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31.
兰州CAWS600-R自动站与人工观测资料对比分析 总被引:7,自引:10,他引:7
利用2002年11月到2003年2月兰州CAWS600-R型自动站与人工观测的温度、本站气压、水汽压、相对湿度、5~320cm地温等资料,分析了对比观测资料的差值。结果表明:对气温、本站气压、水汽压、相对湿度及320cm地温等要素观测误差较小,5~160cm地温的观测误差较大。自动观测仪器的系统性偏差、测量元件的精度及对气象要素变化响应的灵敏度、观测时间的差异和人为因素的影响是造成对比观测误差的原因。 相似文献
32.
三维旋转式自动进样器的研制 总被引:1,自引:0,他引:1
介绍了自行研制的三维旋转式自动进样器的结构和特点,提出了三维模式、气动升降臂、旋转定位的自动进样器解决方案,并成功地用于自动进样器的研制。文章中给出了三维旋转式自动进样器的组成,气动式升降臂控制原理和系统的软件流程。 相似文献
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提出了一种由平面三角网格自动生成三维空间四面体单元网格的方法,其基本思路是将含水层平面分成三角形单元网格,将每个三角形沿垂直方向对应一个三棱柱,作为最初的三棱柱;依次将每个三棱柱按照潜水面位置和分层信息划分成不同数目的四面体,从而生成三维空间四面体单元网格。剖分结果表明,此方法综合考虑了潜水面的位置和各含水层顶底板的起伏情况,能够简洁地生成层面起伏的空间四面体网格,特别适用于刻画潜水面波动、含水层顶底板起伏和存在透镜体或岩性缺失等含水层结构复杂的情况下,自动地剖分并生成单元信息,为三维计算的实现奠定了基础。 相似文献
35.
ZHANGQiaoping IsabelleCouloigner 《地球空间信息科学学报》2004,7(2):89-95
This paper presents a tramework for road network change detectlon In order to upctate the Canadian National Topographic DataBase (NTDB). The methodology has been developed on the basis of road extraction from IRS-pan images (with a 5.8 m spatial resolution) by using a wavelet approach. The feature matching and conflation techniques are used to road change detection and updating. Elementary experiments have showed that the proposed framework could be used for developing an operational road database updating system. 相似文献
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等高线拓扑关系的构建以及应用 总被引:9,自引:1,他引:9
提出了等高线拓扑关系的描述框架 ,其规范化描述形式具有更强的适用性 ,使用三角网作为工具设计了建立拓扑关系的算法。以提出的拓扑关系描述为基础 ,具体实现了等高线高程自动赋值 ,处理过程可以同时考虑开曲线 (包括断线 )和闭曲线 ,提高了可靠性和自动化程度 ,并进一步将断线连接为完整目标 ,减少了人机交互的编辑工作 相似文献
38.
本文针对CAPPS2.0系统在业务化自动运行过程中的一些问题,提供了一套具体可行的解决方案,实现了CAPPS系统的全自动运行,具有很高的实用价值。 相似文献
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In the identifying process of an oil spill accident, manual integral and artificial visual comparison are commonly used at present to determine the oil spill sources, these methods are time-consuming and easily affected by human factors. Therefore, it is difficult to achieve the purpose of rapid identification of an oil spill accident. In this paper, an intelligent method of automatic recognition, integration and calculation of diagnostic ratio of Gas Chromatography-Mass Spectrometer (GC/MS) spectrum are established. Firstly, four hundreds of samples collected around the world were analyzed using a standard method and Retention time locking technology (RTL) was applied to reduce the change of retention time of GC/MS spectrum. Secondly, the automatic identification, integration of n-alkanes, biomarker compounds, polycyclic aromatic hydrocarbons and calculation of the diagnostic ratios were realized by MATLAB software. Finally, a database of oil fingerprints were established and applied successfully in a spill oil accident. Based on the new method and database, we could acquire the diagnostic ratios of an oil sample and find out the suspected oil within a few minutes. This method and database can improve the efficiency in spilled oil identification. 相似文献
40.
Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献