4results about How to "Avoid complex calculations" patented technology

The application discloses a kind of quick cross path scheduling methods of inter-city area customized public transport system, the shortest distance method between regions is used to build start point area end point set and end point area start point set, to generate start point area travel sequence Yo by insertion method, to generate end point area travel sequence Yd by insertion method, then the Yo and Yd are optimized by quick exchange method, finally the minimum value of start point × Yo × Yd is solved, which is the final inter-city area customized public transport system target path, with the shortest bus travel distance as the target;The method does not use probability distribution, effectively avoids the fluctuation of the final path result, according to the characteristics that the distance between nodes in different regions is much larger than the distance between nodes in the same region, the inter-regional traffic node set is established, and it is used as the end point of the start point region and the start point of the end point region, respectively, to maximize the range of optimal solution, effectively reducing the overall calculation scale.

This application discloses a method for determining a display mode and a vehicle, relating to the field of vehicle control technology. The method includes: determining the first importance of a vehicle function to be displayed to the occupants based on their attribute information; determining the second importance of the vehicle function to the current driving process based on the vehicle's current driving scenario; determining the vehicle's usage preference for the vehicle function based on its historical usage information; and fusing the first importance, second importance, and usage preference levels to determine the target display mode corresponding to the vehicle function based on the fusion processing result. The technical solution of this application embodiment can make the target display mode more closely match the actual driving conditions of the vehicle and the actual needs of the occupants, thereby improving the convenience and experience of occupants using vehicle functions.

This invention discloses a machine learning-based method and system for predicting the production capacity of gas-water two-phase gas in tight sandstone. The method includes: constructing production capacity prediction models for different well types using an artificial neural network; inputting data such as critical flow saturation, water saturation, water phase relative permeability curve index, starting pressure gradient, permeability, reservoir thickness, fracture conductivity, fracture length, cluster number, and stress sensitivity coefficient as input variables into the production capacity prediction model, and using cumulative gas and water production as output variables. The input variables are then imported into the corresponding production capacity prediction model for different well types to obtain the cumulative gas and water production for each well type. This method uses an artificial neural network to construct a production capacity prediction model to predict the cumulative gas and water production in tight sandstone, achieving rapid and accurate prediction of the production capacity of the gas-water two-phase gas in tight sandstone, avoiding complex calculation processes, and reducing computation time and production costs.