区域水资源开发利用程度综合评价的GPPIM

水资源开发利用程度评价是一个由多指标组成的复杂巨系统,其难点是如何合理地建立评价该系统的数学模型。当前的评价模型随着评价内容的不同而变化,精度较难控制。为解决单项水资源开发利用程度评价指标评价结果的不相容问题,提高水资源开发利用程度综合评价各层次的分辩力和评价模型的精度,论文采用大样本数据,利用投影寻踪、遗传算法、插值型曲线和水资源开发利用程度评价标准,为水资源开发利用程度综合评价建立了一种新的数学模型---遗传投影寻踪插值模型(GPPIM)。实例研究表明,GPPIM建模方法直观、可靠、精度高,既有较强的分类功能,又有较好的排序功能,可广泛应用于各种水资源问题的综合评价。     

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas     

旱涝趋势的投影寻踪预测模型

介绍了投影寻踪回归（ＰＰＲ）建模的基本原理和算法实现。选用太阳黑子年平均数和旱涝分型的转移概率作因子，建立了长江中下游旱涝趋势的ＰＰＲ预测模型，并与用相同资料建立的Ｂ－Ｐ神经网络模型预测结果进行了比较。     

Water Quality Assessment and Modeling of an Effluent-Dominated Stream, the Notwane River, Botswana

In an effort to assess current and future water quality of the only perennial river in southeastern Botswana, this study presents water quality monitoring and modeling results for the effluent-dependent Notwane River. The water quality along the Notwane River, pre- and post-implementation of secondary wastewater treatment, was compared and results demonstrated that water quality improved after the new wastewater treatment plant (WWTP) went online. However, stream standards for chemical oxygen demand, total dissolved phosphorous, and fecal coliform were exceeded in most locations and the critical dissolved oxygen (DO) reached concentrations of less than 4 mg L⁻¹. High dissolved P concentrations and intense macrophyte growth at the impounding ponds and at sites within 30 km of the effluent waste stream confluence suggest that eutrophication was a function of P release from the ponds. Results of DO modeling demonstrated that an unpolluted inflow at approximately 10 km downstream of the confluence was responsible for raising DO concentrations by 2.3 mg L⁻¹, while SOD was responsible for a decline in DO concentrations of 1.4 mg L⁻¹ at 6 km downstream of the confluence. Simulations also showed higher DO concentrations during winter months, when water temperatures were lower. Simulations, in which the distributed biochemical oxygen demand (BOD) loading from cattle excrement was decreased, produced nominal increases in DO concentrations. An increase in WWTP BOD loadings to projected 2020 values resulted in a 1.3 mg L⁻¹ decrease in the critical DO concentration. Furthermore, a decrease in treatment plant efficiency, from 94% to 70% BOD removal, produced critical DO concentrations and anoxia along much of the modeled reach. This has significant implications for Gaborone, especially if decreased WWTP efficiency occurs as a result of the expected future increase in pollutant loadings.     

环境质量评价中关键因子识别的方法研究

应用投影寻踪聚类方法分析环境影响指标的数据资料 ,不但可以根据数据内在特性确定各评价指标的相对权重 ,避免权重人为给定的任意性 ,而且还可以通过逐次筛选找出影响环境质量的关键因子。本文将该方法成功地应用于南京市秦淮河水环境评价中 ,筛选出了影响秦淮河水质的关键因子 ,可供秦淮河水环境监测和治理作参考。另一方面 ,该方法还可以推广应用于其它类似问题的综合分析研究中。     

周庄旅游者的结构特征及利益追求

旅游客源市场由不同结构特征的旅游者组成,其利益追求各不相同,对此加以分析,可以制定正确的营销策略,提供科学依据.以周庄为案例,采用随机抽样问卷调查法,分别对周庄旅游者的性别结构、年龄结构、文化结构、家庭收入水平结构和职业结构进行了分析.结果显示,周庄旅游者以男性游客为主体,25～44岁的中青年游客占大多数;文化程度以大专及以上层次为主,职业构成比较分散,企事业管理人员居多;家庭月收入水平高于全国平均水平.对旅游者的利益追求进行了初步的探讨,并结合游客结构特征和利益追求的分析结果,提出了周庄未来旅游产品的营销策略.     

基于两阶段降维的中国经济发展协调性评价

为了研究中国2000 - 2008年间经济发展与环境、资源、人民生活水平三个方面的协调程度,本文建立了包括4个子系统、9个子项目、112个指标的评价指标体系,利用主成分分析方法与投影寻踪方法对评价指标进行两阶段降维分析,将高维数据转化为直观的评价值.根据最终投影函数值对2000 - 2008年中国经济发展的总体协调性进行了评价,评价结果显示:近年来,中国经济发展协调性发展趋势良好,且各子系统对经济发展的协调性都有着重要影响.在对各子系统的发展情况迸一步分析后指出:对于环境、资源、生活子系统的发展影响最大的子项目分别是污染排放与治理、矿物能源和农村生活水平.为了衡量各子系统间的协调程度,本文提出了一种新的计算系统间协调度的方法,在现有系统协调度评价方法的基础上进行了一定的改进.经济—环境、经济—资源、经济—生活三组子系统的协调度计算结果显示:各组子系统间的协调度都在经历迅速提高后,逐渐回落波动至平稳,而环境、资源和生活子系统的发展目前仍滞后于经济子系统.     

基于投影寻踪聚类的油气管道失效可能性评价

为保障油气管道运行安全,将投影寻踪聚类的方法引入油气管道失效可能性评价中,从系统理论的角度将油气管道失效分为致灾因子危险性、承灾体的脆弱性和应对能力脆弱性3个子系统,据此建立油气管道失效可能性评估指标体系,然后基于投影寻踪聚类的失效可能性评价模型,对油气管道失效可能性进行量化分析,从而确定其失效可能性等级。实例分析表明,所建立的失效可能性评价模型能对油气管道失效可能性进行评价,可为管道的风险管理提供决策依据。     

舟山群岛降水中阴离子及pH值的特征分析

通过对舟山站点降水中的4种阴离子(F^-、Cl^-、NO^3-和SO4₄^2-)及pH值近2a的连续观测,对阴离子和pH值的范围及变化趋势进行了描述;利用本征矢量投影技术对实验数据进行降维处理,并对造成异常样品点的影响因素进行了分析.进一步因子分析结果显示,舟山站点降水样本点在阴离子及pH值方面的分布特征可基本确定为2个因子,SO₄^2--NO₃^-因子(FA1)及Cl^-因子(FA2),可将其概括为“人类活动因子”与“海洋因子”,因子分析结果得到的主要因子FA1、FA2与本征矢量投影得到的主成分PC1、PC2基本对应,因子分析的结果对解释影响样品点差异的实际变量方面更具实际意义,即舟山站点样本点的异常值可归为2类,受SO4₄^2---NO₃^-因子(FA1)影响及受Cl^-因子(FA2)影响.     

水环境质量评价的投影寻踪模型及其应用

将投影寻踪分类模型应用于水环境质量综合评价中,利用基于实码的加速遗传算法来优化投影方向,将多维数据指标转换成低维子空间,通过寻求最优投影方向来计算投影函数值,从而根据投影值的大小进行水环境质量评价。结合实例进行了应用,结果较令人满意,为水环境质量评价提供了一条新的方法和途径。