基于PSO-SVM算法的环境监测数据异常检测和缺失补全

针对环境监测数据异常和数据缺失问题,提出了基于支持向量机的粒子群优化数据异常检测和缺失补全算法。利用粒子群优化算法选取较优的支持向量机训练参数组合,以此建立非线性的支持向量机模型,并利用结果模型对测得的真实数据拟合预测。以宁夏回族自治区某污水处理厂的污染物测量数据作为实验数据,结果表明,利用该算法预测数据的准确率可达97.977%,检测异常数据准确度高,缺失数据补全正确。     

Estimating marine biogeochemical rates of the carbonate pH system—A Kalman filter tested

Oxygen (O₂), nitrate (NO₃), dissolved inorganic carbon (DIC) or pCO₂, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying time-scales. Although these properties are increasingly being monitored at high frequency, they have not been extensively used for studying ecosystem dynamics. We test whether we can estimate time-evolving biogeochemical rates (e.g. primary production, respiration, calcification and carbonate dissolution, and nitrification) from synthetic high frequency time-series of O₂, NO₃, DIC, pCO₂, TA or pH. More specifically, a Kalman filter has been implemented in a very simplified biogeochemical model describing the dynamics of O₂, NO₃, DIC and TA and linking the concentration data to biogeochemical fluxes. Different sets of concentration data are assimilated and biogeochemical rates are estimated. The frequency of assimilation required to get acceptable results is investigated and is compared with the frequency of sampling in the field or in controlled experimental settings.Smoothing of the data to remove data noise before assimilation improves the estimation of the biogeochemical rates. The best estimated rates are obtained when assimilating O₂, NO₃ and TA although the assimilation of DIC instead of TA also gives satisfactory results. In case pH or pCO₂ is assimilated rather than DIC or TA, the linearization of the (now nonlinear) observation equation introduces perturbations and the Kalman filter behaves suboptimal. We conclude that, given the resolution of data required, the tool has potential to estimate biogeochemical rates of the carbonate system under controlled settings.     

气体、粉尘爆炸灾害及其安全技术

对可燃性气体、蒸汽、粉尘的爆炸特性及其抑爆、隔爆安全技术进行了系统的研究 ,并对常见的可燃性气体、蒸汽和粉尘的各种爆炸特性参数和气体抑爆安全技术参数进行了实验测定。根据实验测定结果得到的结论对这种可燃性物质的安全应用具有重要的参考价值     

近断层强震速度脉冲效应及连续梁桥减隔震特性分析

应用非线性时程分析的方法 ,对于减、隔震连续桥梁在近场地震作用下的有效性和响应特性 ,作了深入的研究。通过有代表性的脉冲型近场强震记录时程分析 ,提出了用速度脉冲峰值及其周期之积来表示速度脉冲能量的方法 ,计算表明近场地震速度脉冲波能近似表征地震动破坏能力的大小 ,它和桥梁结构承受的地震响应大体成正比例关系。铅芯橡胶隔震支座在近场地震作用下仍然适用 ,但对于个别脉冲型强震记录效果不够明显 ,支座参数有必要进行优化。     

Strength and tightness evaluation method for pipe flange connections considering thermal effects

The pipe flange connection is widely applied in chemical, power plants, petrochemical, offshore oil and gas industries, and its strength and tightness are significant for the safe operation. However, there are still no practical and applicable strength and tightness evaluation methods for pipe flange connections working in dramatically varying temperatures. This paper proposed an approach to evaluate the pipeline's strength and sealing performance considering thermal effects in actual operating conditions by combining the experimental measurement and thermostructural analysis. The critical thermodynamic parameters are identified through measured temperature data in operating conditions, and then these parameters are used in the thermostructural analysis to obtain the actual temperature and stress fields. Then, the strength and tightness in complex temperature cases can be evaluated accurately. The pipe flange connection of a liquefied natural gas (LNG) fueling station is analyzed to verify the presented method's effectiveness. This method applies to evaluating the pipeline's strength and tightness and can predict the pipeline's performances under extreme temperatures using the tested data within the measurement range and the corresponding thermostructural analysis. Furthermore, the work in this paper also provides a reference for the design and analysis of pipe flange connections working in complex temperature conditions.     

Effect of Widespread Agricultural Chemical Use on Butterfly Diversity across Turkish Provinces

Although agricultural intensification is thought to pose a significant threat to species, little is known about its role in driving biodiversity loss at regional scales. I assessed the effects of a major component of agricultural intensification, agricultural chemical use, and land‐cover and climatic variables on butterfly diversity across 81 provinces in Turkey, where agriculture is practiced extensively but with varying degrees of intensity. I determined butterfly species presence in each province from data on known butterfly distributions and calculated agricultural chemical use as the proportion of agricultural households that use chemical fertilizers and pesticides. I used constrained correspondence analyses and regression‐based multimodel inference to determine the effect of environmental variables on species composition and richness, respectively. The variation in butterfly species composition across the provinces was largely explained (78%) by the combination of agricultural chemical use, particularly pesticides, and climatic and land‐cover variables. Although overall butterfly richness was primarily explained by climatic and land‐cover variables, such as the area of natural vegetation cover, threatened butterfly richness and the relative number of threatened butterfly species decreased substantially as the proportion of agricultural households using pesticides increased. These findings suggest that widespread use of agricultural chemicals, or other components of agricultural intensification that may be collinear with pesticide use, pose an imminent threat to the biodiversity of Turkey. Accordingly, policies that mitigate agricultural intensification and promote low‐input farming practices are crucial for protecting threatened species from extinction in rapidly industrializing nations such as Turkey. Efectos del Uso Extensivo de Agroquímicos sobre la Diversidad de Mariposas en Provincias Turcas     

Pseudoreplication in Tropical Forests and the Resulting Effects on Biodiversity Conservation

Tropical forest ecosystems are threatened by habitat conversion and other anthropogenic actions. Timber production forests can augment the conservation value of primary forest reserves, but studies of logging effects often yield contradictory findings and thus inhibit efforts to develop clear conservation strategies. We hypothesized that much of this variability reflects a common methodological flaw, simple pseudoreplication, that confounds logging effects with preexisting spatial variation. We reviewed recent studies of the effects of logging on biodiversity in tropical forests (n = 77) and found that 68% were definitively pseudoreplicated while only 7% were definitively free of pseudoreplication. The remaining proportion could not be clearly categorized. In addition, we collected compositional data on 7 taxa in 24 primary forest research plots and systematically analyzed subsets of these plots to calculate the probability that a pseudoreplicated comparison would incorrectly identify a treatment effect. Rates of false inference (i.e., the spurious detection of a treatment effect) were >0.5 for 2 taxa, 0.3–0.5 for 2 taxa, and <0.3 for 3 taxa. Our findings demonstrate that tropical conservation strategies are being informed by a body of literature that is rife with unwarranted inferences. Addressing pseudoreplication is essential for accurately assessing biodiversity in logged forests, identifying the relative merits of specific management practices and landscape configurations, and effectively balancing conservation with timber production in tropical forests. Pseudoreplicación en Bosques Tropicales y Efectos Resultantes Sobre la Conservación de Biodiversidad     

Bayesian analysis under ordered functions of parameters

Ordered parameter problems arise in a wide variety of real world situations and are dealt with extensively in the literature. Traditional frequentist methods for dealing with these problems are rather complicated theoretically, especially when sample sizes are small. Bayesian methods are not widely used because high dimensional numerical integration is often required. However, Markov chain Monte Carlo methods provide alternatives to such numerical integration and also deal with ordered parameter problems in a straightforward manner. Little is known about the situation where functions of parameters are ordered. Such problems may seem to be of little practical concern initially, but one can readily see their importance in situations where ordering is placed on the means and variances of several normal or Gamma populations. For the Gamma distribution we will present real examples where we will analyze monthly precipitation data from San Francisco, California and Oakland Mills, Iowa. For the San Francisco data we will simultaneously order both monthly precipitation means and variances. For the Iowa data we will place ordering on seasonal average while still estimating monthly means. Our results show that we would obtain sharper, more accurate inference when order restrictions are employed.     

斜坡稳定性的二级模糊推断

根据对斜坡稳定性影响的大小,选取了七个主要因于,引用了山西明水河流域几个斜坡样点实测数据．应用模糊近似推论方法及信息分配原理,对斜坡稳定性进行了单因子灰色隶属度分析及综合二级模糊近似推论,该方法克服了传统单因子评价的弊端,能比较真实地反映实际,为布设护坡工程提供了理论依据。     

太湖水质指标相关性与富营养化特征分析

为研究太湖第一阶段治理水质富营养化的特征，根据1999年10月采样数据，对总磷、总氮等与富营养化相关的水质指标进行了统计分析。发现透明度与叶绿素a之间并未表现出显著的相关性，而在聚类图中，悬浮物与总磷、总氮显示出密切关系。指出农村面源仍是太湖中营养物质的重要来源。