基于TNPE的智能电网虚假数据注入攻击检测

为实现智能电网中虚假数据注入攻击的实时检测,提高电力系统运行的安全性,采用1种基于时序近邻保持嵌入的方法,对正常状态下采集到的电网历史量测数据建立离线模型,得到T2统计限,将实时数据通过模型获得的T2统计量与离线模型的统计限进行对比,若超过统计限,则说明存在虚假数据注入攻击.该方法在提取局部空间结构特征的基础上,可同时...     

Estimating non-native plant richness with a species-accumulation model along roads

Monitoring non-native plant richness is important for biodiversity conservation and scientific research. The species-area model (SA model) has been used frequently to estimate the total species richness within a region. However, the conventional SA model may not provide robust estimations of non-native plant richness because the ecological processes associated with the accumulation of exotic and native plants may differ. Because roads strongly dictate the distributions of exotic plants, we propose a species-accumulation model along roads (SR model), rather than an SA model, to estimate the non-native plant richness within a region. Using 270 simulated data sets, we compared the differences in performance between the SR and SA models. A decision tree based on prediction accuracy was created to guide model application, which was validated using field data from 3 national nature reserves in 3 different provinces in China. The SR model significantly outperformed the SA model when non-native species were restricted to the roadsides and the proportion of uncommon exotic species was small. More importantly, the SR model accurately estimated the non-native plant richness in all field sites with an error of <1 species per site. We believe our new model meets the practical need to efficiently and robustly estimate non-native plant richness, which may facilitate effective biodiversity conservations and promote research on non-native plant invasion and vegetation dynamics.     

A Bayesian-weighted approach to predicting the number of newly discovered rare species

In natural ecological communities, most species are rare and thus susceptible to extinction. Consequently, the prediction and identification of rare species are of enormous value for conservation purposes. How many newly found species will be rare in the next field survey? We took a Bayesian viewpoint and used observed species abundance information in an ecological sample to develop an accurate way to estimate the number of new rare species (e.g., singletons, doubletons, and tripletons) in an additional unknown sample. A similar method has been developed for incidence-based data sets. Five seminumerical tests (3 abundance cases and 2 incidence cases) showed that our proposed Bayesian-weight estimator accurately predicted the number of new rare species with low relative bias and low relative root mean squared error and, accordingly, high accuracy. Finally, we applied the proposed estimator to 6 conservation-directed empirical data sets (3 abundance cases and 3 incidence cases) and found the prediction of new rare species was quite accurate; the 95% CI covered the true observed value very well in most cases. Our estimator performed similarly to or better than an unweighted estimator derived from Chao et al. and performed consistently better than the naïve unweighted estimator. We recommend our Bayesian-weight estimator for conservation applications, although the unweighted estimator of Chao et al. may be better under some circumstances. We provide an R package RSE (r are s pecies e stimation) at https://github.com/ecomol/RSE for implementation of the estimators.     

Integrating Modeling and Field Experiments to Evaluate Impacts of Vegetative Practices on Ponderosa Pine Watersheds1

Abstract: Determining watershed response to vegetation treatment has been the subject of numerous hydrologic studies over the years. However, generalizing the information obtained from traditional paired‐watershed studies to other watersheds in a region is problematic because of the empirical nature of such studies and the context dependence of hydrologic responses. This paper addresses the issue of generalizing hydrologic information through integration of process‐based modeling and field observations from small‐scale watershed experiments. To this end, the results from application of a process‐based model were compared with the results from small‐scale watershed experiments in ponderosa pine forests of Arizona. The model simulated treatment impacts reasonably well when compared to the traditional paired‐watershed approach. However, the model tended to overestimate water yields during periods of low flow, and there was a significant difference between the two approaches in the estimation of treatment impacts during the first four years following treatment. The results indicate that the lumped‐parameter modeling approach used here may be limited in its ability to detect small changes, and tends to overestimate changes that occur immediately following treatment. It is concluded that watershed experiments can be highly informative due to their direct examination of cause‐effect relationships, while process‐based models are useful for their processing power and focus on functional relationships. The integrated use of both watershed experiments and process‐based models provides a way to generalize hydrologic information, illuminate the processes behind landscape treatment effects, and to generate and test hypotheses.     

长江中下游夏季极端降水事件频次的统计降尺度模拟与预估

利用CMIP5三个耦合模式的历史模拟及不同情景预测结果、NCEP/NCAR再分析资料和长江中下游观测降水资料,采用统计降尺度方法对长江中下游夏季极端降水频次进行模拟和预估。首先,通过计算相关的方法,获取建立统计降尺度预测模型所需的预测因子。提取的预测因子同时满足既是观测环流要素场影响极端降水的关键区域,又是模式要素场预报的高技巧区域两个条件;然后,结合挑选出的预测因子,利用多元线性回归方法建立长江中下游极端降水的统计降尺度预测模型,并对模型性能进行检验。交叉检验结果表明,此种统计降尺度方法能对过去长江中下游极端降水变化有较好的再现能力,且多个降尺度模型结果的集合能进一步提高降尺度方法的模拟技巧;最后,将建立的统计降尺度模型应用于CMIP5未来3种不同的排放情景来对极端降水进行未来预估,并对多模式结果进行集合。结果显示,统计降尺度模型预估未来几个年代际长江中下游夏季极端降水频次相对于1986~2005年呈增加趋势,21世纪中、后期高排放情景下极端降水频次增加幅度高于低排放情景。     

近30 a长三角地区港口规模分布演化分析

以港口货物吞吐量和港口集装箱吞吐量为指标,运用首位度、位序-规模法则和Kernel密度估计对长三角地区港口规模分布进行研究。结果表明:(1)长三角地区港口等级规模分布由首位分布向位序-规模分布演变;港口货物运输与集装箱运输的首位分布特征演变具有内在一致性,但演变态势、具体时点等方面存在差异;港口体系结构由单核枢纽演变为双核枢纽,并有望形成三足鼎立新格局;(2)长三角地区港口规模分布逐步优化,等级结构不断趋于合理,港口体系基本满足位序-规模法则,但还没有达到理想状态;港口体系呈现分散化发展态势,集装箱技术的应用减缓了港口体系的分散化发展;(3)港口货物吞吐量与港口集装箱吞吐量的核密度曲线由多峰结构分别变为双峰结构和单峰结构,货物运输和集装箱运输均向协调态势发展。     

有色金属行业CO2排放估算方法研究

通过对国内外有色金属行业温室气体排放估算方法研究现状的分析,将联合国政府间气候变化专门委员会（IPCC）温室气体排放清单指南、国际有色行业协会和环境科学研究中的一些常用算法,总结归纳应用于有色金属行业温室气体的排放量估算,从估算方法和结果上分析各种方法的优缺点和使用条件。以原铝生产CO2排放估算为例,对有色金属温室气体排放进行实证分析,为有色金属行业温室气体排放估算提供参选方法,促进有色金属工业的节能减排。     

西藏林芝地区空气动力学阻抗估算模型适用性分析

空气动力学阻抗的准确估算是目前卫星反演地表显热通量的关键,为了准确反演藏东南地区的地表显热通量,利用2013年6月10日西藏林芝地区的草地、麦田、河滩、林地阴坡和阳坡5种下垫面的边界层观测数据,分析常用的Thom_1975,Thom_1977和Choudhury空气动力学阻抗估算模型的适应性。结果表明:林地阴坡Choudhury模型估算值与涡动相关测量的结果有较好的一致性,其他下垫面建议采用Thom(1975)模型。     

Kriging and Bilinear Methods for Estimating Spatial Pattern of Atmospheric Pollutants

Two statistical methods to reconstruct the spatial pattern ofenvironmental data are compared: the Kriging and the Bilinear.The comparison is performed by evaluating two differentcharacteristics of the methods: the interpolation and the estimation. The Kriging method is demonstrated to be better thanthe Bilinear regarding all the statistics studied, although thedifferences are not very significant. Especially, the Kriging ismore efficient than the Bilinear in the reconstruction of peakvalues and it does not extrapolate local trends. The methods areapplied to a set of environmental data measured in an urban area.     

地震灾害损失评估

回顾了我国地震灾害损失评估的发展与现状,介绍了地震灾害损失评估的内容、方法和步骤,探讨了地震灾害损失评估中需要进一步研究的若干问题。