With the acceleration of urbanisation in China, preventing and reducing the economic losses and casualties caused by urban rainstorm waterlogging disasters have become a critical and difficult issue that the government is concerned about. As urban storms are sudden, clustered, continuous, and cause huge economic losses, it is difficult to conduct emergency management. Developing a more scientific method for real-time disaster identification will help prevent losses over time. Examining social media big data is a feasible method for obtaining on-site disaster data and carrying out disaster risk assessments. This paper presents a real-time identification method for urban-storm disasters using Weibo data. Taking the June 2016 heavy rainstorm in Nanjing as an example, the obtained Weibo data are divided into eight parts for the training data set and two parts for the testing data set. It then performs text pre-processing using the Jieba segmentation module for word segmentation. Then, the term frequency–inverse document frequency method is used to calculate the feature items weights and extract the features. Hashing algorithms are introduced for processing high-dimensional sparse vector matrices. Finally, the naive Bayes, support vector machine, and random forest text classification algorithms are used to train the model, and a test set sample is introduced for testing the model to select the optimal classification algorithm. The experiments showed that the naive Bayes algorithm had the highest macro-average accuracy. 相似文献
This paper presents the results of field tests performed to investigate the compressive bearing capacity of pre-bored grouted planted (PGP) pile with enlarged grout base focusing on its base bearing capacity. The bi-directional O-cell load test was conducted to evaluate the behavior of full scale PGP piles. The test results show that the pile head displacements needed to fully mobilize the shaft resistance were 5.9% and 6.4% D (D is pile diameter), respectively, of two test piles, owing to the large elastic shortening of pile shaft. Furthermore, the results demonstrated that the PHC nodular pile base and grout body at the enlarged base could act as a unit in the loading process, and the enlarged grout base could effectively promote the base bearing capacity of PGP pile through increasing the base area. The normalized base resistances (unit base resistance/average cone base resistance) of two test piles were 0.17 and 0.19, respectively, when the base displacement reached 5% Db (Db is pile base diameter). The permeation of grout into the silty sand layer under pile base increased the elastic modulus of silty sand, which could help to decrease pile head displacement under working load.
Fine characterization of pore systems and heterogeneity of shale reservoirs are significant contents of shale gas reservoir physical property research.The research on micro-control factors of low productivity in the Qiongzhusi Formation(Fm.)is still controversial.The lower Cambrian Qiongzhusi Fm.in the Qujing,Yunnan was taken as the object to investigate the influence of mineral compositions on the phys-ical properties of the reservoir and the heterogeneity of shale,using the algorithm to improve the char-acterization ability of Atomic Force Microscopy(AFM).The results showed that:(1)The pores are mainly wedge-shaped pores and V-shaped pores.The pore diameter of the main pore segment ranges from 5 to 10 nm.Mesopores are mainly developed in the Qiongzhusi Fm.shale in Well QD1,with the average pore diameter of 6.08 nm.(2)Microscopic pore structure and shale surface properties show strong hetero-geneity,which complicates the micro-migration of shale gas and increases the difficulty of identifying high-quality reservoirs.(3)The increase of clay mineral content intensifies the compaction and then destroys the pores.Conversely,brittle minerals can protect pores.The support and protection of brittle minerals to pores space depend on their content,mechanical properties and diagenesis.(4)Compression damage to pores,large microscopic roughness and surface fluctuations and strong pore structure heterogeneity are the reasons for the poor gas storage capacity of the Qiongzhusi Fm.,which will lead to poor productivity in the Qiongzhusi Fm. 相似文献
China Ocean Engineering - In order to reduce the hydrodynamic and structural influences on the detection accuracy especially in the very-low-frequency range, some vibration restraint methods are... 相似文献
A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topo-logical distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
Journal of Geographical Sciences - Mountains in western China, hosted rich biodiversity and millions of people and inhabitant with vital ecosystem services, had experienced the most serious... 相似文献
Existing spatial clustering methods primarily focus on points distributed in planar space. However, occurrence locations and background processes of most human mobility events within cities are constrained by the road network space. Here we describe a density-based clustering approach for objectively detecting clusters in network-constrained point events. First, the network-constrained Delaunay triangulation is constructed to facilitate the measurement of network distances between points. Then, a combination of network kernel density estimation and potential entropy is executed to determine the optimal neighbourhood size. Furthermore, all network-constrained events are tested under a null hypothesis to statistically identify core points with significantly high densities. Finally, spatial clusters can be formed by expanding from the identified core points. Experimental comparisons performed on the origin and destination points of taxis in Beijing demonstrate that the proposed method can ascertain network-constrained clusters precisely and significantly. The resulting time-dependent patterns of clusters will be informative for taxi route selections in the future. 相似文献