Abstract A Bayes discriminant model for water source identification of kasrt cave in Xulingguan tunnel is established using 53 water samples of 9 dynamic monitoring points. It chooses hydrochemical major constituents as discriminant index and bases on Bayes discrimninant theory. 51 of all the samples are classified correctly with 96.23% accuracy rate, when the model is adopted to test the training samples, indicating that this model has perfect performance and good generalization ability. P1m+q aquifer is identified as the water source of RQ1 and RQ2 in No. 1 karst cave when using the above Bayes model, combining with its flow characteristic, isotopic analysis result and development position. According to the results, the water of No. 1 karst cave is suggested to be drained from its own channel.
Abstract：
A Bayes discriminant model for water source identification of kasrt cave in Xulingguan tunnel is established using 53 water samples of 9 dynamic monitoring points. It chooses hydrochemical major constituents as discriminant index and bases on Bayes discrimninant theory. 51 of all the samples are classified correctly with 96.23% accuracy rate, when the model is adopted to test the training samples, indicating that this model has perfect performance and good generalization ability. P1m+q aquifer is identified as the water source of RQ1 and RQ2 in No. 1 karst cave when using the above Bayes model, combining with its flow characteristic, isotopic analysis result and development position. According to the results, the water of No. 1 karst cave is suggested to be drained from its own channel.
LIU Jian,
LIU Dan
.Water Source Identification of Karst Cave in Xulingguan Tunnel Based on Bayes Discriminant Analysis[J] MODERN TUNNELLING TECHNOLOGY, 2012,V49(1): 72-77
2012, Vol. 49 