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In the grey prediction, the GM(1, 1) model is an important type, but it sometimes shows big prediction errors. To improve the prediction precision of GM(1, 1) model, the paper makes improvements from the following three aspects: (1) to improve the data's adaptability to the model, the paper transforms the accumulated generating sequence of original time sequence; (2) to make the model meet the variation characteristics of data, the paper extends the grey action of traditional GM(1, 1) model; (3) to avoid big average simulation or prediction relative error of model, the paper considers the minimum of the maximum of the two errors as the optimization objective function. The new extended grey model is called the GM(1, 1, exp × sin, exp × cos) model. The paper uses an improved particle swarm optimization (PSO) algorithm for the parameter optimization of GM(1, 1, exp × sin, exp × cos) model and thus improves the model's convergence rate and precision. According to the model and method proposed, the paper builds a GM(1, 1, exp × sin, exp × cos) model for China's GDP per capita. Results show that the model has high precision. [ABSTRACT FROM AUTHOR]

The dynamic effect is a very important issue widely debated by scholars when studying the genetic and disaster-causing mechanisms of earthquake-triggered landslides. First, the dynamic effect mechanism and phenomena of earthquake-triggered landslides were summarized in this paper. Then, the primary types of dynamic effects were further used to interpret the Mogangling landslide in Moxi Town of Luding County, China. A field investigation, remote sensing, numerical calculation and theoretical analysis were carried out to illustrate the failure mechanism of slope rock masses affected by earthquakes. The interaction between seismic waves and slope rock masses and the induced dynamic effect of slope rock masses were primarily accounted for in the analysis. The slope topography, rock mass weathering and unloading characteristics, river erosion, regional seismogenic structure, and rock mass structure characteristics were also discussed. The results showed that the formation of the Mogangling landslide was mainly related to the high amplification effect of seismic acceleration and back slope effects, interface dynamic stress effects, and double-sided slope effects of seismic waves caused by the catastrophic Ms 7.75 Moxi Earthquake in 1786. The principles for the site and route selection of large-scale infrastructure in the planning stage and the scientific prevention of seismic geological disasters were proposed on the basis of the dynamic effect of earthquake-induced landslides. [ABSTRACT FROM AUTHOR]