矿区地表彩色点云的自动分类

以矿区的彩色三维激光点云数据为研究对象，提出了矿区点云快速自动分类及目标提取的方法。首先根据彩色点云的RGB值计算HSV空间中的H值，根据各地物间H值的差异，分别对地面点与非地面点根据地物颜色先验值进行点的提取。然后对提取的点进行聚类计算，利用各类地物点云在空间分布上的显著差异，采用分层截面投影，由投影点最小包围盒的长宽比及面积比对矿区地物点云进行自动分类与提取。最后以Riegl VZ-1000扫描仪采集的某矿区地表点云数据为试验对象，验证本文算法的可行性和实用性。     

Stress-dilatancy behaviour of a polymer-coated sand

Acta Geotechnica - Natural sands can be coated by substances of various origins, from natural to anthropogenic substances (from contamination or synthesized). Therefore, predicting the mechanical...     

工程控制网观测纲要的最优设计

讨论了工程控制网观测纲要的最优化设计,同时,还把网的可靠性作为一个重要的设计指标,用以限制观测粗差对控制网的影响。     

“Giant pressure shadow” structure and ore-finding method of tectonic stress field in the Tongchang Cu-Au polymetallic orefield,Shaanxi, China: II. Dynamics of tectonic ore-forming processes and prognosis of concealed ores

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Evaluating water reuse applications under uncertainty: generalized intuitionistic fuzzy-based approach

Water reuse is a viable option to increase urban water supply, especially under new realities of climate change and increasing anthropogenic activities. A sustainable water reuse application should be cost-effective and have acceptable health risk to consumers. Water reuse application evaluation is complex because data acquisitions are usually associated with the problems of uncertainty, hesitancy, and parameterization. In this paper, a generalized intuitionistic fuzzy soft set (GIFSS)-based decision support framework is proposed to provide an effective approach to describe uncertainty and hesitancy in an intuitionistic fuzzy number. In addition, the modified measures of comparison and similarity are proposed to compare water reuse applications. Then, the proposed framework is applied to the City of Penticton (British Columbia, Canada) to evaluate seven water reuse applications. The evaluation results show that the applications of garden flower watering and public parks watering are the most preferred alternatives, which are consistent with the existing practice in the city. Furthermore, the results are highly affected by the generalized parameter and the weights of evaluation criteria. Both the comparison measure-based and similarity measure-based evaluations within the same GIFSS-based framework produce consistent results, indicating an applicable and efficient methodology.     

Helium, lead and sulfur isotope geochemistry of the Gejiu Sn-polymetallic ore deposit and the sources of ore-forming materials

Studies on the helium, lead and sulfur isotopic composition were performed of the Gejiu super-large Sn-polymetallic ore deposit. The results indicated that the ore-forming materials came from different sources and the deposit is a product of superimposed mineralization. The deposit is characterized by multi-source and multi-period mineralization, which experienced submarine hydrothermal deposition and Late Yanshanian magmatic hydrothermal mineralization. It is held that the Gejiu super-large Sn-polymetallic ore deposit is a multi-genesis deposit.     

基于百度AI卷积神经网络的茶树结霜智能识别北大核心

基于采集的近20000张茶园图像,分别筛选出1000张茶园结霜和1000张未结霜图像作为训练样本,利用百度AI开放平台的EasyDL经典版图像识别功能,应用卷积神经网络算法,建立茶园结霜识别模型,进行茶树结霜图像智能判别。茶树结霜智能识别模型的准确率、F1评分、精确率、召回率分别为99.2%、99.2%、99.3%、99.1%。模型检验结果为:样本地20张结霜图像的平均识别置信度为95.51%,20张非结霜图像的平均识别置信度为99.99%;非样本地(江南茶区)80张结霜图像的平均识别置信度为97.53%,80张非结霜图像的平均识别置信度为95.11%。