Analysis and Evaluation Research on Road Damage of Post-Earthquake Using Generalized Information Diffusion Model

Abstract

Timely and effective estimation of road damage degree can provide scientific and reasonable support for emergency rescue. In this paper, we shall first briefly introduced a generalized information diffusion model to evaluate the damage degree of roads. Since the road earthquake loss system is influenced by many factors, which has some characters such as smaller and random sample size, the excessive features and nonlinear, etc. Based on it, several measured indicators of road damage were selected as key impacting indicators to estimate the failure grade, including the damage degree of road and bridge x1, damage degree of subgrade and pavement x2 and damage degree of roadside environment destruction on road x3. Moreover, the fuzzy diffusion and interpolation mapping for sparse data points has been defined by the fuzzy mapping theory. Next, the heterogeneous information diffusion from limited data point information to its adjacent area points was implemented. In this procedure, the fuzzy approximate reasoning and information centralization of road rupture width are also has been estimated. The numerical results show that the Generalized Information Diffusion (GID) model can reasonably approximate and extend effective information for incomplete data samples, which also can be applied to treat the nonlinear relationship between road damage degree of postearthquake.Finally, an example is given to illustrate the effectiveness and feasibility of the method.

Interpolation of China’s Nearshore Sea Surface Temperature Based on Information Diffusion with Small Sample Sizes

“…Zhang employed an information diffusion model to conduct comprehensive risk assessments of agricultural drought disasters in the main grain-producing areas of Jilin Province, China [10]. Wang utilized a generalized information diffusion model to evaluate and analyze post-earthquake road damage situations [11]. Altogether, the information diffusion model plays a significant role in small-sample risk assessment [12][13].…”