Fuzzy inference-based approach to the mining-induced pipeline failure estimation

Natural Hazards - The correct evaluation of failure hazard in water and gas supply pipelines has been a great problem in areas which are subject to considerable surface movements. The complexity of...     

Classification and regression tree theory application for assessment of building damage caused by surface deformation

A framework of applying the classification and regression tree theory (CART) for assessing the concrete building damage, caused by surface deformation, is proposed. The prognosis methods used for approximated building hazard estimation caused by continuous deformation are unsatisfactory. Variable local soil condition, changing intensity of the continuous deformation and variable resistance of the concrete buildings require the prognosis method adapted to the local condition. Terrains intensely induced by surface deformation are build-up with hundreds of building, so the method of their hazard estimation needs to be approximated and relatively fast. Therefore, promising might be addressing problems of reliable building damage risk assessment by application of classification and regression tree. The presented method based on the classification and regression tree theory enables to establish the most significant risk factors causing the building damage. Chosen risk factors underlie foundation for the concrete building damage prognosis method, which was caused by the surface continuous deformation. The established method enabled to assess the severity of building damage and was adapted to the local condition. High accuracy of shown approach is validated based on the independent data set of the buildings from the similar region. The research presented introduces the CART to determination of the risk of building damage with the emphasis on the grade of the building damage. Since presented method bases on the observations of the damages from the previous subsidence, the method might be applied to any local condition, where the previous subsidence is known.