Natural Resources Research - This study tested and compared the mineral potential mapping capabilities of the random forest (RF) and maximum entropy (MaxEnt) algorithms using gold deposit... 相似文献
Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2?cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast. 相似文献
The carbonate-free fraction of 20 surface sediments collected from the ultraslow-spreading Southwest Indian Ridge(SWIR) was studied by grain size analysis and mineralogical analysis with X-ray powder diffraction(XRD),stereo microscopy and scanning electron microscopy(SEM). The characteristics of the carbonate-free fraction of the sediments were obtained, and related influential factors were discussed. The results show that the mean grain size of this fraction is in 1.96Φ–8.19Φ, with poorly sorting and unimodal, bimodal or irregular bimodal distribution patterns. Four grain size end members of the fraction are derived with the End Member Model method. The finest end member EM1 shows a significant contribution of terrigenous materials of the aeolian input and sediment carried by the bottom current. End member EM2 with medium size mainly reflects sediment of a siliceous bioclast origin. EM3 and EM4 are interpreted as representing the coarser volcanic materials related to bedrock weathering or volcanic activities. Multi-provenance is the dominant factor controlling the grain size pattern of the carbonate-free fraction of the sediments in that area. In addition, sediment transport processes such as the bottom current and wind are the minor factors that influence the grain size distribution of the carbonate-free fraction sediments. 相似文献
The knowledge of prey small fish stock, distribution and abundance is necessary to guide stocking of piscivorous fish for the biomanipulation in domestic tap water lakes. This study describes the current status of small fish community in Lake Kuilei (China), and examines the spatial and seasonal variations of the community in relation to key environmental factors. Based on submerged macrophyte cover and water depth, the lake was divided into five major habitats: (1) macrophyte covered shallow habitat of water depth < 2.00 m, (2) uncovered or less-covered shallow habitat (2.00 m–3.50 m), (3) uncovered medium shallow habitat (3.50 m–5.00 m), (4) uncovered medium deep habitat (5.00 m–6.50 m) and (5) uncovered deep habitat (6.50 m–8.50 m). The abundance and composition of small fish were monitored by benthic fykenet sampling from April 2013 to January 2014. A total of 2881 individuals belonging to 5 families and 21 species were collected. Based on their abundance (accounted for 88.96% of the total) and occurrence (more than 33.33%), Acheilognathus chankaensis, Acheilognathus macropterus, Microphysogobio microstomus, Pseudorasbora parva and Rhinogobius giurinus were recognized as dominant small fish species. The results of correlation analysis identified that species richness ( Sr ), Shannon-Wiener diversity index ( H′ ) and Margalef′s richness index ( D ) were significantly negatively correlated with water depth, but positively correlated with biomass of submerged macrophytes.Redundancy analysis (RDA) revealed that the spatial distributions of most small fishes were negatively associated with water depth. The details of these findings are beneficial to understanding the adaptation of the small fishes in degraded environments, and to developing suitable biomanipulation strategies for the management of fish resources and water quality in the lakes along the lower reach of the Changjiang (Yangtze) River basin.
