Data structures for three-dimensional spatial information systems in geology

Abstract

The accumulation of geological information in digital form, due to modern exploration methods, has introduced the possibility of applying geographical information system technology to the field of geology. To achieve the benefits in information management and in data analysis and interpretation, however, it will be necessary to develop spatial models and associated data structures which are specifically designed for working in three dimensions. Some progress in this direction has already been demonstrated, with the application of octree spatial subdivision techniques to the storage of uniform volume elements representing mineral properties. By imposing octree tessellations on more precisely-defined geometric data, such as triangulated surfaces and polygon line segments, it may now be possible to combine efficient spatial addressing with topologically-coded boundary representations of geological strata. The development of storage schemes capable of representing such geological boundary models at different scales poses a particular problem, a possible solution to which may be by means of hierarchical classification of the vertices of triangulated surfaces according to shape contribution.     

Assessment of sediment transport approaches for sand-bed rivers by means of machine learning

Abstract

The quantification of the sediment carrying capacity of a river is a difficult task that has received much attention. For sand-bed rivers especially, several sediment transport functions have appeared in the literature based on various concepts and approaches; however, since they present a significant discrepancy in their results, none of them has become universally accepted. This paper employs three machine learning techniques, namely artificial neural networks, symbolic regression based on genetic programming and an adaptive-network-based fuzzy inference system, for the derivation of sediment transport formulae for sand-bed rivers from field and laboratory flume data. For the determination of the input parameters, some of the most prominent fundamental approaches that govern the phenomenon, such as shear stress, stream power and unit stream power, are utilized and a comparison of their efficacy is provided. The results obtained from the machine learning techniques are superior to those of the commonly-used sediment transport formulae and it is shown that each of the input combinations tested has its own merit, as they produce similarly good results with respect to the data-driven technique employed.

Editor Z.W. Kundzewicz     

Comparative analysis of fuzzy inference systems for water consumption time series prediction

Two types of fuzzy inference systems (FIS) are used for predicting municipal water consumption time series. The FISs used include an adaptive neuro-fuzzy inference system (ANFIS) and a Mamdani fuzzy inference systems (MFIS). The prediction models are constructed based on the combination of the antecedent values of water consumptions. The performance of ANFIS and MFIS models in training and testing phases are compared with the observations and the best fit model is identified according to the selected performance criteria. The results demonstrated that the ANFIS model is superior to MFIS models and can be successfully applied for prediction of water consumption time series.     

基于钻孔数据的含断层地质体三维建模方法

提出了一种构建含断层地质体三维模型的新方法。该方法以广义三棱柱作为建模的基本体元,根据钻孔数据的特点和知识推理规则,进行断层等复杂地质构造的推理和自动建模,避免了不必要的人为干预,扩展了钻孔数据建模的适用范围和表现能力。最后,通过研究实例展示该方法的实际建模效果。      

前兆台站及观测测项的密度改正方法

介绍了使用MYCIN不精确推理模型生成发震可信度分布图、 可信度密度等值线图以及进行前兆测项的密度改正方法。 通过对1989年大同6.1级和1998年张北6.2级地震的震前异常进行推理和比较, 经过密度改正的可信度密度等值线图可以克服某些地区由于前兆测项密度较高而造成对地点判断的偏差, 从而对未来发震地区的判断起到较好的效果。     

基于交互多模型的水下目标跟踪方法

According to the requirements of real-time performance and reliability in underwater maneuvering target tracking as well as clarifying motion features of the underwater target, an interacting multiple model algorithm based on fuzzy logic inference （FIMM） is proposed. Maneuvering patterns of the target are represented by model sets, including the constant velocity model （CA）, the Singer mode~, and the nearly constant speed horizontal-turn model （HT） in FIMM technology. The simulation results show that compared to conventional IMM, the reliability and real-time performance of underwater target tracking can be improved by FIMM algorithm.     

龙卷风的风强分析与极值推断

本文采用1955－1997年影响盐城市的龙卷风资料,按富士达F等级定义龙卷风风强分类级别,对盐城市受袭击点的破坏程度进行风强分级,并分析各个时段龙卷风风强等级的频数。应用耿贝尔极值分布理论,对影响盐城市的龙卷风风速极值进行统计推断,获得1％风险度龙卷风风速极值,以及各种特定重视期间的极值。     

Model-free estimation from spatial samples: A reappraisal of classical sampling theory

A commonly held view among geostatisticians is that classical sampling theory is inapplicable to spatial sampling because spatial data are dependent, whereas classical sampling theory requires them to be independent. By comparing the assumptions and use of classical sampling theory with those of geostatistical theory, we conclude that this view is both false and unfortunate. In particular, estimates of spatial means based on classical sampling designs require fewer assumptions for their validity, and are therefore more robust, than those based on a geostatistical model.