基于BP人工神经网络的枯水径流预报方案研究

介绍了BP人工神经网络的桔水径流预报方法,编制了锦屏一级水电站枯水径流预报方案.根据枯水径流预报方案的预报精度评定成果,总结了应用BP人工神经网络进行枯水径流预报的特点.研究表明基于BP人工神经网络的枯水径流预报方案能够满足水文情报预报规范,具有较好的实用性和可行性.     

The sudden disappearance of a dark filament observed on October 26, 1989

We present H monochromatic and spectroscopic observations of the sudden disappearance of a dark filament located near the center of the solar disk on October 26, 1989. The event was not associated with the flare activity. The dark filament first disintegrated into two loop-like components, and then each component successively showed ascending motion with a velocity greater than 30 km s^–1. Comparison of the H pictures taken before and after the start of this event suggests that the dark filament was originally composed of two magnetic flux loops.     

基于MAPGIS的市政设施数据模型研究

本文主要介绍了市政基本设施的组成,提出了基于MAPGIS基本数据组织的市政设施数据模型,并讨论了市政设施数据模型的实现。从而,利用该数据组织模型可实现城市级的市政设施管理的综合集成与共享,提高市政设施管理和养护水平。     

基于GIS的油田数字化管道的实现

全国油田都在进行一场"数字油田"的革命,而数字化管道又是其中的一个重要环节.本文与油田实际相结合,基于MAPGIS进行二次开发,论述了数字化管道实现的基本理论.     

江西省九岭区地质灾害危险性区划

对九岭区地质灾害发育的基本特征及其地质环境条件进行了概述,并对其形成条件进行了相关性分析;通过对地质灾害发育的基本规律、控制因素、触发因素与地质灾害关系的分析,采用环境地质学原理,建立区域地质灾害空间预测模型,圈定九岭区地质灾害的危险性分区,为实时地质灾害时间预警预报圈定有效的空间靶区。预测单元采用规则的栅格(500m×500m),共14415个单元;评价指标主要包括地形地貌、工程地质岩类、地质构造、破坏地质环境人类工程活动等四大类26个因子;利用GIS技术,提取出相关的数据信息;信息量预测方程:Ii=-1.164X1-0.999X2-0.681X3 …… 0.203X25-0.135X26(其中X1、X2、X3、…X26取1或0,即某单元中存在某种因素时取1、否则取0),据此计算出各单元格的信息量;根据地质灾害危险性分区临界指标,确定单元格的地质灾害危险性等级;合并同类项,并考虑类似的地质、自然环境具有类似的地质灾害问题的原则,进行归并与单元边界线的修改,得出九岭区地质灾害危险性分区。     

Estimating the minimum in-stream flow requirements via wetted perimeter method based on curvature and slope techniques

Under the assumptions of triangular cross section channel and uniform stable flow, an analytical solution of the minimum ecological in-stream flow requirement (MEIFR) is deduced. Based on the analytical solution, the uncertainty of the wetted perimeter method is analyzed by comparing the two techniques for the determination of the critical point on the relationship curve between wetted perimeter, P and discharge, Q. It is clearly shown that the results of MEIFR based on curvature technique (corresponding to the maximum curvature) and slope technique (slope being 1) are significantly different. On the P-Q curve, the slope of the critical point with the maximum curvature is 0.39 and the MEIFR varied prominently with the change of the slope threshold. This indicates that if a certain value of the slope threshold is not available for slope technique, curvature technique may be a better choice. By applying the analytical solution of MEIFR in the losing rivers of the Western Route South-to-North Water Transfer Project in China, the MEIFR value via curvature technique is 2.5%-23.7% of the multi-year average annual discharge, while that for slope technique is 11%-105.7%. General conclusions would rely on the more detailed research for all kinds of cross-sections.     

吉林台爆破料应力应变关系的三轴试验研究

通过室内大型三轴实验，研究了吉林台水库爆破料在不同级配下的应力应变关系，得到了在一定击实功下爆破料的最大干密度随细料含量变化的规律，分析了爆破料在不同级配和不同围压下应力与应变的变化规律、轴向应变与体积应变的关系及抗剪强度变化特性．从微观的角度说明了变化规律产生的原因，得出爆破料的抗剪强度随级配的变化而变化的规律．     

山东省移动气象台通信网络系统

本文主要介绍移动气象台中的通信网络系统,包括网络的整体结构,各部分的功能与实现方式,及各种网络设备的软硬件配置等.     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.