基于PCA-ELM模型的露采爆破振动对民房破坏的预测分析

针对露天采矿爆破振动对民房破坏的预测问题,采用主成分分析(PCA)和极限学习机(ELM)方法,选取爆破振幅、主频率、主频率持续时间、灰缝强度、砖墙面积率、房屋高度、屋盖形式、圈梁立柱、施工质量、场地条件10个主要影响因素。引入相关性分析在主成分分析过程中,对相关性高的指标进行降维,把得到的3个综合因子和爆破振幅、主频率、主频率持续时间、砖墙面积率作为输入变量,构建露天煤矿PCA-ELM预测模型。选取露天矿实际爆破过程中测量的100组数据作为模型训练样本,用另外20组数据作为测试样本进行预测。结果表明:对民房破坏影响因素中灰缝强度、房屋高度、屋盖形式、圈梁立柱、施工质量、场地条件之间具有较高的关联度。该模型处理高维数据时较传统的ELM算法具有预测精度高、稳定性好等特点,可准确预测爆破振动对民房的破坏程度,误判率为1/20。     

基于EMD-MFOA-ELM的瓦斯涌出量时变序列预测研究

为准确分析工作面绝对瓦斯涌出量的非平稳特征,实现瓦斯涌出量的准确预测,基于经验模态分解(EMD)、修正的果蝇优化算法(MFOA)和极限学习机(ELM)基本原理,构建瓦斯涌出量的EMD-MFOA-ELM多尺度时变预测模型。通过EMD将瓦斯涌出量时变序列进行深层次分解,获得多尺度本征模态函数(IMF);采用MFOA-ELM对各IMF时变序列建立动态预测模型,等权叠加各预测值,得到模型最终预测结果。以晋煤某矿瓦斯涌出量监测时序样本为例进行研究分析,结果表明:EMD能充分挖掘出监测数据隐含信息,有效降低数据复杂度;该模型预测相对误差为0.024 3%~0.651 0%,平均值仅为0.252 6%,预测精度和泛化能力高于未经EMD分解模型,能很好地适用于非平稳时变序列预测。     

城市化对长三角地区极端气温影响的时空分异研究

论文利用长三角地区65个气象站1960—2014年日最高、最低气温资料,分析并比较了大城市站、一般城市站和乡村站极端气温指数变化趋势以及城市化对大城市站和一般城市站各极端气温指数趋势变化的影响。结果表明：极端气温暖指日数明显增加,冷指日数明显减少,极值指数呈微弱上升趋势。暖指数城市站比乡村站增加趋势明显,冷指数城市站比乡村站减少趋势明显。除月最低气温极小值外,其他极值指数变化趋势在城市、乡村间差异较小。大城市站冰冻日数、霜冻日数、冷（暖）昼日数和月最低气温极小（大）值城市化影响显著,一般城市站冰冻日数、霜冻日数和月最低气温极小值城市化影响显著,城市化对极端气温影响明显的是长三角北部、江苏南部和浙东南的部分城市站点。冷昼日数城市化效应在冬季较明显,暖昼（夜）日数城市化效应在夏季较明显,春季、夏季、冬季城市化对极值指数的影响显著。     

Flooding in Texas: Examination of Temporal Changes and Impacts of Tropical Cyclones

Annual maximum peak discharge measurements from 62 stations with a record of at least 70 years are used to assess extreme flooding in Texas at the regional scale. This work focuses on examination of the validity of the stationarity assumption and on the impact of tropical cyclones (TCs) on the upper tail of the flood peak distribution. We assess the validity of the stationarity assumption by testing the records for abrupt and gradual changes. The presence of abrupt changes in the first two moments of the flood peak distribution is assessed using the Lombard test. We use the Mann‐Kendall test to examine the presence of monotonic trends. Results indicate that violations of the stationarity assumption are most commonly caused by abrupt changes, which are often associated with river regulation. We fit the time series of stationary flood records with the generalized extreme value distribution to investigate whether TCs control the upper tail of the flood peak distribution. Our results indicate that TCs play a diminished role in shaping the upper tail of the flood peak distribution compared with areas of the eastern United States subject to frequent TCs.     

Horizontal distribution and levels of heavy metals in the biggest snowstorm in a century in Shenyang, China

The horizontal distribution and levels of heavy metals in the biggest snowstorm in Shenyang since 1904 were investigated by analyzing 4 metals (As,Cd,Pb,and Cu) in a series of ultraclean samples collected from 17 sites distributed in different regions of the Shenyang area,China.The results showed that the concentrations of all the 4 heavy metals in snow from the industrial regions were high,up to 7.3 (As),2.2 (Cd),850.0 (Pb),and 0.197-20.2 (Cu)μg/kg,respectively.In the suburb,in contrast,their concentrat...     

风蚀扬尘抑尘剂效率测试方法与应用

风蚀扬尘抑尘剂是一种控制风蚀扬尘的有效措施,探讨使用便携式风洞(PI-SWERL)测试风蚀扬尘抑尘剂效率的方法,并对比国内外2种抑尘剂对风蚀扬尘PM2. 5的抑制效率,以研究喷洒方式、稀释倍数和风速对抑尘效率的影响.结果表明:①按照推荐的稀释倍数分别配置G和Enviroseal(ES)抑尘剂水溶液并测试,液滴喷洒方式对应的抑尘效率优于雾化喷洒方式,在17. 2 m·s~(-1)(相当于8级风)风速时G抑尘剂效率(99. 5%)优于ES抑尘剂(94. 0%)和水(77. 5%);②对稀释倍数为50、100、150、200和400倍的G抑尘剂进行测试,在17. 2 m·s~(-1)风速时,抑尘效率分别为99. 7%、99. 5%、99. 7%、98. 1%和95. 9%,可根据抑尘效率变化拐点确定抑尘剂最佳成本效益稀释倍数;在13. 1～17. 2 m·s~(-1)风速范围内,抑尘效率随风速增加而增加.③使用便携式风洞测试风蚀扬尘抑尘剂效率的方法,可以量化抑尘剂对风蚀扬尘PM2. 5的抑制效率,建议对风蚀扬尘抑尘剂开展抑尘有效期和环境友好性测试.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.     

极端温度下帐篷内部热环境适应性实验及模拟研究*

为揭示民用救灾帐篷热环境适应性变化规律,通过大尺度环境气候舱构建高温与低温环境,采用Ansys Fluent商用软件代码进行仿真验证,并对帐篷蓬围结构和内部热环境分布变化规律进行实验与数值模拟。研究结果表明:使用大尺度环境舱直接进行模拟帐篷内外热环境变化可行,其内部热环境变化规律与实验基本一致;帐篷特殊的篷围结构导致高温环境下帐篷内部温度高于外界,帐内人员头部和脚部温差可达5 ℃,低温环境下帐篷同一高度横向区域温度对称分布,在中心区域温度较低,边缘和中心温差近8 ℃。     

基于链式多重插补的WOA-ELM煤与瓦斯突出预测模型*

为了提高缺失数据下煤与瓦斯突出预测准确率,提出1种基于链式支持向量机多重插补（MICE_SVM）的鲸鱼优化算法（WOA）-极限学习机（ELM）预测模型,以淮南朱集矿区为例,选取5个煤与瓦斯突出影响指标作为模型特征,采用提出的MICE_SVM算法插补突出事故数据中缺失值,利用WOA优选ELM输入层权值及隐含层阈值,构建煤与瓦斯突出预测模型,将插补后数据用于WOA-ELM模型的训练与测试,并与其他模型的预测效果对比。研究结果表明:MICE_SVM插补前、后的有突出数据预测准确率分别为83.02%,90.41%,MICE_SVM显著提高了有突出预测准确率,对无突出和整体的预测准确率提高不明显;数据插补后WOA优化ELM对无突出、有突出和整体的预测准确率分别为97.94%,96.25%,96.48%,较优化前分别提高了5.79%,5.84%,5.55%,数据插补后WOA-ELM为最佳预测模型。     

UNCERTAINTY OF EXTREME FLOOD ESTIMATES INCORPRATING HISTORICAL DATA1

ABSTRACT: The ability to predict extreme floods is an important part of the planning process for any water project for which failure will be very costly. The length of a gage record available for use in estimating extreme flows is generally much shorter than the recurrence interval of the desired flows, resulting in estimates having a high degree of uncertainty. Maximum likelihood estimators of the parameters of the three parameter lognormal (3PLN) distribution, which make use of historical data, are presented. A Monte Carlo study of extreme flows estimated from samples drawn from three hypothetical 3PLN populations showed that inclusion of historical flows with the gage record reduced the bias and variance of extreme flow estimates. Asymptotic theory approximations of parameter variances and covariances calculated using the second and mixed partial derivatives of the log likelihood function agreed well with Monte Carlo results. First order approximations of the standard deviations of the extreme flow estimates did not agree with the Monte Carlo results. An alternative method for calculating those standard deviations, the “asymptotic simulation” method, is described. The standard deviations calculated by asymptotic simulation agree well with the Monte Carlo results.