灰介质辐射传热的一种数学模型

在前人工作的基础上，从辐射传热的基本原理出发，给出了描述介质辐射传热的一组控制微分方程组。该方程克服了目前热流法中空间、方向耦合差的缺陷，并反映了辐射传热的三维本质特性，同时也引进了辐射热流方向耦合系数矩阵、辐射热通流量，辐射场强等概念。该方程组较容易与其它传输方程耦合在一起，解决生产实际问题。     

Roll Subsectional Cooling Adaptive Fuzzy Control Based on Fuzzy Model Inversion

 Flatness is an important equality indicator of strip rolling and roll sub-sectional cooling is an important method for flatness control, especially for high order flatness component control. It is very hard to build the mathematic model of roll sub-sectional cooling because of its characteristics of nonlinearity, hysteresis quality and strong coupling etc. In order to improve the control effect of roll sub-sectional cooling control model, the roll sub-sectional cooling adaptive fuzzy control model based on fuzzy model inversion is built according to the separation principle of fuzzy form on the basis of the conventional fuzzy control model, where the parameters of the fuzzy controller can be dynamically regulated according to the change of rolling conditions. Simulation experiment results of the model indicate that the proposed roll sub-sectional cooling adaptive fuzzy control model based on fuzzy model inversion has high control precision and rapid response speed with strong self-learning and anti-interference capacity and a new method is provided for high-precision flatness control.     

基于TM影像的大浪淀水库悬浮物含量的模型反演

以沧州大浪淀水库为研究时象,将实测的悬浮物含量和遥感数据进行分析处理,构建了悬浮物含量与TM2+TM3多光谱模型,并对模型进行了反演,其结果符合水体实际水质分布情况,表明所建模型可应用于该水体悬浮物含量的监测需要.     

基于循环经济的南四湖流域经济发展模式及对策研究

从南四湖流域应该大力发展循环经济模式入手,阐述了循环经济的含义,对南四湖流域在发展循环经济中农业、工业企业、废物利用等方面存在的问题进行分析,结合循环经济发展的农户、企业、区域以及社会4种模式,针对南四湖流域发展循环经济提出相应的对策和建议:一是建立发展南四湖流域大农业循环经济的政府引导机制;二是建立南四湖流域循环经济的工业企业激励制度;三是调整南四湖流域产业结构,优化能源消费结构.     

Modeling of Radiative Heat Transfer in an Electric Arc Furnace

Metallurgical and Materials Transactions B - Radiation is an important means of heat transfer inside an electric arc furnace (EAF). To gain insight into the complex processes of heat transfer...     

Effect of Gridding Method on Digital Terrain Model Profile Data Based on Scattered Data

Various forms of data such as profile, cross section, volume, height, and surface area can be derived from the digital terrain model (DTM). Although many research studies were carried out on the accuracy of the DTM, especially on grid data-based DTMs and on the effect of the grid size or grid resolution, the accuracy of profile data derived from a scattered data-based DTM and the effect of the gridding (interpolation) method on the accuracy of the profile data derived are still unfamiliar to many DTM producers and users. Therefore, the purpose of this study was to determine the accuracy of DTM profile data based on scattered data points for several gridding methods. Linear interpolation in triangles and interpolations of Sibson (natural neighbor), nearest neighbor, weighted average, polynomial, multiquadric, and minimum curvature were tested on five theoretical test surfaces. After 1-m grid DTMs were generated using the gridding methods mentioned above, nine different profile data in the y direction for each test surface and for each gridding method were derived from the DTMs. The standard deviation of each profile for each gridding method was derived by differences between true and interpolated profile values. As a result of the case study, the author recommends using interpolations of minimum curvature and multiquadric curvature for more accurate DTM profile data.     

基于多源数据的水稻种植面积提取

引入水稻关键期提取和变化向量分析方法,以江苏省海安县水稻为研究对象,以MODIS数据和环境小卫星数据为主要数据源,分析了2009年水稻物候期内的规律,并根据该指示选择合适的中分辨率数据进行变化向量分析.研究表明,该方法可以有效地反映耕地地块内水稻像元的变化规律,且基于物候关键期内的时相选择可以提高水稻种植面积识别精度.     

广东河台金矿区倒转背斜的控矿意义

以岩性、微量元素、稀土元素分析为依据,证实河台金矿区存在一个倒转背斜,该倒转背斜控制了矿床在空间上的分布,其北西翼为北矿带,南东翼为南矿带,核部为中矿带,根据背斜两翼对应关系,认为矿区南矿带具有较好的找矿前景。     

基于粒子群算法地应力场反演研究进展

阐述了基于粒子群算法的地应力场反演方法的基本原理,介绍了粒子群算法在地应力场反演中的研究现状,分析了其存在的不足,并指出与其他智能算法的结合是其发展的方向。     

基于改进迁移学习算法的岩体质量评价模型

岩体质量分级是进行工程设计和施工的基础。通过搜集不同地区55组实测样本和17组插值样本建立案例库,考虑岩体的复杂不确定性和异地岩体的差异性,在案例库基础上提出了一种改进两阶段回归迁移学习（Two-stage TrAdaBoost.R2）—孤立森林（Isolated Forest）多因素岩体质量等级预测模型。将广州抽水蓄能电站第1期地下工程的12个样本用于模型测试,结果表明：（1）迁移学习可以通过权重调整选出与目标区域岩体相似的样本,解决了传统机器学习方法中同区域训练样本数量不足的问题。（2）孤立森林算法与迁移学习相结合可以排除异常数据的影响,增加模型的稳定性。（3）利用训练好的模型对12个测试样本进行多次判定,结果与实际情况基本相符,验证了模型的有效性。