Scenario derivation and consequence evaluation of dust explosion accident based on dynamic Bayesian network

In order to clarify the correlation between the evolution path of dust explosion accidents and emergency decision-making, and to accurately predict the disaster damage levels of various disaster bearing bodies. This paper extracts 56 key scenario elements from four aspects, namely state, answer, goal and environment, based on the analysis of typical dust explosion accident cases. At the same time, a general scenario evolution path of dust explosion accident is constructed. Using fuzzy number set theory and dynamic Bayes joint probability model, the accurate solution of scenario state probability was realized. With the help of accident cases and dynamic Bayes approach, the dust explosion consequence prediction index system and evaluation criteria were constructed, covering factors such as dust explosion intensity, casualties, direct economic losses, equipment damage, building damage, environmental damage and other factors. A polyethylene wax dust explosion accident in a city of China was used to verify the dust explosion accident scenario evolution model and consequences prediction model. The predicted results were in good agreement with the actual damage of various carriers of the accident, which indicated that the model could be used for dust explosion accident prediction and disaster loss prediction. The research results provided reference and technical support for the prediction of dust explosion accident evolution direction, emergency aid measures decision and deployment, disaster damage prediction and evaluation.     

Sparse regression for analyzing the development of foliar nutrient concentrations in coniferous trees

Analyzing and predicting the development of foliar nutrient concentrations are important and challenging tasks in environmental monitoring. This article presents how linear sparse regression models can be used to represent the relations between different foliar nutrient concentration measurements of coniferous trees in consecutive years. In the experiments the models proved to be capable of providing relatively good and reliable predictions of the development of foliage with a considerably small number of regressors. Two methods for estimating sparse models were compared to more conventional linear regression models. Differences in the prediction accuracies between the sparse and full models were minor, but the sparse models were found to highlight important dependencies between the nutrient measurements better than the other regression models. The use of sparse models is, therefore, advantageous in the analysis and interpretation of the development of foliar nutrient concentrations.     

城市生态系统的预测与综合评价的思想体系

本方针对国内外城市生态系统的研究,提出了一套预测一评价一对策的思想体系,并对其预测、评价方法作了初步理论探讨.     

基于神经网络的城市夜间环境监控与预测

因夜间天空亮度分布具有非线性变化特点,故引入神经网络算法,建立基于时间序列的夜天空亮度预测模型,夜天空亮度预测模型可为城市光污染防治提供评价依据.文章对神经网络的原理进行了论述,建立了基于时间序列预测模型.以测试数据为训练样本集,基于MATLAB(矩阵实验室,Matrix Laboratory的简称),采用改进的BP算法(误差反向传播算法)对网络进行学习训练,并对存在的误差进行了分析.基于时间序列BP神经网络的夜天空预测模型,当隐含层神经元数目为5,训练函数为L-M优化算法(trainlm)时,最大绝对误差可达到0.003 6 cd/m2,最大相对误差达到2.361 4%.结果表明,模型的运行结果与试验数据比较吻合,输出与目标矢量之间相关性也较好.     

亚运时段广州大气污染物来源数值模拟研究

利用嵌套网格空气质量预报模式系统(Nested Air Quality Prediction Model System,NAQPMS)研究2006年亚运时段广州的空气质量状况,同时结合污染源追踪方法,分析珠三角各城市的源排放对广州全市、广州二环以内市区、广州6个亚运加强观测站的污染物浓度贡献.结果表明,NAQPMS模式能较好地反映广州各污染物(NO2、SO2、PM10)浓度的变化;广州全市、广州市区、6个亚运加强观测站的污染物最主要来源于本地排放,而周边城市以东莞的贡献最大.3个源受体中,广州市区受本地排放的影响最显著,来自本地的NO2、SO2、PM10的月均贡献率分别为89.5%、75.4%、86.7%;东莞则对6个亚运加强观测站的影响最为突出,其NO2、SO2、PM10的月均贡献率达9.3%、23.8%、21.7%,而日最大贡献率高达19.3%、40.2%、48.7%.因此在大力削减广州本地污染排放的同时,对周边城市特别是东莞实施区域联防联控,将能有效改善亚运场馆附近的空气质量.     

Predicting reproduction rate of varroa

A single equation is derived to predict population-density effects on the reproduction rate of the honey bee parasite Varroa destructor Anderson and Trueman. This equation provides a simpler alternative to the approach currently used in the literature, and additionally corrects an anomaly in that approach. The method is then extended to the case of co-existing haplotypes of Varroa. It thus derives an equation used without proof for modelling biocontrol of Varroa, and examines the error caused by an approximation necessary for a closed form solution. Additionally a varroa population model incorporating the derived equation is described.     

水质灰色预测模型在VBA中的实现

灰色预测是环境污染预测应用相当广泛的方法。根据文献报道,基于Matlab和Excel实现灰色预测中存在着占用内存、单元格填埋计算公式等等的不足,因此提出了一种基于VBA在Excel下编写宏程序轻松实现灰色预测的方法,并将其运用到北海市地表水污染物预测。结果表明,本程序简短,操作方便,计算结果准确可靠,彻底把用户从繁琐的手工操作中解放出来。     

上海市城郊臭氧浓度变化分析及模拟预报

利用上海市普陀、南汇、淀山湖3个臭氧观测站2005年的臭氧小时观测资料,首先对市区和郊区的大气臭氧浓度的污染特征和变化情况进行了分析,结果表明,上海市郊区的臭氧浓度和污染水平高于市区,且臭氧浓度日变化在市区呈现明显的双峰现象,而郊区则是单峰型变化规律。然后运用基于统计学理论的最小二乘支持向量机（LSSVM）方法对3个站的日（24h）平均和白日（12h）平均以及日最大值臭氧浓度进行预测,得到较好的预报效果。     

陕西省关中,陕南地区初夏干旱特点及预测研究

应用1958～1995年38a6月份陕西省关中、陕南地区24站的降水资料，研究了关中、陕南6月份的降水特点；选取其中12站作为资料站，计算出关中、陕南6月份的降水指数f,研究了关中、陕南初夏（6月份）的干旱特点；就初夏干旱发生的高空500hPa环流形势与历年平均状况进行了对比分析，并对初夏干旱作了预测。