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There are various liquefaction assessment methods empirically based on test data used both domestically and internationally. Among them, the cone penetration test (CPT) has become a common method due to its inherent advantages. This paper elaborates on four commonly used CPT-based liquefaction assessment methods from both domestic and international sources: the NCEER method, the Code for investigation of geotechnical engineering method, the Specification for geotechnical invesitgation in soft clay area method, and the General rules for performance-based seismic design of buildings method. It compares the assessment results of these methods and utilizes data-driven classification and regression tree (CART) and random forest (RF) algorithms to study and analyze the importance of liquefaction influencing factors and the interplay among them. A new set of standards for determining liquefaction occurrence was developed, showing that: The General Rules method proposed by YUAN Xiaoming et al. is balanced with the highest accuracy for liquefaction assessment, achieving over 94% accuracy in seismic intensity zones of 7, 8 and 9, which is higher than the NCEER method, and significantly better than the Geotechnical Specification and Soft Soil Procedure methods. The NCEER method, though ranking second best, tends to misclassify a large quantity of non-liquefaction data as liquefaction in deeper layers of intensity zone 9, which is not consistent with reality. The performance of the Geotechnical Specification and Soft Soil Procedure methods is the worst. The accuracies of the two machine learning methods are 97.6% and 97.5% respectively, with the importance ranking of predictive variables being largely consistent. Factors such as relative density (Dr), soil behavior type index (Ic), fines content (FC), and cover thickness (CT) have a significant impact on triggering liquefaction, whereas peak ground acceleration (PGA), groundwater table (GWT), and critical thickness of the liquefiable layer (CTL) have a lesser impact. The proposed new standards for liquefaction triggering are in line with the impact trends of various influencing factors, providing references and support for the prediction and assessment of liquefaction triggering.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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