Health risk analysis of volcanic SO<Subscript>2</Subscript> hazard on Vulcano Island (Italy)

Since the last eruption of the Fossa crater in 1888–1890, intense volcanic degassing has been remaining on Vulcano Island of Sicily (Italy). Toxic sulfur dioxide (SO₂) of the solfataric action in this area represents, when inhaled, a permanent natural hazard harming humans. Approximately 500 permanent residents live and 15,000 tourists visit during the summer time the Porto village in the North of Vulcano Island. A cross-disciplinary fuzzy logic risk assessment has been conducted to evaluate health risks of human individuals exposed to higher SO₂-concentrations C over certain exposure times t. The simple approach, based on fuzzy set theory, explains health risks semantically by words rather than by numbers. Advantages of this approach are, first, experts, non-experts, decision makers, or the public are able to understand and communicate risk degrees by words without using numbers. Second, in comparison to other risk definitions, the risk is not equal to the vulnerability; it is based on the hazard (SO₂-gas clouds) and vulnerability (health effects) in combination. Third, risk levels can be still estimated even when limited or no statistical information is available, e.g., high SO₂-concentrations or long exposure times. Moreover, human health risks were determined for C−t-scenarios based on threshold values of the European Union and the World Health Organization. Independently, two additional methods were used to determine the proportions of the population who are exposed to levels of SO₂ at which health effects may be expected and also safety zones for civil protection around the degassing fields. In conclusion, SO₂-gas concentrations in many parts of Vulcano Island go beyond the proclaimed alert threshold of the European Union and the World Health Organization. For example, the results show that sensitive individuals, such as asthmatics, young children, or elderly people, should not be exposed at any time to the degassing areas in Porto di Levante and at the NE-rim of the Fossa crater. In contrast, healthy non-sensitive individuals should be exposed less than 10 min to the SO₂-clouds at these degassing areas, while hiking on the crater rim.     

基于TS模型的结构振动模糊控制方法

将TS模糊控制模型用于结构振动控制中,提出了一种新型的模糊控制器。利用传统LQR控制算法确定TS模糊控制器的参数,提出一种新的形成模糊控制规则的方法,克服了TS模糊控制器参数较多,规则难以确定的缺点;并结合一座三层钢框架模型,进行仿真分析,验证了提出的方法的有效性。     

模糊分维及其在地震研究中的某些应用

在模糊集理论与分形理论的基础上,引进了模糊分维的概念;给出了模湖容量维D₀与模糊关联维D₂的定义与确定方法;讨论了模糊分维与常用的分维（清晰分维）的关系.给出了模糊分维在地震研究中的应用结果: 1.根据模糊容量维D₀随时间的上升趋势变化,可以划分出大地震活动的高潮期;由模糊容量维D₀与模糊关联维D₂随时间变化的曲线,可以分析识别大地震前的中长期前兆异常. 2.根据模糊容量维D₀随空间和时间的变化,可以划分出未来大震所在的地区,并可发现大震前数年D₀呈现增大或减小的趋势. 3.根据前兆数据的模糊时间分维D₀随时间的变化,可以发现大地震的短期前兆异常.     

模糊分维理论在地下流体资料分析中的应用

本文采用模糊集理论与分形理论相结合的模糊分维方法,计算了聊城１井水氡和豫０１井水位动态资料,发现在１９８１年河北宁晋Ｍｓ５．８,１９８３年山东菏泽Ｍｓ５．９和１９８５年河北任县Ｍｓ５．０地震前出现了明显的降维特征。选出了两台项的模糊分维基值为０．６０和０．７５。分析结果认为,模糊分维值反映了地震前兆时序观测资料的结构变化特征,具有一定物理意义。做为地下流体前兆观测资料提取地震异常信息的新方法,有一     

大同-阳高地震水位异常的模糊识别与预报

采用模糊数学从属函数和异常系列方法，以大同－阳高地震为例，对强震发生的时间与地点预测进行研究。结果表明：模糊数学从属函数方法是提取水位异常的较好方法。强震发生前在一定区域内，水位群体异常在不同时间尺度上显示出增长和加速变化图象，这种图象可作为预报强震发生时间的标志。水位变化值异常的集中分布区与水位异常井位置在空间呈两组条带展布时，两组条带交汇地区可作为预报强震发生地点的标志     

Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering

Changing climatic conditions contribute to a time varying nature of hydrological responses over different temporal scales. The temporal dynamics of hydrological systems bring uncertainties into hydrological simulation which are different to uncertainties from spatial heterogeneity of soil and land use. This study develops a new approach to improve the calibration of hydrological based on hydroclimatic similarities. Six climatic indexes are integrated using Principal Component Analysis and Fuzzy C-mean Clustering methods to transform hydrological years into hydroclimatic periods. Parameter sets of SWAT model are calibrated independently for each period and used together to generate continuous simulation for a prairie watershed in southern Canada. Results indicate that the multi-period model exhibits comprehensive advantages over the traditional single-period model under various flow conditions. The simulation ability of the model is improved through using period-specific parameter sets in fitting the observations to compensate for deficiencies in the model structure or input data.     

Fuzzy inference system for identification of geological stratigraphy off Prydz Bay, East Antarctica

The analysis of well logging data plays key role in the exploration and development of hydrocarbon reservoirs. Various well log parameters such as porosity, gamma ray, density, transit time and resistivity, help in classification of strata and estimation of the physical, electrical and acoustical properties of the subsurface lithology. Strong and conspicuous changes in some of the log parameters associated with any particular geological stratigraphy formation are function of its composition, physical properties that help in classification. However some substrata show moderate values in respective log parameters and make difficult to identify the kind of strata, if we go by the standard variability ranges of any log parameters and visual inspection. The complexity increases further with more number of sensors involved. An attempt is made to identify the kinds of stratigraphy from well logs over Prydz bay basin, East Antarctica using fuzzy inference system. A model is built based on few data sets of known stratigraphy and further the network model is used as test model to infer the lithology of a borehole from their geophysical logs, not used in simulation. Initially the fuzzy based algorithm is trained, validated and tested on well log data and finally identifies the formation lithology of a hydrocarbon reservoir system of study area. The effectiveness of this technique is demonstrated by the analysis of the results for actual lithologs and coring data of ODP Leg 188. The fuzzy results show that the training performance equals to 82.95% while the prediction ability is 87.69%. The fuzzy results are very encouraging and the model is able to decipher even thin layer seams and other strata from geophysical logs. The result provides the significant sand formation of depth range 316.0- 341.0 m, where core recovery is incomplete.     

日照茶树种植区典型茶园的土壤肥力状况评价

通过野外采样和室内测定,以日照茶树种植区3个典型茶园为研究对象,每个茶园分别取鸠坑、黄山群体、福鼎大白各3个品种。最终取得9种茶样生长地的土样,研究分析土样的pH。有机质,全N,P,K,有效N,P,K等指标的土壤养分含量状况,并以此为评价指标,运用模糊综合评判法,对3个茶园的土壤肥力质量进行了综合评价。结果表明,茶园肥力综合水平为北垛春〉碧波山庄〉北叶青i茶园土壤总体上,pH值较适中,有机质含量很缺乏,全N含量偏低,全P含量中等,全K含量较高,有效N含量很缺乏,有效P含量非常丰富,有效K含量中等,并据此提出了关于该地区3个典型茶园今后合理施肥的一些建议。     

模糊数学在岩质边坡稳定性分析中的应用

模糊评判法作为一种评价边坡稳定性方法,其关键在于能否准确地建立评价模型,是否能准确建立模型的重点在于隶属度与各评价因子权重的确定。在实际工程中,几乎所有研究者都是采用专家打分法来定权重。虽然这一方法应用广泛,但是主观性太强,不够客观合理。采用判断矩阵分析法来确定评价因子的权重,用二级模糊评判对某工程实例进行计算分析,结果表明用该法确定权重简便,亦能较好反映边坡所处状态。     

秦岭特长隧道涌水量的预测研究

论述了模糊聚类理论用于隧道涌水量预测的基本思路与方法, 提出了影响隧道涌水量的主要因素及其量化公式, 并以秦岭特长隧道 (Ⅱ线)为对象, 预测出其涌水量介于 1.0~ 3.0m³/d·m之间, 与该隧道开挖后的实际涌水量 2.07m³/d·m基本吻合, 从而证明了用该方法进行预测的合理性。