绿色生态住宅小区环境性能评价研究

建立一套标准的、适用的和可操作的绿色生态小区环境性能评价指标体系。已成了推广和发展绿色生态小区的必要条件。本文按照评价指标体系建立的原则．从住宅小区的水环境系统、气环境系统、声环境系统、光环境系统、热环境系统、能源系统、绿化系统、废弃物管理与处置系统、绿色建筑材料系统、小区智能化系统、开发系统和管理系统方面，建立评价指标体系。使用层次分析法对评价指标体系的指标权重进行确定，应用灰色系统评价方法对住宅小区环境性能进行评价．通过具体实例证实模型是科学和实用的。     

顺义区地下水水源地脆弱性评价

从顺义区地下水源地的特点和实际情况出发,建立了顺义区地下水源地脆弱性综合评价指标体系,并基于该指标体系采用灰关联度评价方法对顺义区地下水源地进行脆弱性综合评价。将综合评价与固有脆弱性评价对比分析,结果表明,采用地下水水源地综合脆弱性与固有脆弱性相结合的评价方法评价结果更为科学合理,可以更好地评价顺义区地下水源地脆弱性。     

基于灰色关联分析的岷江上游流域震后水质综合评价

汶川大地震是我国建国以来强度最大、破坏最严重的一次地震,使本就脆弱的岷江上游生态环境和水环境受到极大影响,岷江是成都市和都江堰市的主要水源,本次地震又发生在这两大城市的上游,震区中岷江水质直接关系到这两个城市的用水安全。本文根据跟岷江映秀段的水质监测结果,利用灰色关联分析法对水质进行综合评价分析,研究震后岷江水质特征,为岷江的水环境保护及成都与都江堰的饮用水安全提供参考。     

基于组合模型的能源需求预测

能源是人类生存和发展的重要物质基础,也是当今国际政治、经济、军事、外交关注的焦点。能源需求预测是合理制定能源规划的基础。能源需求预测的模型很多,总的来说,可以分为单一模型预测和组合模型预测。本文在分析几种常用单一模型的优缺点和适用范围的基础上,建立BP神经网络与灰色GM的优化组合模型,对江苏省未来十五年煤炭和石油的需求量进行预测。结果表明:①随着经济的发展,未来江苏省对煤炭和石油的需求量逐渐增加,其中煤炭从2008年的19 601.39万t标准煤增加到2020年的25 615.26万t标准煤,年均增长率为1.81%;石油从2008年的2 628.64万t标准煤增加到2020年的3 532.60万t标准煤,年均增长率为1.36%;②基于BP网络与GM(1,1)的组合模型克服了单一模型的缺点,实现了优化组合模型"过去一段时间内组合预测误差最小"的原则,且预测结果误差较小,不仅适用于能源的中长期预测,还可以推广到其他领域。     

灰色关联度模型在海洋产业分析中的应用——以辽宁省为例

辽宁省作为中国的海洋资源大省,在国内率先提出"海上辽宁"战略。阐述了辽宁省海洋经济的现状,以动态的分辨系数为基础,用灰色关联度模型对辽宁省的海洋产业特点进行了分析,进而针对辽宁省海洋产业结构应如何调整等问题提出了积极的对策和建议。     

Abundance, behavior, and movement patterns of western gray whales in relation to a 3-D seismic survey, Northeast Sakhalin Island, Russia

A geophysical seismic survey was conducted in the summer of 2001 off the northeastern coast of Sakhalin Island, Russia. The area of seismic exploration was immediately adjacent to the Piltun feeding grounds of the endangered western gray whale (Eschrichtius robustus). This study investigates relative abundance, behavior, and movement patterns of gray whales in relation to occurrence and proximity to the seismic survey by employing scan sampling, focal follow, and theodolite tracking methodologies. These data were analyzed in relation to temporal, environmental, and seismic related variables to evaluate potential disturbance reactions of gray whales to the seismic survey. The relative numbers of whales and pods recorded from five shore-based stations were not significantly different during periods when seismic surveys were occurring compared to periods when no seismic surveys were occurring and to the post-seismic period. Univariate analyses indicated no significant statistical correlation between seismic survey variables and any of the eleven movement and behavior variables. Multiple regression analyses indicated that, after accounting for temporal and environmental variables, 6 of 11 movement and behavior variables (linearity, acceleration, mean direction, blows per surfacing, and surface-dive blow rate) were not significantly associated with seismic survey variables, and 5 of 11 variables (leg speed, reorientation rate, distance-from-shore, blow interval, and dive time) were significantly associated with seismic survey variables. In summary, after accounting for environmental variables, no correlation was found between seismic survey variables and the linearity of whale movements, changes in whale swimming speed between theodolite fixes, mean direction of whale movement, mean number of whale exhalations per minute at the surface, mean time at the surface, and mean number of exhalations per minute during a whales surface-to-dive cycle. In contrast, at higher received sound energy exposure levels, whales traveled faster, changed directions of movement less, were recorded further from shore, and stayed under water longer between respirations.     

Distribution and abundance of western gray whales off northeastern Sakhalin Island, Russia, 2001’003

In 2001–2003, >60,000 km of aerial surveys and 7,700 km of vessel surveys were conducted during June to November when critically endangered Korean–Okhotsk or western gray whales (Eschrichtius robustus) were present off the northeast coast of Sakhalin Island, Russia. Results of surveys in all years indicated gray whales occurred in predominantly two areas, (1) adjacent to Piltun Bay, and (2) offshore from Chayvo Bay, hereafter referred to as the Piltun and offshore feeding areas. In the Piltun feeding area, the majority of whales were observed in waters shallower than 20 m and were distributed from several hundred meters to ∼ 5 km from the shoreline. In the offshore feeding area during all years, the distribution of gray whales extended from southwest to northeast in waters 30–65 m in depth. During all years, the distribution and abundance of whales changed in both the Piltun and offshore feeding areas, and both north–south and inshore–offshore movements were documented within and between feeding seasons. The discovery of a significant number of whales feeding in the offshore area each year was a substantial finding of this study and raises questions regarding western gray whale abundance and population levels, feeding behavior and ecology, and individual site-fidelity. Fluctuations in the number of whales observed within the Piltun and offshore feeding areas and few sightings outside of these two areas indicate that gray whales move between the Piltun and offshore feeding areas during their summer–fall feeding season. Seasonal shifts in the distribution and abundance of gray whales between and within both the Piltun and offshore feeding areas are thought, in part, to be a response to seasonal changes in the distribution and abundance of prey. However, the mechanism driving the movements of whales along the northeast coast of Sakhalin Island is likely very complex and influenced by a multitude of factors. *Deceased     

基于灰色聚类方法的湖泊营养状态综合评价

将湖泊水体的营养状态看作一个灰色系统,建立用于识别湖泊营养状态属性的灰色聚类综合评价模型,将水质级别作为一个灰类,水质状态作为灰色变量,根据灰色白化权函数聚类方法来确定水体营养状况归类。以太湖为例,基于分布全湖的20个监测点数据,运用灰色聚类法对其进行富营养状态综合评价,结果表明,监测时段太湖大部分水体基本处于中营养水平,局部湖面达到中度富营养状态,客观地反映了太湖湖区水体营养状况。     

基于主成分—聚类分析的贫困县（区）经济发展研究——以陕南地区国家级贫困县（区）为例

采用国内生产总值、人均纯收入、城镇固定资产投资、社会消费品零售总额等11个指标,运用主成分分析法对陕南地区20个国家级贫困县（区）的经济发展水平进行了评价,在此基础上运用聚类分析法将贫困县（区）分成四种类型：第一类是＂第二、第三产业并进型＂的汉滨区,第二类是＂特色农业带动型＂的商州区,第三类是＂优势矿业驱动型＂的洛南县和旬阳县,第四类是＂传统农业主导型＂的其余16个贫困县,针对各类型贫困县（区）提出相应的发展对策。     

基于可变模糊聚类的城镇综合承灾能力评价研究

城镇灾害的多样性、频繁发生与其造成的各种损失和破坏的严重化趋势,已经对城镇经济社会发展构成重大威胁。城镇应对灾害的预测、防御、救助及灾后恢复的综合能力,直接决定了城镇可持续发展的基础和能力。建立了基于城镇社会、经济和环境属性功能的城镇综合承灾能力评价指标体系,运用可变模糊聚类方法,通过指标权重、相对隶属度与聚类中心之间的动态迭代,得到了更为合理的样本城镇的防灾、抗灾、救灾和灾后恢复能力相对比较结果。与已有研究相比,可变模糊聚类在综合评价问题上的数据处理和分析能力更客观和多样化。