观测数据时空密度对集合卡尔曼滤波计算精度的影响

集合卡尔曼滤波（EnKF）算法在地下水数据同化领域中的应用受到了越来越广泛的关注。作为同化系统的重要组成部分,观测数据的空间/时间密度的配置直接影响滤波运算结果。本文构造了一个理想二维地下水流算例考察空间/时间密度对传统EnKF和局域化EnKF的影响。研究结果表明：随着空间密度的增大,局域化EnKF运算精度增高,而传统EnKF运算精度无此改进倾向。总体趋势上时间密度增大使EnKF运算精度增高,但对不同数目的观测井方案,这种精度增高的幅度有所变化,观测井越多,增高越不明显。由此得出结论：局域化改进EnKF能够有效同化更多的观测井数据,给出更精确的结果;模拟初期水头变化波动较大,观测数据价值较高;在一定时间密度配置下,低空间密度局域化EnKF运算精度可以接近甚至超过高空间密度配置。     

The perception of assimilation in newly learned novel words.

The present study investigated the mechanisms underlying perceptual compensation for assimilation in novel words. During training, participants learned canonical versions of novel spoken words (e.g., decibot) presented in isolation. Following exposure to a second set of novel words the next day, participants carried out a phoneme monitoring task. Here, the novel words were presented with final alternations (e.g., decibop) in carrier sentences that either licensed assimilation (viable context: Our decibop behaved badly) or did not (unviable context: Our decibop does very well). Listeners had to monitor for the underlying form of the assimilated consonant (e.g., /t/ in decibop). Results showed more responses corresponding to the underlying form in viable than in unviable contexts. This viability effect was equivalent for novel words learned on the same day and on the previous day but was absent for unexposed control items. The processing difference between exposed and control novel words supports the idea that compensation for assimilation interacts with newly acquired phonological information and suggests that contextual compensation for assimilation is enhanced by lexical knowledge. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

社会比较对薪酬不公平感的心理作用机制

运用社会比较理论,分析了在组织内部影响薪酬不公平感的社会比较类型与评判内容;利用对比效应与同化效应,解释了薪酬不公平感的形成。在此基础上,探讨了人力资源管理中减少或克服人际攀比带来不良影响的途径。     

贺兰山小松山基性—超基性 杂岩体岩石地球化学特征

贺兰山小松山岩体的岩石地球化学研究表明,基性岩的Mg#为0.71～0.76,接近原生岩浆的值,超基性岩 的Mg#为0.80～0.89,具有岩浆早期堆晶的特征,稀土总量.REE为(13.03～82.66)×10-6;δ(Eu)为1.08～ 1.61,具弱正异常;(La/Yb)N为2.49～5.24,(Ce/Yb)N为3.01～4.97,配分曲线表现为轻稀土相对富集的右倾型。 微量元素配分曲线图表现为大离子亲石元素富集。岩石地球化学数据综合分析证明,该岩体产于板内拉张环境, 岩体形成过程中经历了岩浆分离结晶作用,后期发生了同化混染,岩体具有寻找铬-铜-镍型岩浆矿床的潜力。     

雷达联合雨量计估算区域降水量精度对比

提出了基于雷达测雨数据的R-G联合法,该法在原有雨量站实测降雨的基础上,引入了雷达测站得到的雷达数据.雨量站实测点雨量精度高,雷达站测的数据在空间上分布合理.R-G联合法结合雨量站和雷达两者的优点,得到面上分布合理并且精度高的降水数据.选择站网密度比较理想的湖北东部区域对各方法进行实际应用,通过与传统数据同化方法的对比分析研究,证明所提方法可明显提高数据同化精度.     

英语语音中的连读

连读是极常见的现象,当与讲英语的人交流时,如果你一个字一个字说。而不是连读.别人会不懂你说什么,同时你也听不懂别人说什么。     

数据同化框架下红外与可见光图像的可控融合

针对现有图像融合方法的规则不易根据融合图像的后续使用要求进行自适应调整,并且各种方法的优点不易综合的问题,提出一种数据同化框架下的基于粒子群优化(PSD)和差分进化(DE)算法的融合方法。该方法把比率低通金字塔变换作为数据同化系统的模型算子,把非下采样的Contourlet变换(NSCT,nonsubsampled contourlet transform)作为观测算子,根据后续处理对图像各个属性指标值的依赖程度构造目标函数,再利用PSD和DE的混合算法来优化目标函数从而获取合适的影像。两组实验从视觉效果和定量指标两方面验证了方法的有效性。     

基于消费者参考价格决策及用户黏性的售电套餐优化

在未来的电力零售市场,更多的售电企业为规避风险,提高市场占有率和持续性,有必要向拥有零售选择权的终端用户提供科学合理并具有竞争力的售电套餐,为此提出一种售电套餐设计优化的新思路。首先,考虑用户消费的偏好行为,引入分类同化系数建立消费者内部参考价格(IRP)决策模型,定义单个用户的黏性行为(或称为惰性行为),建立单个用户黏性函数。然后,建立用户决策矩阵反映群体用户对套餐的选择情况,建立基于用户黏性和决策矩阵的售电企业总效用目标函数,以固定费用和单位费用相结合的套餐结构为基础,以套餐价格为变量,对最优目标进行搜索。接着,采用交叉粒子群算法,将传统的搜索方式改进为以元胞数组为单位的种群多区域同时搜索。同时,利用对决策矩阵的两次修正模拟用户无偏好条件下的绝对理性消费和存在偏好条件下的非理性消费。最后进行算例分析,通过对比优化前后潜在用户对套餐的选择情况,验证了模型的可行性与优化效果。     

Development of a coupled land-atmosphere satellite data assimilation system for improved local atmospheric simulations

This study developed a coupled land-atmosphere satellite data assimilation system as a new physical downscaling approach, by coupling a mesoscale atmospheric model with a land data assimilation system (LDAS). The LDAS consists of a land surface scheme as the model operator, a radiative transfer model as the observation operator, and the simulated annealing method for minimizing the difference between the observed and simulated microwave brightness temperature. The atmospheric model produces forcing data for the LDAS, and the LDAS produces better initial surface conditions for the modelling system. This coupled system can take into account land surface heterogeneities through assimilating satellite data for a better precipitation prediction. To assess the effectiveness of the new system, 3-dimensional numerical experiments were carried out in a mesoscale area of the Tibetan Plateau during the wet monsoon season. The results show significant improvement compared with a no assimilation regional atmospheric model simply nested from the global model. The surface soil moisture content and its distribution from the assimilation system were more consistent to in situ observations. These better surface conditions affect the land-atmosphere interactions through convection systems and lead to better atmospheric predictability as confirmed by satellite-based cloud observations and in situ sounding observations. Through the use of satellite brightness temperature, the developed coupled land-atmosphere assimilation system has shown potential ability to provide better initial surface conditions and its inputs to the atmosphere and to improve physical downscaling through regional models.     

Assimilation of SPOT/VEGETATION NDVI data into a sahelian vegetation dynamics model

This paper presents a method to monitor the dynamics of herbaceous vegetation in the Sahel. The approach is based on the assimilation of Normalized Difference Vegetation Index (NDVI) data acquired by the VEGETATION instrument on board SPOT 4/5 into a simple sahelian vegetation dynamics model. The study region is located in the Gourma region of Mali. The vegetation dynamics model is coupled with a radiative transfer model (the SAIL model). First, it is checked that the coupled models allow for a realistic simulation of the seasonal and interannual variability of NDVI over three sampling sites from 1999 to 2004. The data assimilation scheme relies on a parameter identification technique based on an Evolution Strategies algorithm. The simulated above-ground herbage mass resulting from NDVI assimilation is then compared to ground measurements performed over 13 study sites during the period 1999-2004. The assimilation scheme performs well with 404 kg DM/ha of average error (n = 126 points) and a correlation coefficient of r = 0.80 (to be compared to the 463 kg DM/ha and r = 0.60 of the model performance without data assimilation). Finally, the sensitivity of the herbage mass model estimates to the quality of the meteorological forcing (rainfall and net radiation) is analyzed thanks to a stochastic approach.