2results about How to "Guaranteed accuracy and reliability" patented technology

The invention relates to the technical field of coal bed gas exploration, in particular to a visualization method for simulating micro occurrence and flowing of deep coal rock gas. According to the visualization method for simulating the microscopic occurrence and flowing of the deep coal rock gas, in-situ pressure, temperature and crustal stress parameters of a preset burial depth are estimated, and simulation boundary conditions including the in-situ pressure, temperature and crustal stress parameters are loaded into a molecular model, so that a simulation boundary consistent with an actual deep environment is directly established, and the real deep coal rock gas microcosmic occurrence and flowing are simulated. And the technical bottleneck that in-situ complex conditions cannot be reproduced in a laboratory is solved, so that a simulation result is closer to engineering practice, and the accuracy and reliability of a visual result are ensured. According to the visualization method, calculation of free-state methane is introduced in a targeted mode, so that the method is more adaptive to the characteristic that the proportion of the free-state methane in the deep coal and rock gas is high, and it is guaranteed that the visualization method can more accurately simulate the actual situation of the deep coal and rock gas.

This application provides a request rewriting method, apparatus, device, and computer storage medium. The method includes: acquiring an information query request for implementing model training operations; determining the rewriting category to which the information query request belongs; determining positive and negative rewriting samples corresponding to the information query request based on the rewriting category; training a model based on the information query request, positive and negative rewriting samples to obtain a request rewriting model; and performing a request rewriting operation using the request rewriting model. In this embodiment, different sample selection strategies are used to perform sample selection operations based on different rewriting categories to which the information query request belongs. Then, model training is performed based on the positive and negative rewriting samples selected in the selection operation to obtain the request rewriting model, thereby ensuring the quality and effectiveness of the model training operation. Subsequently, the request rewriting operation is performed based on the request rewriting model, thus effectively ensuring the quality and efficiency of the request rewriting operation.