摘要
Abstract
Soil stratification is a critical foundation in engineering geological investigation.The alluvial plain was characterized by complex sedimentary environment,poor stratum continuity and well-developed transition zones.Different engineers may draw reasonable judgments that comply with specifications yet yield divergent conclusions based on experience,which would introduce subjective ambiguity in stratification results.A weighted K-means clustering method incorporating a hybrid weighting strategy was proposed to objectivize the stratification process and quantify decision-making.Based on the survey data from a plain reservoir in the lower Yellow River,the authors selected 8 independent feature indicators from 18 geotechnical test parameters,that is dry density(ρd),liquid limit(wL),plastic limit(wp),mean particle size(d50),internal friction angle(φ),cohesion(c),com-pression coefficient(a1-2),and sampling elevation(SE).After KMO-Bartlett suitability verification and Z-score standardization,a hybrid weighting strategy integrating the Analytic Hierarchy Process(AHP),expert sur-vey,and Principal Component Analysis(PCA)was employed.The optimal subjective-objective weight ratio(6∶4)was determined through sensitivity analysis.A weighted Euclidean distance clustering model was subse-quently constructed,and the optimal number of strata(K=6)were identified using the elbow method.Validation results demonstrated that the stratification results by this method exhibited strong agreement with comprehensive expert judgments(Kappa=0.836),and it could achieve fine identification of stratigraphic transition zones(86.7%accuracy),confirming the effectiveness of the hybrid weighting strategy.This research provided a data-driven,reproducible,and objective decision-support tool for soil stratification in alluvial plains,offering technical support for standardizing stratification schemes.关键词
冲积平原/土体分层/聚类分析/加权 K-means/混合赋权/工程地质勘察Key words
alluvial plain/soil stratification/clustering analysis/weighted K-means/hybrid weighting/engi-neering geological investigation分类
天文与地球科学
