It is of great theoretical and practical significance to utilize a large number of landslide disaster datasets for statistical analysis and to establish a probabilistic prediction model for typhoon rainstorm-induced landslides.Derivation of an incremental Bayesian classification prediction probabilistic model for landslides based on continuous type variables based on Bayesian theory and incremental learning theory.A dataset of 539 typhoon storm-type landslides from previ-ous years in the study area was employed as study samples for joint spatial and temporal prediction forecasting.Some landslides in the study area were selected as samples to be predicted to test the learning performance and prediction ac-curacy of the model.The results are as follows.The model is self-updating and achieves continuity in time,capturing the effects of small changes in continuous variables on parameter learning and updating.Under the current conditions of learning samples,the incremental prediction model has a more complete and generalized model structure due to the in-clusion of samples from the part of the test tuple.The overall prediction accuracy of the model reaches 75%,and it can better realize the joint forecast of disasters in time and space.
关键词
影响因子/滑坡/贝叶斯理论/概率预测模型/时空联合预报
Key words
impact factor/landslide/Bayesian formulation/probabilistic prediction models/integrating time and space forecast
维普
万方数据