A Method of Determining Mechanical Indexes of Double Bridge Static CPT Data Based on BP Neural Network
A technology of BP neural network and static penetration testing, which is applied in the fields of foundation structure test, on-site foundation soil survey, foundation structure engineering, etc., can solve the problems of lack of theory and method, difficulty of wide application, and limited scope of application, etc. Achieve the effects of reducing the number of drilling holes, ensuring accuracy and shortening the survey cycle
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[0026] The following describes the implementation of the present invention by specific examples, please refer to figure 1 , a BP neural network-based method for determining the mechanical indexes of static penetration data of twin bridges:
[0027] ①. Collection and arrangement of Shuangqiao static sounding data and soil mechanical indicators: By collecting and arranging engineering geological survey reports and geotechnical test results in typical geological regions in the Yangtze River Delta region, the Shuangqiao static sounding data and The mechanical index of soil, a total of 89 groups, including Q 4 al Clay 28 groups, Q 4 al Silty clay 22 groups, Q 4 al Silt 27 groups, Q 4 al 12 groups of silt;
[0028] ②. Establish the BP neural network prediction model for the determination of the mechanical indicators of the double bridge static penetration penetration: Based on the BP neural network algorithm, use the data information in step ① to establish a prediction model...
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