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- W2348666683 abstract "In order to predict the Karst collapse tendency level accurately,the rock quality coefficient,rock mass structure coefficient,ground water coefficient,soil stratum coefficient,landform physiognomy coefficient and environment condition coefficient were determined as the major discriminant factors through analyzing a lot of observation examples.By training twelve observation samples,a classification prediction model for Karst collapse tendency level was built based on FDA method.By SPSS software,four discriminant functions were established for the FDA model.According to the functions,the training samples were differentiated and two prediction samples were predicted.The results show that the comprehensive discriminant efficacy of the first and second discriminant function reaches 100% and meets the need of actual engineering well,and that the return discriminant method is used to differentiate the trained samples and its misjudgment rate is zero,also the prediction results of two prediction samples coincide with the practical results exactly." @default.
- W2348666683 created "2016-06-24" @default.
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- W2348666683 date "2011-01-01" @default.
- W2348666683 modified "2023-09-24" @default.
- W2348666683 title "Classification Prediction of Karst Collapse Tendency Level Based on Fisher Discriminant Analysis Method" @default.
- W2348666683 hasPublicationYear "2011" @default.
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