Extracting geochemical anomalies from geochemical exploration data is one of the most important activities in mineral exploration. Geochemical anomaly detection can be regarded as a binary classification problem. The similarity between geochemical samples can be measured by their distance. The key issue of this classification is to find the intrinsic relationship and distance between geochemical samples to separate geochemical anomalies from background. In this paper, a hybrid method that integrates random forest and metric learning (RFML) is used to identify geochemical anomalies related to Fe-polymetallic mineralization in Southwest Fujian Province of China. RFML does not require any specific statistical assumption on geochemical data, nor does it depend on sufficient known mineral occurrences as the prior knowledge. The geochemical anomaly map obtained by the RFML method showed that the known Fe deposits and the generated geochemical anomaly area have strong spatial association. Meanwhile, the receiver operating characteristic curves for the results of RFML and another method, namely maximum margin metric learning, indicated that the RFML method exhibited better performance, suggesting that RFML can be effectively applied to recognize geochemical anomalies.
The static balance and the geostrophic balance are the common balances in meteorology.All the synoptic systems and most of the mesoscale systems satisfy the above two balances.However,due to the strong convection and non-geostrophic feature,many mesoscale systems usually present as static imbalance,and the quasi-geostrophic approximation is no longer attainable.This paper tried to find out a kind of balance that exists for mesoscale convective system.To do this,the concrete mathematics definitions for balance and imbalance equations were defined.Then,it is proposed that the new balance equation should include the divergence,vorticity,and vertical motion simultaneously,and the helicity equation was a good choice for the basis.Finally,the mesoscale balance and imbalance equations were constructed,as well as a new balance model that was based on the helicity,horizontal divergence,vertical vorticity,continuity,and thermal dynamic equations under same approximations.Moreover,the corresponding potential vorticity(PV)inversion technique was introduced.It was pointed out that by using the PV conservation and the potential temperature conservation,the flows of the mesoscale balance model can be deduced,and their comparison with the real fields would give the degree of the imbalance. 相似文献
With the development of precise point positioning (PPP), the School of Geodesy and Geomatics (SGG) at Wuhan University is now routinely producing GPS satellite fractional cycle bias (FCB) products with open access for worldwide PPP users to conduct ambiguity-fixed PPP solution. We provide a brief theoretical background of PPP and present the strategies and models to compute the FCB products. The practical realization of the two-step (wide-lane and narrow-lane) FCB estimation scheme is described in detail. With GPS measurements taken in various situations, i.e., static, dynamic, and on low earth orbit (LEO) satellites, the quality of FCB estimation and the effectiveness of PPP ambiguity resolution (AR) are evaluated. The comparison with CNES FCBs indicated that our FCBs had a good consistency with the CNES ones. For wide-lane FCB, almost all the differences of the two products were within ±0.05 cycles. For narrow-lane FCB, 87.8 % of the differences were located between ±0.05 cycles, and 97.4 % of them were located between ±0.075 cycles. The experimental results showed that, compared with conventional ambiguity-float PPP, the averaged position RMS of static PPP can be improved from (3.6, 1.4, 3.6) to (2.0, 1.0, 2.7) centimeters for ambiguity-fixed PPP. The average accuracy improvement in the east, north, and up components reached 44.4, 28.6, and 25.0 %, respectively. A kinematic, ambiguity-fixed PPP test with observation of 80 min achieved a position accuracy of better than 5 cm at the one-sigma level in all three coordinate components. Compared with the results of ambiguity-float, kinematic PPP, the positioning biases of ambiguity-fixed PPP were improved by about 78.2, 20.8, and 65.1 % in east, north, and up. The RMS of LEO PPP test was improved by about 23.0, 37.0, and 43.0 % for GRACE-A and GRACE-B in radial, tangential, and normal directions when AR was applied to the same data set. These results demonstrated that the SGG FCB products can be produced with high quality for users anywhere around the world to carry out ambiguity-fixed PPP solutions. 相似文献
Scientific interpretation of the driving forces of built-up land expansion is essential to urban planning and policy-making. In general, built-up land expansion results from the interactions of different factors, and thus, understanding the combined impacts of built-up land expansion is beneficial. However, previous studies have primarily been concerned with the separate effect of each driver, rather than the interactions between the drivers. Using the built-up land expansion in Beijing from 2000 to 2010 as a study case, this research aims to fill this gap. A spatial statistical method, named the geographical detector, was used to investigate the effects of physical and socioeconomic factors. The effects of policy factors were also explored using physical and socioeconomic factors as proxies. The results showed that the modifiable areal unit problem existed in the geographical detector, and 4000 m might be the optimal scale for the classification performed in this study. At this scale, the interactions between most factors enhanced each other, which indicated that the interactions had greater effects on the built-up land expansion than any single factor. In addition, two pairs of nonlinear enhancement, the greatest enhancement type, were found between the distance to rivers and two socioeconomic factors: the total investment in fixed assets and GDP. Moreover, it was found that the urban plans, environmental protection policies and major events had a great impact on built-up land expansion. The findings of this study verify that the geographical detector is applicable in analysing the driving forces of built-up land expansion. This study also offers a new perspective in researching the interactions between different drivers. 相似文献
Due to the continuous and intense rainfall from June 26 to 28, 2016, Xinlu Village in Ganshui Town, Qijiang District, Chongqing, experienced a unitary-slip landslide at approximately UTC+8 19:30 on June 28. This landslide disrupted the Chuan-Qian railway and damaged four residential buildings. To analyze and rehabilitate the landslide, the engineering geology, hydrological conditions, and deformation instability mechanism of this landslide were investigated and comprehensively analyzed based on an in situ survey, geophysical drilling, and a laboratory quick-shearing test. The results show that the landslide is a typical gradual progressive landslide. 相似文献
Previous studies showed that the climatic processes drive the streamflow of the inland river in Northwest China. However, it is difficult to quantitatively assess the climatic-hydrological processes in the ungauged mountainous basins because of the scarce data. This research developed an integrated approach for multi-temporal scale modeling the climatic-hydrological processes in data-scarce mountain basins of Northwest China by combining downscaling method (DM), backpropagation artificial neural network (BPANN), and wavelet regression (WR). To validate the approach, we also simulated the climatic-hydrological processes at different temporal scales in a typical data-scarce mountain basin, the Kaidu River Basin in Northwest China. The main results are as follows: (i) the streamflow is related with regional climatic change as well as atmosphere-ocean variability, (ii) the BPANN model well simulated the nonlinear relationship between the streamflow and temperature and precipitation at the monthly temporal scale, and (iii) although the annual runoff (AR) appears to have fluctuations, there are significant correlations among AR, annual average temperature (AAT), annual precipitation (AP), and oscillation indices, which can be simulated by equations of WR at different temporal scales of years. 相似文献