基于引力搜索算法的分数阶变异时序回归GSA-TSGM(1,1)模型

为了利用分数阶累加算子在灰色短期预测中的高效性能,首次将分数阶累加算子引入变异时序回归模型以期取得更高的预测精度。主要方法如下：首先取湖北省链子崖某监测点1978—1987年的十年数据作为训练集并使用引力搜索算法确定最佳分数阶累加阶数,而1988—1993年的六年数据作为验证集验证提出的模型;其次对比了经典灰色模型GM(1,1)、分数阶累加灰色模型、变异时序回归模型TSGM(1,1)三种灰色模型。结果如下：首先修正了陈西江等人变异时序回归模型仿真时出现的错误,其次表明了相比于其他的模型,基于引力搜索算法的分数阶累加时序回归模型在进行灰色长期预测中具有较高的预测精度。因此,通过分数阶累加算子提高了灰色理论中长期预测模型的精度,为灰色长期预测提供了指导。     

岩石节理三维粗糙度各向异性表征新方法

针对传统二维节理面粗糙度表征方法的不足,提出一种新的岩石节理面三维粗糙度描述方法。首先,利用光学扫描系统得到节理表面点云数据并建立三维模型;运用改进的变异函数方法,提出一种新的基于正态分布模型参数的三维粗糙度(VA)方法;最后,运用新方法对花岗岩张拉型节理表面的粗糙特性进行分析。结果表明,提出的新方法能够反映节理面的起伏变化、频率和分形特征,并因此能描述出节理粗糙度的各向异性特性。     

Face detection based on skin color likelihood

We propose a face detection method based on skin color likelihood via a boosting algorithm which emphasizes skin color information while deemphasizing non-skin color information. A stochastic model is adapted to compute the similarity between a color region and the skin color. Both Haar-like features and Local Binary Pattern (LBP) features are utilized to build a cascaded classifier. The boosted classifier is implemented based on skin color emphasis to localize the face region from a color image. Based on our experiments, the proposed method shows good tolerance to face pose variation and complex background with significant improvements over classical boosting-based classifiers in terms of total error rate performance.     

Critical evaluation of coupling particle size distribution with the shrinking core model

The shrinking core model (SCM) is widely used to model fluid-solid reactions such as the leaching of metals from minerals. In most cases, however, the particle size distribution (PSD) of the solid material was disregarded. In this paper the erroneous shift in the control regime when neglecting PSD was quantified and the dependence of the shift on the coefficients of variation (CV) and the type of PSD was analysed. By coupling the SCM with a Gamma PSD, it was found that neglecting the PSD would shift the control regime from chemical reaction to inert/ash layer diffusion, when the CV was between 0.7 and 1.2. For a system controlled by liquid film diffusion, neglect of the PSD, would shift the control regime to chemical reaction when CV is between 0.3 and 0.7 or to inert/ash layer diffusion when CV is greater (0.9-1.5). It was therefore postulated that some researchers had unknowingly made invalid conclusions about the control regime due to the neglect of PSD. However, an inert/ash layer diffusion-controlled process was insensitive to the neglect of PSD. When CV<0.3, neglect of the PSD would not cause any erroneous shifts, irrespective of the control regime. Experimental data confirmed the observation. For a given CV, the deviation in the fraction reacted from the mono-PSD increases with CV and decreases with time. The maximum deviation, which occurs at the beginning, is about 10% with a gamma PSD of CV=0.3. The percent deviation is dependent of the type of PSDs. Gamma PSD gives the lowest deviation while Gaudin-Schuhmann results in the largest deviation (maxi. ∼19%, with CV=0.3) in the first half of dissolution process. Log-normal distribution gives a larger deviation than gamma but quickly approaches the latter with time. The deviation for Rosin-Rammler is between log-normal and Gaudin-Schuhmann. For systems with CV less than 0.3, the SCM can be fairly used without considering PSD. When CV is greater than 0.3, particularly in the early stage of a dissolution process with a PSD other than gamma, PSD should be included to avoid substantial errors.     

2016年长江第1号洪水预报及调度影响分析

通过分析2016长江第1号洪水的水雨情发展、洪水组成、水情预报、调度还原计算成果等,解析了该场洪水的暴雨洪水特性、预报对调度的支撑作用以及三峡水库调度对城陵矶河段水位的影响。分析表明：金沙江、乌江来水对第1号洪水起筑底作用,三峡区间洪水则为该场洪水造峰,三者最大1d洪量占三峡入库来水比率分别达26.1%,15.6%,38.1%;第1号洪水期间,水情预报为调度决策提供了长预见期、较高精度的前提支撑,78,54,30,6 h预见期的三峡入库洪峰预报误差分别仅为-20.0%,-10.0%,-4.0%,0;三峡水库在第1号洪水期间通过防洪调度将入库洪峰流量削峰38%,最大拦蓄洪量约29亿m3,削减莲花塘站洪峰水位0.39 m左右,避免了城陵矶河段出现超保证水位。     

潮汐双向流条件下丁坝水流特性研究

以长江口南支河段为原型,概化并建立水槽数学模型,研究径潮双向流条件下丁坝附近的水流结构。研究表明:丁坝一侧河岸,丁坝下游潮差远大于上游,在丁坝上游潮差小于对岸侧,下游潮差大于对岸侧;落潮时,丁坝回流区与壅水区长度大于涨潮,转流时刻,丁坝坝头附近流速相对较大;河床底部剪切应力变化在涨落急时刻最大,且落潮大于涨潮,转流时刻坝头及坝身迎水侧剪切应力增加明显。     

基于KPCA-PSO-SVM的径流预测研究

为提高径流预测模型的准确性与稳定性,对KPCA-PSO-SVM的径流预测方法进行了研究。在分析径流影响因素的基础上,利用核主成分分析(KPCA)法对径流影响因子进行非线性特征提取,获得主成分作为支持向量机(SVM)的输入变量,建立了径流预测SVM模型,其中模型参数通过粒子群算法(PSO)进行优化。模型建立后,以新疆伊犁河雅马渡站中长期径流预测为例进行分析。预测分析结果表明,在拟合和检验阶段模型的平均相对误差分别为0.77%和7.64%,与其他预测模型比较,基于KPCA-PSO-SVM方法建立的径流预测模型有较好的预测和泛化能力,是一种行之有效的中长期径流预测方法。     

昭通横江流域年径流预测

针对昭通横江由南到北贯穿昭通全境,水资源量丰富,但南北差异大,南部少、北部多的特点,根据流域内水文站实测年径流、大气环流指数、海温指数及其他指数等资料系列,采用多元回归分析法拟合1981—2010年径流,建立了预测模型,验证、预测分析了2011—2016年径流量。结果表明:干流控制站预测精度高于干流上段及支流代表站,水利工程建设等人类活动影响是导致出现这样结果的主要原因;多元回归分析在横江流域径流预测中具有一定的适应性,但因指标的差异及相关参数可获取性的差异,预测结果存在区域间、等级间的差别。     

城市径流总量控制指标分解及实现路径探索与实践

针对海绵城市径流总量控制目标,提出一种在城市规划体系中控制性详细规划和修建性详细规划阶段分解落实年径流总量控制率的方法。在控制性详细规划阶段分解径流总量控制指标时,分步骤先后确定各项低影响开发措施的面积率和下沉深度;在修建性详细规划阶段,配合径流总量控制指标分解结果,给出适宜的各项低影响开发措施的技术实施导则,以保证各单项指标的正确实施,并以某项目为例介绍了技术实施导则的构建方法。     

灞河流域气候因子对水沙变化的影响

利用灞河流域蓝田气象站和马渡王水文站1960—2012年的气象、水文实测资料,分析灞河流域气候及水沙变化规律,同时运用相关性分析、灰色关联分析、多元线性回归模型等多种方法探讨了该流域水沙变化与气候变化的关系。结果表明:灞河流域降雨量、蒸发量、径流量和输沙量皆呈显著下降趋势,而气温呈上升趋势;降雨量与水沙都有重要的相关关系,1960—1990年影响径流量的气候因子敏感度由大至小依次为降雨量、气温、蒸发量,而1991—2012年则为降雨量、蒸发量、气温,当气温和蒸发量不变时,降雨量每增加1 mm,两阶段的年径流量分别增加0.14亿m3和0.08亿m3;1960—2012年影响输沙量的气候因子敏感度由大至小依次为降雨量、气温、蒸发量,当气温和蒸发量不变时,降雨量每增加1 mm,年输沙量增加0.668万t。