purpose of this study is to construct a two-stage effective and innovative going concern prediction model to predict going concern doubt for the sustainability of enterprises and capital market development. Samples of this study are the companies listed on the Taiwan Stock Exchange or the Taipei Exchange, totalling 196 companies and including 49 companies with going concern doubt and 147 normal companies (with no going concern doubt). The data are taken from the Taiwan Economic Journal (TEJ) and the Market Observation Post System during the period from 2001 to 2016 (totalling 16 years). This study adopts a two-stage way to construct the going concern prediction models. In Stage I, the traditional statistical method of stepwise regression (SR) and the data mining technique artificial neural network (ANN) are applied to select the important variables. In Stage II, two decision tree algorithms (data mining techniques): classification and regression tree (CART) and C5.0 are used to establish the prediction models. The results show that the SR + CART model has the highest going concern prediction accuracy, with an overall accuracy of 87.42%.     

Bayesian assessment of dimensionality in reduced rank regression

We consider Bayesian inference about the dimensionality in the multivariate reduced rank regression framework, which encompasses several models such as MANOVA, factor analysis and cointegration models for multiple time series. The fractional Bayes approach is used to derive a closed form approximation to the posterior distribution of the dimensionality and some asymptotic properties of the approximation are proved. Finite sample properties are studied by simulation and the method is applied to growth curve data and cointegrated multivariate time series.     

中国电子商务企业生存的实证分析

本文通过Logisitc回归模型，对电子商务企业生存的影响因素进行了分析。笔者认为，电子商务企业的生存是受企业自身基因构成决定的，而电子商务企业的基因构成包括了企业家才能、资金、信息资本、人力资本、社会资本和技术资本。同时，企业的基因会随着环境的变化而不断地进行着调整和整合，以适应竞争的需要。实证分析的结果证实了笔者的判断。     

城市公交行业顾客满意度测评及其提升对策——以合肥市为例

城市公交作为城市经济运转的动脉,已经成为国内城市发展规划中的重中之重。然而,目前在城市公交行业占主体地位的国有公交企业却亟待提高营运效益,增强企业活力,以摆脱经营上的困境。立足于安徽省省会城市合肥市的公交行业,通过实证研究与规范研究相结合的方式,针对城市公交行业的顾客满意度测评及其提升对策问题进行了较为深入的探讨。     

Development of Habitat Suitability Criteria and In‐Stream Habitat Assessment for the Benthic Cyanobacteria Phormidium

Global demand for freshwater has led to unprecedented levels of water abstraction from riverine systems. This has resulted in large alterations in natural river flows. The deleterious impacts of reduced flows on fish and macroinvertebrate abundances have been thoroughly investigated; in contrast, there is a limited understanding of the potential for changes in the abundance of nuisance benthic algal/cyanobacterial blooms. In New Zealand, Phormidium sp. blooms are common in numerous rivers during summer low flows. In this study, an in‐stream habitat assessment is used to examine the relationship between Phormidium habitat availability and reducing flows. Over 650 observations of Phormidium mats, from seven sites (Hutt River, lower North Island, New Zealand), were used to construct habitat suitability curves for depth, velocity and substrate. Preference curves were fitted using both the ‘forage ratio’ and ‘quantile regression’ methods. Phormidium growth, observed at all seven sites, increased significantly from upstream (uppermost site, 5.2% mat cover) to downstream (63.5%). The habitat suitability curves revealed Phormidium had a large tolerance to velocity, depth and substrate type. Consequently, decreases in flow had only negligible effects on available Phormidium habitat. During periods of stable flow, Phormidium abundance positively correlated with increased nitrogen concentrations, potentially explaining the large variation in Phormidium cover from upstream to downstream. Quantile regression generated habitat suitability criteria were a more accurate predictor of available Phormidium habitat than the forage ratio criteria. Copyright © 2013 John Wiley & Sons, Ltd.     

城市需水的智能预测方法研究

选取对城市用水影响较大的因素作为预测指标,通过HP滤波分析其指标及用水量的趋势成分及波动成分。应用多元线性回归法对趋势性成分进行模拟,应用模糊神经网络对波动性成分进行网络训练,以获得城市需水的总预测值。以大连市1980~2000年用水及其相关因子为例建模,以2001~2007年指标对模型进行检验,预测了大连市2010、2020年的需水值,为城市水资源规划提供一定的理论支持。     

蚁群生成树算法研究

应用蚁群生成树算法搜索了有34个节点的连接图的生成树,并采用正交设计法和均匀设计法进行了参数优化配置方法研究。结果表明:对于参数较多的蚁群算法,应用正交设计法和均匀设计法进行参数优化配置是一种可行且有效的途径,可有效提高蚁群算法的收敛速度,在求解精度上也有一定优势;充分发挥人类智能与仿生物智能的各自优势是克服单纯靠智能优化方法随机搜索缺点的关键;当蚂蚁数目为100、信息素相对重要性因素为0.3、信息素衰减系数为3.6、信息素挥发系数为0.4、信息素增加强度系数为14时,蚁群生成树算法效果最佳。