Uniaxial strength forecasting method for jointed rock mass

The invention discloses a uniaxial strength forecasting method for a jointed rock mass. The uniaxial strength forecasting method comprises the following steps: (1) determining respective main factors; (2) constructing a neural network learning sample and a test sample; (3) setting an error threshold value; (4) performing repeated reciprocating training on a BP neural network model until an error between an output forecast value and a desired value is smaller than the set threshold value, thus obtaining a relatively reasonable BP neural network model after training; and (5) inputting the respective main factors, which affect a uniaxial compressive strength value, of a jointed rock mass test piece into the relatively reasonable BP neural network model for forecasting the uniaxial compressive strength of the jointed rock mass, thus obtaining the uniaxial compressive strength value of the jointed rock mass test piece. According to the uniaxial strength forecasting method for the jointed rock mass based on the BP neural network model, complicated parameter solving of the jointed rock mass can be avoided, and the uniaxial compressive strength value of the jointed rock mass can be accurately and quickly obtained; meanwhile, the requirement of a uniaxial compressive strength test for the jointed rock mass can be met.