Model for quality classification of dam foundation rock mass based on Gaussian function weighted KNN algorithm and its application

The geological conditions in the dam area of Baihetan Hydropower Station are very complex, with columnar joints accounting for up to 39.9% of the base area. None of the existing methodologies for rock mass classification are fully suitable for the purposes of quality classification of columnar jointed basalt rock masses. This article addresses the challenges in evaluating and classifying the quality of the columnar jointed basalt rock mass at the dam foundation of the Baihetan Hydropower Station on the Jinsha River. Considering the engineering geological conditions, rock mass characteristics, and environmental context of the Baihetan dam area, evaluation indicators were selected for engineering rock mass quality classification. It also introduces a new rock mass classification model that combines the Gaussian function with the K-nearest neighbor (KNN) classification algorithm. Different weight coefficients were assigned based on the similarity of the samples. Thus, the proposed model was used for the evaluation and classification of the rock mass at the dam foundation in the key area. Ultimately, a new classification tool is proposed for assessing engineering properties of the rock mass at Baihetan dam foundation, providing a viable solution for quality classification in this particular area.