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Optimizing slope safety factor prediction via stacking using sparrow search algorithm for multi-layer machine learning regression models
The safety factor is a crucial quantitative index for evaluating slope stability. However, the traditional calculation methods suffer from...
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Using crop models, a decline factor, and a “multi-model” approach to estimate sugarcane yield compared to on-farm data
Sugarcane is an important crop in Brazilian agribusiness due to its diversified use. Crop forecast models are important tools for planning and making...
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Soft Computing-Based Models for Estimating Undrained Bearing Capacity Factor of Open Caisson in Heterogeneous Clay
Open caissons are commonly used in the construction of various underground structures, such as launch and reception shafts for tunnel-boring...
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A Common Factor Analysis Based Data Mining Procedure for Effective Assessment of 21st Century Drought under Multiple Global Climate Models
Continued global warming has increased the risk of drought all over the world. Therefore, effective drought assessment, in conjunction with accurate...
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Performance analysis of landslide susceptibility assessment under different factor-filtering models
Landslide susceptibility assessment is usually considered as an essential part of landslide hazard risk reduction, and the key steps of it are to...
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Rainfall-induced landslide prediction models, part ii: deterministic physical and phenomenologically models
Landslides are frequent hillslope events that may present significant risks to humans and infrastructure. Researchers have made ongoing efforts to...
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Prediction of compressive strength of concrete under various curing conditions: a comparison of machine learning models and empirical mathematical models
Considering the pivotal role of compressive strength in assessing concrete quality, accurately predicting it is essential for guiding construction...
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Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models
Accurate soil moisture (SM) prediction is critical for understanding hydrological processes. Physics-based (PB) models exhibit large uncertainties in...
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Depth of the pedological profile as a conditioning factor of soil erodibility (RUSLE K-Factor) in Ecuadorian basins
Soil erodibility (K-Factor) is one of the fundamental parameters to estimate its rainfall erosion through mathematical models such as RUSLE. Carrying...
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Study on separation factor models for well anti-collision analysis
Anti-collision analysis has been becoming even more important in the past few years with the increasing amount of wells drilled in highly congested...
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GIS-based evaluation of water-inrush risk from coal floor using logistic regression and certainty factor models
With the gradual increase in coal mining depth in China, the threat of floor water disaster in coal mines is also increasing. The risk assessment of...
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The Variation Law of Shape Factor for Fractured Carbonate Reservoirs
Shape factor of fractured porous media is crucial to characterize fluid flow in fractured carbonate reservoirs. However, due to the complex...
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Influence of LS Factor Overestimation Soil Loss on RUSLE Model for Complex Topographies
Soil loss is a crucial problem due to its importance in agricultural and livestock production, where intensive human activities have exacerbated...
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Advances in Atmospheric Radiation: Theories, Models, and Their Applications. Part II: Radiative Transfer Models and Related Applications
The subject of “atmospheric radiation” includes not only fundamental theories on atmospheric gaseous absorption and the scattering and radiative...
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Menger Sponge Models
Menger Sponge (in 3D) and Sierpiński CarpetSierpiński carpet (in 2D) are the most useful fractal modelsFractal model of the rocks’ pore spacePore...
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Random Network Models
The common way to compute hydraulic and electric flow in porous media is to substitute the pore structure by a network consisting of nodesNode (for...
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Uncertainty analysis method of slope safety factor based on quantile-based ensemble learning
To overcome the problem that the point prediction method of slope safety factor has uncertainty in its prediction and hence cannot a reliable slope...
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Glacial debris flow susceptibility map** based on combined models in the Parlung Tsangpo Basin, China
Machine learning (ML)-based prediction models for map** hazard (e.g., landslide and debris flow) susceptibility have been widely developed in...
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Parameterization Method of Wind Drift Factor Based on Deep Learning in the Oil Spill Model
Oil spill prediction is critical for reducing the detrimental impact of oil spills on marine ecosystems, and the wind strongly influences the...
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Model of transferability for the rainfall erosivity factor
Empirical models such as the universal soil loss equation (USLE) are used to measure sediment production. Applying the USLE requires determining the...
