基于F-范数的不确定性平差模型的解算方法

为提高基于F-范数的不确定性平差模型的解算效率，给出直接迭代算法进行参数估计。该算法无需SVD，解算过程简单且易于编程计算，同时给出迭代不收敛时的SVD-解方程算法。二元线性拟合及沉降观测AR模型的算例结果表明，这2种算法正确可行，与SVD-迭代算法具有等价性。当迭代收敛时，宜使用直接迭代算法，收敛速度更快，解算效率更高；当迭代不收敛时，可釆用SVD-解方程算法。     

资源三号和天绘一号卫星影像无控联合平差精度分析

近年来国产卫星传感器类型日益丰富，使用自主可控的国产卫星影像进行生产和研究的需求越来越大，多源国产卫星影像联合平差的精度分析显得尤为重要。本文针对在立体测图生产中，资源三号卫星影像在时相较旧、噪声较大、云覆盖和摄影漏洞等特殊困难的条件下，利用天绘一号卫星影像进行补漏生产的情况，最终分析并验证了两者无控联合平差的可行性和成果精度。     

浅谈项目投资失败的原因及对策

地勘单位在向企业化经营转变的过程中 ,投资兴办了许多企业 ,但不少项目以失败告终。文章分析探讨了失败的原因 ,并提出相应的对策     

TROS-Ⅰ型流动人卫激光测距仪光学系统设计

介绍了车载流动型人卫激光测距仪光学系统(包括激光发射系统、接收系统及微光电视监视系统)的设计思想和方法,着重叙述了光学系统的结构设计、关键部件几何尺寸的确定及重要元器件的选取。设计基于流动型仪器应满足的防振、体积小、调校方便、抗环境干扰能力强等特点。多年的实测证明,这种光学系统不仅能满足流动型人卫激光测距仪总体设计要求,而且经济实用。     

LAMOST/GALAXY计划:利用LAMOST研究银河系

本文讨论了利用LAMOST作银河系研究的科学意义及可能性；并提出具体实施LAMOST/GAIAXY计划的初步方案。     

Socio-economic and Environmental Implications of the Hydroelectric Projects in Uttarakhand Himalaya, India

This paper deals with detailed analysis of the fiasco created by the Tehri High Dam in Uttarakhand, India, particularly in terms of resettlement and rehabilitation of the local inhabitants. Aspects pertaining to the environmental issues are also discussed. Currently, the river valleys in Uttarakhand state of India are the targets of increasing hydroelectric projects. Virtually all rivers are being exploited for generating environmental friendly power. Having being learned the hard lesson from Tehri Dam, it has been decided to opt for such schemes in which comparatively little submergence and tempering with the fragile eco-systems is involved.However, our observations suggest that even in such schemes if due care is not taken they may turn out to be a failure.     

西部大开发中的科技伦理调控

在阐述西部大开发中科技主导地位的基础上 ,从科技应用成效二重性的视角 ,探讨了关注西部科技伦理的必要性 ,并初步提出了西部大开发战略的科技伦理调控机制     

丽江高美古台址和2m级望远镜项目(英文)

自 1992年起云南天文台开始了在云南省西北部的天文选址。丽江高美古最终被选择作为未来中国地基天文光学观测的新址点。并且 ,在国家科技部 ,云南省政府 ,以及中科院的支持下 ,2m级天文望远镜项目在 2 0 0 0年 12月获得立项。在文中 ,我们简要的介绍了高美古台址的情况 ,并给出了 2 .4m望远镜的详细情况 ,以及其他相关情况。     

智能照明系统在现代建筑照明中的应用研究

在对传统照明系统和智能照明系统进行对比分析的基础上,剖析了智能照明系统的控制策略,并结合实际的工程应用,着重讨论了基于ABB I-Bus产品的智能照明控制系统的实现,结果表明该系统具有高效、便捷、节约能源等优点.同时,还对系统与建筑物楼宇自控系统问的系统集成方式进行了研究.     

Neural network prediction of nitrate in groundwater of Harran Plain, Turkey

Monitoring groundwater quality by cost-effective techniques is important as the aquifers are vulnerable to contamination from the uncontrolled discharge of sewage, agricultural and industrial activities. Faulty planning and mismanagement of irrigation schemes are the principle reasons of groundwater quality deterioration. This study presents an artificial neural network (ANN) model predicting concentration of nitrate, the most common pollutant in shallow aquifers, in groundwater of Harran Plain. The samples from 24 observation wells were monthly analysed for 1 year. Nitrate was found in almost all groundwater samples to be significantly above the maximum allowable concentration of 50 mg/L, probably due to the excessive use of artificial fertilizers in intensive agricultural activities. Easily measurable parameters such as temperature, electrical conductivity, groundwater level and pH were used as input parameters in the ANN-based nitrate prediction. The best back-propagation (BP) algorithm and neuron numbers were determined for optimization of the model architecture. The Levenberg–Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 25. The model tracked the experimental data very closely (R = 0.93). Hence, it is possible to manage groundwater resources in a more cost-effective and easier way with the proposed model application.