遥感影像制图综合的智能化研究

本文以人工智能为基础,用计算机模拟一般制图人员对遥感图像进行制图综合的过程,用框架的知识表示方法建立了一个实验性的知识库,并设计了一个推理机。对蒙古人民共和国乌布苏淖尔地区的ＴＭ分类图进行了实验,取得了较好的效果。     

Prognosis of TiO2 abundance in lunar soil using a non-linear analysis of Clementine and LSCC data

We suggest a technique to determine the chemical and mineral composition of the lunar surface using artificial neural networks (ANNs). We demonstrate this powerful non-linear approach for prognosis of TiO₂ abundance using Clementine UV-VIS mosaics and Lunar Soil Characterization Consortium data. The ANN technique allows one to study correlations between spectral characteristics of lunar soils and composition parameters without any restrictions on the character of these correlations. The advantage of this method in comparison with the traditional linear regression method and the Lucey et al. approaches is shown. The results obtained could be useful for the strategy of analyzing lunar data that will be acquired in incoming lunar missions especially in case of the Chandrayaan-1 and Lunar Reconnaissance Orbiter missions.     

城市暴雨内涝综述：特征、机理、数据与方法

建成环境的高空间异质性与致灾过程的复杂性给城市暴雨内涝研究带来巨大的挑战,具体表现为模型代表性不够、计算效率低、基础数据和验证数据匮乏。以机器学习为代表的人工智能技术、高分遥感和互联网大数据的快速发展则为城市暴雨内涝研究提供了新的契机。论文结合人工智能、高分遥感和互联网大数据等新技术发展,从特征、机理、数据与方法4个维度对暴雨内涝的研究现状和发展趋势进行了系统总结,主要结论包括：① 暴雨内涝具有短历时性、空间散布性、连锁性和突变性,其热点呈现空间上的动态迁移特征。② 降雨时空特征和城市化程度决定暴雨内涝灾害的量级,地形条件尤其是微地形则决定发生位置和内涝频率。地形控制作用指数(topographic control index, TCI)对暴雨内涝发生位置具有良好的指示能力。③ 排水管网、高精度地形和不透水面分布是暴雨内涝模拟的关键基础数据;降雨过程的高时空变异性是暴雨内涝近实时预报预警的主要瓶颈,需要充分利用天气雷达观测提高其精准度;互联网众包大数据是获取高空间覆盖度暴雨内涝灾情信息的新途径,但也面临不同类型信息融合、提炼和质量控制的挑战。④ 结合水动力模拟与机器学习可建立兼具物理基础和计算效率的暴雨内涝模拟方法,是实现近实时模拟与快速预报预警的有效途径。     

关于发展人工影响天气数值模式的一些问题

人工影响天气的学科基础是中小尺度天气动力学与云降水物理学,需要将天气-动力-云降水物理耦合为一体。考虑到目前将天气动力学性质的基础数值模式用于人工影响天气中的问题,从数值模式动力方程、模式分辨率、云物理过程、数值求解方案、初边值条件等方面系统地探索了发展人工影响天气数值模式中一些需要重点解决、且不可忽视的特色问题,并举例对相关问题提出了解决思路和方法。期望提出的问题有助于构思更适合于人工影响天气数值模式,使数值模式功能真正向满足人工影响天气的要求靠近一步。     

渤海湾西北岸泻湖自然演变及其人为陆化

渤海湾西北岸发育有中纬度地区典型的滨外沙坝泻湖及沿岸沙坝泻湖。泻湖不仅是该海岸区域内的一个重要组成部分,同时亦是海岸带自然资源丰富的地带。然而,由于泻湖的自然演变退化,更重要的是人类活动的影响,致使泻湖生境遭到严重破坏,同时也加速了泻湖陆化消亡过程。本文以渤海湾西北岸泻湖为例,讨论了泻湖的自然演变及其人为陆化问题。     

30多年来呼伦贝尔草原沙漠化的演变特点及防治对策研究

采用遥感技术与野外调查相结合的方法,通过3个典型小区对呼伦贝尔草原30多年来的沙漠化演变特点进行了系统研究。结果表明:该区的樟子松林区发生着强烈的沙漠化逆转,许多地段已转变为非沙漠化土地;其它地区除部分地段由于人类的积极治理而发生沙漠化逆转外,仍处于不断发展的过程中。因此,对于樟子松天然分布区,可充分利用樟子松的优良防风固沙特性和较强的扩展能力来防治沙漠化,而对其它地区则应以封育为主,加强人工抚育和草原建设。     

新型智能化互感器校验仪的研究与实现

通过分析互感器比、角差测量方法,提出并实现了一种基于精密90°锁相移相电路的新型智能化互感器校验仪自动化测量方案。     

Using computational intelligence techniques to model subglacial water systems

Measurements of water pressure beneath Trapridge Glacier, Yukon Territory, Canada show that the basal water system is highly heterogeneous. Three types of behaviour were recorded: pressure records which are strongly correlated, records which are strongly anticorrelated, and records which alternate between strong correlation and strong anticorrelation. We take the pressure in bore-holes that are connected to the evacuation route for basal water as the forcing, and the other pressures as the response to this forcing. Previous work (Murray and Clarke 1995) has shown that these relationships can be modelled using low-order nonlinear differential equations optimized by inversion. However, despite optimizing the model parameters we cannot be sure that the final model forms are themselves optimal. Computational intelligence techniques provide alternative methods for fitting models and are robust to missing or noisy data, applicable to non-smooth models, and attempt to derive optimal model forms as well as optimal model parameters. Four computational intelligence techniques have been used and the results compared with the more conventional mathematical model. These methods were genetic programming, artificial neural networks, fuzzy logic and self-organizing maps. We compare each technique and offer an evaluation of their suitability for modelling the pressure data. The evaluation criteria are threefold: (1) goodness of fit and an ability to predict subsequent data under different surface weather conditions; (2) interpretability, and the extent and significance of any new insights offered into the physics of the glacier; (3) computation time. The results suggest that the suitability of the computational intelligence techniques to model these data increases with the complexity of the system to be modelled.     

伊乐藻-草鱼圈养人工复合生态系统建设的研究

十多年来,在长江中下游浅水湖泊,特别是城郊湖泊,围栏圈养草食性鱼类发展迅速,产量大幅度提高,经济效益明显增长。养鱼过程中,由于大量投喂商品饲料和过量利用湖泊水草资源,加之湖滨人口不断增加等多种原因,导致不少草型湖泊水生植被退化,水草消失,加速了湖泊富营养化进程,湖泊整体功能下降。 伊乐藻是1986年从国外引种东太湖的高等沉水植物,已在东太湖归化,并被广大渔民用作草食性养殖鱼类的饲料。本研究是充分利用伊乐藻的生物学和生态学特性,以及易种植、生物量大、可利用程度高等特点,研究了在浅水湖泊人工种植、采收时间和刈割方法,提高其单位面积产量;测定了草鱼对伊乐藻的消化吸收和饲料系数;研究了伊乐藻在水生态系统中的功能等,从而在浅水湖泊中设计和建设伊乐藻—草鱼圈养人工复合生态系统。即以种植伊乐藻为中心,并以它作为草食性鱼类饲料和在水界物质循环的中介,在湖泊大系统内建立的草—鱼平衡系统,以提高湖泊养鱼产量和其他水产品产量,改善渔业水质和优化湖泊生态环境为主要目的。