基于人工神经网络的沿海风速多步预测研究

基于气象历史观测资料,将长短期记忆网络LSTM方法和Transformer模型结合提出了混合短期风速多步预测模型BLSTM TRA。以山东半岛南部沿海6个台站为研究区域,通过气象台站观测数据构建数据集。经与2018年ECMWF模式6 h预报结果对比分析,得出如下结论：构建的BLSTM TRA多步预测模型可大幅度降低风速误差,BLSTM TRA的1 h单步预测结果和ECMWF预报模式结果对比,其RMSE平均降低了58.9%,MAE平均降低了63.2%;风速误差和大风统计过程分析发现,BLSTM TRA模型具有一定的抗干扰能力,可以抓住短时大风等敏感信息,对于大风预报结果明显优于ECWMF模式和传统LSTM模型。     

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利用伪归一化差异水体指数提取城镇周边细小河流信息

通过对归一化差异水体指数NDWI中的绿波段修正,提出了不依赖于中红外波段的伪归一化差异水体指数FNDWI（False NDWI）。使用NDWI和FNDWI分别在背景地物为城市、城郊、乡镇、村落和山区的遥感影像上进行河流水体提取,实验表明,FNDWI影像中城镇建筑用地与河流水体的可分离性较NDWI有所提升,提升率为116%~335%不等;相关性分析表明,河流宽度与可分离性提升率具有明显的负相关关系,相关系数为-0.82;分类结果显示,在城市和城郊区域,NDWI提取的水体中混杂有较多城镇建筑用地信息,而FNDWI提取的水体中基本未见混杂。总体上,FNDWI提高了2种地物的可分离性,剔除了NDWI影像混入的城镇建筑用地信息,较好地解决了NDWI城镇建筑用地与河流水体的混淆问题,尤其适用于城镇周边的细小河流。     

地图概括中空间目标几何信息传递模型研究

地图概括是实现多比例尺地图生产和更新的一种重要理论方法。目前,国际国内制图学界对地图概括的研究主要集中在发展地图概括算法方面,在地图概括的质量评价方面的研究还很少。为此,本文以信息论为理论基础,以地图概括中空间目标几何信息的传递问题为研究对象,以相应空间目标几何信息的传递效率来度量地图概括中单个空间目标的概括质量。首先,建立了地图概括的空间信息传递模型,描述不同比例尺地图之间空间信息的传递过程。进而提出了地图概括过程中空间目标(即:线和面目标)几何信息的传递模型,并且对地图概括中空间目标几何信息的传递状况进行了评估,给出了具体的计算和实现方法。最后,通过实验初步验证了地图概括中空间目标几何信息传递模型的可行性。     

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燕山水库的主要环境工程地质问题

本文在简要介绍燕山水库工程地质环境的基础上,分析论述了可能产生的环境工程地质问题。指出水库淹没及浸没、水库诱发地震、坝基渗透变形及膨胀土体稳定问题是该水库的主要环境工程地质问题,并提出了进一步研究的途径。     

Evaluation on tourism ecological security in nature heritage sites —Case of Kanas nature reserve of Xinjiang, China

The nature heritages are the precious legacy of nature with outstanding scientific and aesthetic value. They are quite different from other common ecotourism areas, because of its original and unique system, sensitive and vulnerable landscape, and peripheral cultural features. Therefore, the tourism development in the nature heritage sites should be on the premise of ecological security. The evaluation index system of tourism ecological security in nature heritage sites was constructed in this article by AHP and Delphi methods, including nature ecological security, landscape visual security and local culture ecological security, and the security thresholds of indices were also established. In the indices’ weights of the evaluation model, the nature ecological security ranked the highest, followed by tourist landscape visual security and culture ecological security, which reflected the influence degree of the limited factor to tourism ecological security. Then, this paper carried out an empirical study of Kanas of Xinjiang Uygur Autonomous Region, China, which has the potential to be the World Nature Heritage. On the basis of the data attained from survey and observation on the spot, as well as questionnaire answered by tourists and local communities, the ecological security status in Kanas was evaluated. The result showed that the status of Kanas tourism ecological security was better, but there had some limiting factors. Lastly, effective measures were put forward to ensure its ecological security. Foundation item: Under the auspices of National Natural Science Foundation of China (No. 40671057), Knowledge Innovation Programs of Chinese Academy of Sciences (No. KZCX3-SW-355)     

Blazar天体3C 66A光学波段准周期光变分析

研究了Blazar天体3C 66A光学波段的准周期光变行为.收集了3C 66A光学V波段将近18 yr (2003—2021年)的测光数据,观测数据主要来源是:上海天文台(ShAO)、 AAVSO (The American Association of Variable Star Observers)数据库、Steward天文台.使用了Jurkevich和Lomb-Scargle两种方法分析了光变数据.Jurkevich方法得到了(850±90) d (～2.3 yr)和(1150±140) d (～3.2 yr)的光变周期,而Lomb-Scargle方法在充分考虑了“红噪声”效应之后同样得到了(869±70) d和(1111±90) d的光变周期,它们的置信水平分别为>99%和> 95%.通过与之前的研究结果比较,发现～2.3 yr的光变周期在3C 66A的历史光变数据中是一个稳定的周期,而～3.2 yr的周期则是不稳定的.     

基于自适应峰值分解的广义局部频率时频分析方法

往复压缩机振动信号具有复杂的多源冲击特性,表现较强的非平稳性,传统的时频分析方法难以提取有效的故障特征.以傅氏变换为基础的传统频率概念和以希尔伯特变换为基础的瞬时频率概念存在固有缺陷,提出一种广义局部频率的概念,并结合自适应峰值分解方法,实现信号时频分布的构造途径;与HHT时频分析方法进行仿真对比,并应用到往复压缩机振动信号故障特征提取.结果表明,基于自适应峰值分解的广义局部频率方法有效揭示往复压缩机不同故障的多源冲击振动信号时频特征,为往复压缩机故障诊断提供一种新的手段.     

Alternative Fuzzy Cluster segmentation of remote sensing images based on Adaptive Genetic Algorithm

Remote sensing image segmentation is the basis of image understanding and analysis. However, the precision and the speed of segmentation can not meet the need of image analysis, due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm (AGA) and Alternative Fuzzy C-Means (AFCM). Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased, and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means (FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.