模糊马尔可夫预测法在空气质量评价中的应用

将模糊综合评价及马尔可夫链同时运用到空气质量的评价中,可克服大气环境系统所固有的模糊性及随机性。通过1994—1998年芜湖市大气环境监测数据计算表明：不仅预测结果准确,而且由于应用了模糊数学方法,使得结果较为可信,且整个过程计算简单,是一种较适合的方法。     

Permeability heterogeneity in bioturbated sediments and implications for waterflooding of tight-oil reservoirs,Cardium Formation,Pembina Field,Alberta, Canada

Bioturbated sediments recording distal expressions of paralic depositional environments are increasingly being exploited for hydrocarbons in the super-giant Pembina Field (Cardium Formation), Alberta, Canada. These strata were previously considered unproductive due to limited vertical and horizontal connectivity between permeable beds. In these “tight oil” plays (0.1–10 mD), pressure decay profile permeametry (micropermeability) data indicate that sand-filled burrows provide vertical permeable pathways between bioturbated and parallel-laminated sandstone beds in the central, northeast and northwest parts of the field. This relationship enables the economic exploitation of hydrocarbons via horizontal drilling and multi-stage hydraulic fracturing. As the exploitation of bioturbated strata progresses in the Pembina Field, additional primary targets are being sought out, and horizontal waterflooding is being considered in areas where horizontal wells exist. Proximal to historical produced conventional targets, reservoir analyses indicate that areas where the bioturbated facies average permeability lies between 0.35 mD and 0.85 mD and sandstone isopach thicknesses are between 0.25 m and 2.5 m should be targeted in east-central Pembina.Micropermeability values enable correlation of bulk permeability from plugs and full-diameter samples to the heterogeneous permeability distributions in intensely bioturbated strata. Bulk and micropermeability data are graphically compared, and permeability distributions are mapped across the field. Using isopach thickness of bioturbated facies, production data, and permeability data, “sweet spots” are identified for placement of effective waterfloods.Production information for recently drilled horizontal wells in the Pembina Field demonstrate that bioturbated muddy sandstones and sandy mudstones in paralic environments can be economically exploited when sand-filled burrows provide connectivity between sand beds. However, well performance within these poorly understood unconventional tight oil plays can better be predicted with an in-depth characterization of their facies and complex permeability heterogeneities. Based on our results, it is clear that micropermeability analysis can be effectively employed to differentiate between economic and sub-economic plays, identify areas with high effective permeability, and high-grade areas for enhanced oil recovery schemes.     

Drought characterization: a probabilistic approach

Using the alternative renewable process and run theory, this study investigates the distribution of drought interval time, mean drought interarrival time, joint probability density function and transition probabilities of drought events in the Kansabati River basin in India. The standardized precipitation index series is employed in the investigation. The time interval of SPI is found to have a significant effect of the probabilistic characteristics of drought.     

Simulating hourly rainfall occurrence within an equatorial rainforest,Borneo Island / Simulation de l'occurrence de pluie horaire au sein de la forêt équatoriale,Ile de Bornéo

Abstract

The ability to simulate characteristics of the diurnal cycle of rainfall occurrence, and its evolution over the seasons is important to the forecasting of hydrological impacts resulting from land-use and climate changes within the humid tropics. This stochastic modelling study uses a generalized linear model (GLM) solution to second-order Markov chain models, as these discrete models are better at describing binary occurrence processes on an hourly time-scale than continuous-time approaches such as stochastic state-space models. We show that transition probabilities derived by the Markov chain method need to be time-varying rather than stationary to simulate the evolution of the diurnal cycle of rainfall occurrence over a Southeast Asian monsoon sequence. The conceptual and pragmatic links between discrete diurnal processes and continuous processes occurring over seasonal periods are thereby simulated within the same model.     

How do machine learning techniques help in increasing accuracy of landslide susceptibility maps?

Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/or semi-mountainous areas.Previous studies of landslide susceptibility mapping conducted near this road using statistical and expert methods have yielded ordinary results.In this research,we are interested in how do machine learning techniques help in increasing accuracy of landslide susceptibility maps in the vicinity of the A1 Highway corridor.To do this,an important section at Ain Bouziane(NE,Algeria) is chosen as a case study to evaluate the landslide susceptibility using three different machine learning methods,namely,random forest(RF),support vector machine(SVM),and boosted regression tree(BRT).First,an inventory map and nine input factors were prepared for landslide susceptibility mapping(LSM) analyses.The three models were constructed to find the most susceptible areas to this phenomenon.The results were assessed by calculating the receiver operating characteristic(ROC) curve,the standard error(Std.error),and the confidence interval(CI) at 95%.The RF model reached the highest predictive accuracy(AUC=97.2%) comparatively to the other models.The outcomes of this research proved that the obtained machine learning models had the ability to predict future landslide locations in this important road section.In addition,their application gives an improvement of the accuracy of LSMs near the road corridor.The machine learning models may become an important prediction tool that will identify landslide alleviation actions.     

Texture Segmentation Based on Image Model and Neural Network

INTRODUCTIoNImagetextureanalysisisanimportantpartofresearchin-tocomputervision.Forobjectidentificationandunderstand-ing,textureanalysisisthebasisoftheresearchwork.Ingeneral,texturecanberegardedasakindofstructurethatconsistsofmanytextureelementsorpatternswhicharemoreorlesssimilar,i.e.,primitivesthatformtexturesandspatialdependenceorinteractionbetweentheprimitives.Ex-tensiveresearchhasbeendoneintextureanalysis,andrefer-ence(Haralick,l979)hasmadeathoroughsurvey.Amongthesetextureanalysismetho…     

面向估计性能的双通道带宽分配策略研究

本文主要研究了面向估计性能的双通道带宽分配策略问题.为了减小网络化控制系统中时滞现象对信号传输的影响,将系统建模为Markov跳变时滞系统.采用双通道传输策略,提升数据到达率,减少数据包的丢失.考虑到信道容量的有限性不利于大量数据的高效传输,将有限的带宽灵活地分配于两个通道,使得信道容量得到充分利用.在此基础上,本文提出了面向估计性能的双通道带宽分配策略,设计了双通道量化传输方案以及状态估计器,推导出了时变估计误差系统满足H_∞性能的充分条件,并得出估计器增益矩阵设计方法,最后给出实例验证了所设计系统的有效性.     

从冰前风沙地貌初看普若岗日冰原的形成演变

野外实地考察和室内样品分析表明,位于普若岗日冰原西侧冰川前缘带的大片风沙地貌,直接发育在冰碛之上,并以冰碛为主要物质来源,与冰川运动和冰原环境具有密切的联系,是相关冰川和冰原形成演化过程的良好反映与记录.结合沙丘沉积序列中的沉积构造测量、粒度分析及腐殖质夹层的¹⁴C测年等结果,初步得出:普若岗日冰原至少形成于18kaBP;冰原降水可能主要来自西风降水;18kaBP以来,冰原在总体上处于收缩过程,在约108kaBP来,冰原西缘的零平衡线的年均水平退缩速率约为088～102m·a^-1,铅直升高速率约为24～32mm·a^-1。     

1998-2012年青藏高原TRMM 3B43降水数据的校准

运用1998-2012年青藏高原的TRMM 3B43降水数据以及气象台站实测降水数据,对比分析了青藏高原地区TRMM 3B43降水数据偏差分布规律。结果表明:(1) TRMM 3B43降水数据在青藏高原地区存在明显误差,特别是降水量大的地区和月份,偏差量较大。(2)青藏高原地区TRMM 3B43降水数据偏差分布与海拔、经纬度、降水量存在密切的关系。用偏差分布规律,加法修正法结合随机森林算法对青藏高原地区TRMM 3B43降水数据进行了校准。经过校准之后,数据精度得到显著提高,有效增加了数据的可用性,多年月平均数据决定系数R²最大可达到0.9(3、10月),最小也接近于0.5(12月),效率系数E均为正值,最大可达到90(3、10月);多年季平均和多年平均降水数据中除了第一季度结果稍差外(决定系数R²为0.58),其余数据校准效果均较好。     

Anwendung eines neuen Feldanalysenverfahrens zur Untersuchung der Stabilität von Arsen und seinen anorganischen Spezies in aquatischen Systemen

Using of a New Field Analysis Method to Investigate the Stability of Arsenic and its Inorganic Species in Aquatic Systems The stability of arsenic species in aquatic systems is limited by the possibilities of chemical and biochemical reactions. Redox reactions and bioalkylation lead to changes of the species ratios. In this work, the stability of As(III) and As(V) was examined at storage of distilled, de-ionized, and drinking water at different conditions (refrigerator/room temperature; daylight/darkness) and additions (sulfuric acid; ascorbic acid). The determination of these species was carried out by a modified spectrophotometric method, suitable for laboratory analysis as well as for field analysis. The results show that chemical oxidation and biochemical reduction can occur. Sulfuric acid is favourable for the stabilization of total arsenic and of the inorganic species.