采卤对接井施工工艺的工程实践

以江西九二盐业403-404采卤对接井组的施工工程为案例,系统介绍了井区地质情况、钻探施工情况;总结了大口径取心工具的优点,螺杆定向钻进施工工艺及攻克技术难点。     

粗糙集理论进行遥感图像监督分类的样本质量评价的研究

In the supervised classification process of remotely sensed imagery, the quantity of samples is one of the important factors affecting the accuracy of the image classification as well as the keys used to evaluate the image classification. In general, the samples are acquired on the basis of prior knowledge, experience and higher resolution images. With the same size of samples and the same sampling model, several sets of training sample data can be obtained. In such sets, which set reflects perfect spectral characteristics and ensure the accuracy of the classification can be known only after the accuracy of the classification has been assessed. So, before classification, it would be a meaningful research to measure and assess the quality of samples for guiding and optimizing the consequent classification process. Then, based on the rough set, a new measuring index for the sample quality is proposed. The experiment data is the Landsat TM imagery of the Chinese Yellow River Delta on August 8th, 1999. The experiment compares the Bhattacharrya distance matrices and purity index zl and △x based on rough set theory of 5 sample data and also analyzes its effect on sample quality.     

中药资源地理国情监测工具集设计与实现

目前第四次全国中药资源普查试点工作采集了大量的成果数据,并且成果数据与地理空间位置之间存在天然的联系。本文以中药资源数据的空间属性作为出发点,在中药资源普查成果数据和已有地理国情监测数据的基础上,建立了基础地理数据库、专题地理数据库和中药资源数据库,设计并实现了能够进行中药资源专题分析计算的地理工具集。最后,基于B/S架构完成了中药资源地理国情监测技术平台的构建,验证了地理工具集设计思路的正确性。     

粗糙神经网络在森林火灾预警中的应用

利用神经网络和粗糙集处理不确定性问题的优势，提出一种粗糙集结合神经网络进行森林火灾预测模型。通过与传统预测模型相比较，证明了该方法的有效性。     

含有集约束向量极值问题的最优性条件

在序线性拓扑空间里研究了含有集约束向量极值问题的最优性条件,并建立了充分性和必要性条件.     

双轴应力下非贯通节理岩体压缩损伤本构模型

针对目前节理岩体损伤变量定义中大多仅考虑节理长度、倾角等几何性质,而未考虑节理抗剪强度等力学性质的不足,基于断裂力学中的由于单个节理存在引起的附加应变能增量与损伤力学中的损伤应变能释放量相关联的观点,推导出了在双轴应力下含单条非贯通闭合节理岩体的损伤变量计算公式,并根据断裂力学理论对双轴压缩荷载下的单个节理尖端应力强度因子计算方法进行了研究,得出了应力强度因子KⅠ、KⅡ的计算公式;同时考虑多节理间的相互作用,给出了单组单排及单组多排非贯通节理尖端应力强度因子计算公式,由此建立了相应的节理岩体双轴压缩损伤本构模型,并利用该模型进行了相应的算例分析。结果表明：对含单条非贯通闭合节理的岩体而言,当节理倾角小于其内摩擦角时,岩体强度与完整岩石相同,岩体损伤为0,而后随着节理倾角增加,岩体强度、损伤随节理倾角的变化分别呈开口向上及向下的抛物线,当节理倾角约为60°时,岩体损伤最大,强度最低。随着节理长度增加,岩体损伤增加,而随着节理内摩擦角的增加,岩体损伤则减小;对含单组单排非贯通闭合节理的岩体而言,当节理总长度一定时,随着单条节理长度的减小及节理条数的增加,岩体损伤则逐渐减小,但其减小幅度与节理条数并不呈线性关系。     

Coastal habitat degradation and green sea turtle diets in Southeastern Brazil

To show the influence of coastal habitat degradation on the availability of food for green turtles (Chelonia mydas), we assessed the dietary preferences and macroalgae community at a feeding area in a highly urbanized region. The area showed low species richness and was classified as degraded. We examined stomach contents of 15 dead stranded turtles (CCL = 44.0 cm (SD 6.7 cm)). The diet was composed primarily of green algae Ulva spp. (83.6%). In contrast, the macroalgae community was dominated by the green alga Caulerpa mexicana. We found a selection for red algae, seagrass and Ulva spp., and avoidance for C. mexicana and brown alga Dictyopteris delicatula. The low diversity of available food items, possibly a result of environmental degradation, likely contributed to the low dietary diversity. The nutritional implications of this restricted diet are unclear.     

百色双套自动气象站雷击故障维修的方法

通过对百色双套自动气象站遇到历史罕见的强雷暴袭击出现故障维修,摸索出了检修双套新型自动站的通信、电源供应、主机HY3000、接口RS232、分采仪器等模块的方法,供同行借鉴.     

基于随机集合的非传统型有效波极值模型

The analysis and design of offshore structures necessitates the consideration of wave loads. Realistic modeling of wave loads is particularly important to ensure reliable performance of these structures. Among the available methods for the modeling of the extreme significant wave height on a statistical basis, the peak over threshold method has attracted most attention. This method employs Poisson process to character- ize time-varying properties in the parameters of an extreme value distribution. In this paper, the peak over threshold method is reviewed and extended to account for subjectivity in the modeling. The freedom in selecting the threshold and the time span to separate extremes from the original time series data is incorpo- rated as imprecision in the model. This leads to an extension from random variables to random sets in the probabilistic model for the extreme significant wave height. The extended model is also applied to different periods of the sampled data to evaluate the significance of the climatic conditions on the uncertainties of the parameters.     

Adaptive Predictive Inverse Control of Offshore Jacket Platform Based on Rough Neural Network

The offshore jacket platform is a complex and time-varying nonlinear system,which can be excited of harmful vibration by external loads.It is difficult to obtain an ideal control performance for passive control methods or traditional active control methods based on accurate mathematic model.In this paper,an adaptive inverse control method is proposed on the basis of novel rough neural networks (RNN) to control the harmful vibration of the offshore jacket platform,and the offshore jacket platform model is established by dynamic stiffness matrix (DSM) method.Benefited from the nonlinear processing ability of the neural networks and data interpretation ability of the rough set theory,RNN is utilized to identify the predictive inverse model of the offshore jacket platform system.Then the identified model is used as the adaptive predictive inverse controller to control the harmful vibration caused by wave and wind loads,and to deal with the delay problem caused by signal transmission in the control process.The numerical results show that the constructed novel RNN has advantages such as clear structure,fast training speed and strong error-tolerance ability,and the proposed method based on RNN can effectively control the harmfid vibration of the offshore jacket platform.