大型基坑工程水平位移监测与预测结果分析

以银川大世界商务广场的基坑为例,介绍了大型基坑工程水平位移监测的实施方案,给出了水平位移监测方法的精度,并对监测成果进行了分析。在此基础上,分别用多项式拟合和时间序列分析模型两种方法进行建模,对基坑水平位移进行预测,结果表明,该基坑水平位移较小,在规范规定的要求之内,说明基坑是稳定的;时间序列分析模型的预测精度要高于多项式拟合模型的精度。     

年尺度地震预测模型的国际研究现状

对未来1年内发生强震的预测在做好备灾应急准备和防震减灾工作上具有重要的现实需求.为反映近年来国际上关于1年尺度地震预测模型研究的进展,本文系统地整理了地震的统计概率预测模型、物理预测模型和混合预测模型,并从方法原理、预测效能评价、部署应用等角度进行了梳理.研究表明,目前国际上发展的1年尺度地震预测模型及其效能评价使用的参考模型的总体数量较少、建模原理主要基于G-R关系等统计学基本定律,显示该领域在基础理论架构、关键技术体系上并未足够成熟,这可能与相应的地震发生机理解释尚不完善、建立数理化的预测模型尚有困难等因素有关.     

New-type urbanization in China: Predicted trends and investment demand for 2015–2030

The future development of new-type urbanization has drawn great attention from both the government and public alike. In this context, the present study had three related research aims. Firstly, it sought to predict the urbanization and population dynamics in China at both national and provincial levels for the period of 2015 to 2030. Secondly, on this basis, it sought to examine the spatial variation of urbanization given the predicted national urbanization rate of 70.12%. Thirdly, it sought to estimate and evaluate the national and provincial demands of investment in the development of new-type urbanization. The main conclusions from this study were as follows: (1) The population size and urbanization rate will reach 1.445 billion and 70.12%, respectively, from 2015 to 2030. (2) The demographic dividend will vanish when the population pressure reaches its maximum. During this period, there will be 70.16 million urban population born. The suburban population that becomes urbanized will be 316.7 million, and thus the net increase in urban population will reach 386 million. (3) Although the urbanization rate of every Chinese province will increase during 2015–2030, it will do so unequally, while differences in urbanization quality among provinces will also be substantial. In some provinces, moreover, the urbanization quality is not compatible with their eco-social development. (4) A total of 4,105,380 billion yuan is required to fund new-type urbanization and the investment demand for each province varies greatly; for example, Guangdong province requires the most funding, amounting to approximately 148 times that required by Tibet, the province in least need of funding. In the final part of this study, policy suggestions concerning the investment of the new-type urbanization are put forward and discussed.     

K 近邻非参数回归概率预报技术及其应用

针对参数回归技术制作概率预报存在拟合好、但预报结果不稳定的现象, 提出了用K近邻非参数回归技术制作概率预报的新途径。K 近邻非参数回归技术包括历史样本数据库、近邻子集生成和优化以及预报量估计4 个主要部分。利用该技术进行了单要素概率预报(主要包括云量和降水)和多维联合概率预报(降水、总云量、风速和气温)试验, 并对试验结果进行了检验。实例研究结果表明:该文所给出的计算方案预报稳定性好, 准确率较高,具有良好的业务应用价值。     

土体流变破坏时间的灰色预测模型

根据不同载荷条件下土体蠕变破坏的时间数据列,建立了土体流变破坏时间的灰色预测模型。该模型能根据土体在较高应力条件下的蠕变破坏时间预测其在较低应力水平条件下的蠕变破坏时间,可用于边坡破坏预测、岩土工程、岩土力学试验等领域。     

Experiments with the Improved Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation over South China

In recent work, three physical factors of the Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation (DSAEF_LTP model) have been introduced, namely, tropical cyclone (TC) track, TC landfall season, and TC intensity. In the present study, we set out to test the forecasting performance of the improved model with new similarity regions and ensemble forecast schemes added. Four experiments associated with the prediction of accumulated precipitation were conducted based on 47 landfalling TCs that occurred over South China during 2004-2018. The first experiment was designed as the DSAEF_LTP model with TC track, TC landfall season, and intensity (DSAEF_LTP-1). The other three experiments were based on the first experiment, but with new ensemble forecast schemes added (DSAEF_LTP-2), new similarity regions added (DSAEF_LTP-3), and both added (DSAEF_LTP- 4), respectively. Results showed that, after new similarity regions added into the model (DSAEF_LTP-3), the forecasting performance of the DSAEF_LTP model for heavy rainfall (accumulated precipitation ≥250 mm and ≥100 mm) improved, and the sum of the threat score (TS250 + TS100) increased by 4.44%. Although the forecasting performance of DSAEF_LTP-2 was the same as that of DSAEF_LTP-1, the forecasting performance was significantly improved and better than that of DSAEF_LTP-3 when the new ensemble schemes and similarity regions were added simultaneously (DSAEF_LTP-4), with the TS increasing by 25.36%. Moreover, the forecasting performance of the four experiments was compared with four operational numerical weather prediction models, and the comparison indicated that the DSAEF_LTP model showed advantages in predicting heavy rainfall. Finally, some issues associated with the experimental results and future improvements of the DSAEF_LTP model were discussed.     

用逐步回归预测棉铃虫发生期和发生量

收集了1973年至2000年的气象，农作物、棉铃虫虫害等196年因子，以运城、汾阳和临汾为山西省代表站，利用最优二分割法把发生量分为10级，5级和不分级3种情况；使用逐步回归计算了219个模型，从中选出27个棉铃虫二、三代发生期，发生量最优模型，在农气服务中应用，预报准确率为95％，效果良好。     

时间尺度重构EEMD-GRNN改进模型预测PM2.5的研究

合理构建PM_2.5浓度预测模型是科学、准确地预测PM_2.5浓度变化的关键。传统PM_2.5预测EEMD-GRNN模型具有较好的预测精度,但是存在过于关注研究数据本身而忽略其物理意义的不足。本研究基于南京市2014-2017年PM_2.5浓度时间序列数据,分析PM_2.5浓度多尺度变化特征及其对气象因子和大气污染因子的尺度响应,基于时间尺度重构进行EEMD-GRNN模型的改进与实证研究。南京市样本数据PM_2.5浓度变化表现为明显的天际尺度和月际尺度,从重构尺度（天际、月际）构建GRNN模型更具有现实意义;同时,PM_2.5对PM₁₀、NO₂、O₃、RH、MinT等因子存在多尺度响应效应,以其作为GRNN模型中的输入变量更具有时间序列上的解释意义。改进后的EEMD-GRNN模型具有更高的PM_2.5浓度预测精度,MAE、MAPE、RMSE和R²分别为6.17、18.41%、8.32和0.95,而传统EEMD-GRNN模型的模型有效性检验结果分别为8.37、27.56%、11.56、0.91。对于高浓度天（PM_2.5浓度大于100 μg/m³）的预测,改进模型更是全面优于传统EEMD-GRNN模型,MAPE为12.02%,相较于传统模型提高了9.03%。     

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斜坡地质灾害气象预报预警空间数据库的设计与建立

斜坡地质灾害的频发常常带来重大的经济损失,尤其是降雨诱发的斜坡地质灾害问题日益严重.鉴于传统数据库不能有效地管理空间数据的局限性,采用ArcSDE Geodatabase和SQL Server空间数据库技术有利于对斜坡地质灾害气象预报预警的各种空间数据进行高效、统一、科学地管理.从数据准备、空间数据库的设计、空间数据库的建立三大方面介绍了斜坡地质灾害气象预报预警空间数据库的设计与建立;最后以云南省怒江州为例,对该数据库进行实例验证,充分地论证了该数据库具有一定的可行性.研究成果可为斜坡地质灾害气象预报预警和防治提供科学的依据.