Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

汾河流域水环境地理信息系统设计

该文结合汾河流域水环境地理信息系统设计的具体实践，论述了系统所采用的三层结构体系、设计的技术策略，重点对系统的功能特别是数据库设计和应用系统功能进行了详细的描述，是地理信息系统在水环境管理领域应用的有益探索。     

城市基准地价评估的容积率内涵及其修正系数的确定--以石家庄市为例

基淮地价评估是当前城市地价评估的主要形式。容积率既反映了土地的利用状况，同时也是影响地价的主要因素之一。该文阐述了容积率内涵，分析容积率与地价、环境的关系，探讨合理容积率的确定，以石家庄市为例，探索容积率修正系数确定的正确途径，避免在容积率概念、修正系数等问题上产生混淆。     

基于空间信息技术的城市应急救援联动系统研究

该文分析国内外城市现代救援体系及其发展趋势，对基于统一的空间信息基础设施平台分布式城市应急救援联动系统(体系结构与系统实现)的关键技术进行研究，以成都市城市应急救援联动系统为例，探讨了城市应急救援联动系统的构成、功能、业务流程、系统平台、用户界面等。     

智能交通系统中的公交车辆指挥调度体系结构

该文阐述公交智能指挥调度系统总体框架，结合智能交通系统ITS(Intelligent Transport Systems)对公交智能化调度的逻辑结构和物理结构要求，分析公交车辆智能化调度系统结构体系及其模型化，探讨智能调度策略和调度机理。根据该系统总体设计框架构思，了解系统各功能间的相互关系，优化公交车辆运营管理模式，以改善现有公交系统的管理水平以及运营效率，为公交指挥调度系统的完善、提高提供可靠技术基础。     

设备树在路灯AM/FM/GIS系统中的应用研究

该文提出了AM／FM／GIS中基于“设备树”的设备设施管理模式，运用“设备树”来组织路灯电力网络中的设备设施对象；阐述了如何从设备设施的物理模型抽象出具有树状层次结构的逻辑网络模型，并根据该逻辑模型设计相应的数据结构来构建“设备树”；并介绍了设备树在南京市路灯AM／FM／GIS系统中的设计与实现。     

东莞城市化过程中若干问题研究

改革开放以来，东莞市积极吸纳海外资本与技术，通过“三来一补”企业的快速发展，带动了非农产业和小城镇的迅速发展。然而，受我国分散的工业化和农村城市化政策体制的影响，在快速城市化过程中也暴露出很多值得关注的问题。该文基于实地考察与问卷访谈，重点分析了土地利用效率低、外来人口集中以及基础设施建设与城市经济发展不相协调等问题，并提出协调城市化发展的对策。     

基于农用地价格体系的征用地价应用研究

农用地价格体系和估价成果应用是当前农用地定级估价工作的难点和争论焦点，该文提出了农用地价格体系应以资源基准地价为基础，通过一系列修正，得出分级分区的征用基准地价、不转变用途的农地流转价、转变用途的农地转用价；以佛山市南海区的农用地估价成果为例，就其与现行征地补偿标准进行了比较，并与南海城区、广州市区城镇建设用地基准地价的相互衔接性进行了验算，应用成本逆推法，从城镇基准地价导出建设用地生地地价，在内涵一致的条件下相互比较。结果表明，按此地价体系建立的农用地征用价能够与城镇地价相衔接，可为城乡地价一体化的建立提供实证。