3results about How to "Accurate Classification and Identification" patented technology

The application discloses an environmental monitoring data processing method and system based on pollution discharge permission execution report, and belongs to the field of environmental monitoring data processing.The method comprises the following steps: obtaining multi-source environmental data flow for preprocessing and space-time alignment to generate a first data set; extracting a constraint condition field, and instantiating a dynamic quality control rule library based on the constraint condition field and working condition state information; adopting double-layer discrimination logic to process the first data set to generate a second data set after quality control, so as to distinguish between false abnormalities and real emission over-standard caused by equipment drift; taking effective data in the second data set after quality control as input, performing emission accounting operation, and outputting a third data set containing a compliance rate and a compliance margin rate; performing memory mapping corresponding to the third data set and an execution report template, and executing a three-level verification control flow to generate a correction suggestion table based on the verification result.The application reduces the misjudgment rate of abnormal data and improves the accuracy of quality control.

The application relates to a 5G environment intelligent pathological auxiliary diagnosis system and relates to the technical field of pathological section diagnosis, in particular to a 5G environment intelligent pathological auxiliary diagnosis system. The application aims to solve the problem that the generalization performance of an existing AI auxiliary pathological diagnosis model is limited and the system cannot maintain the recognition accuracy of pathological digital images. The 5G environment intelligent pathological auxiliary diagnosis system comprises a CT image acquisition module, a CT image processing module, a deep learning module and a recognition module. The CT image acquisition module is used for acquiring CT images of patients by a CT scanner. The CT image processing module is used for processing the acquired CT images of patients to obtain processed CT images of patients, and the processed CT images of patients are used as a training set. The deep learning module is used for constructing a deep learning model and obtaining a trained deep learning model based on the training set. The recognition module is used for recognizing the processed CT images of patients to be measured based on the trained deep learning model.

The embodiment of the application discloses a control method and device of a fuel cell turbo-compressor. The method comprises the following steps: identifying a current working condition according to an operating parameter; in a slow load reduction working condition, slowly opening a bypass valve, slowly closing a variable nozzle ring, reducing a high-speed drive motor speed and a throttle opening degree, maintaining a compressor outlet flow rate not lower than a minimum safe flow rate, recovering turbine residual pressure energy and motor rotor kinetic energy; in a rapid load reduction working condition, quickly opening the bypass valve, quickly closing the variable nozzle ring, reducing the high-speed drive motor speed and the throttle opening degree, maintaining the compressor outlet flow rate not lower than the minimum safe flow rate, recovering the turbine residual pressure energy and the motor rotor kinetic energy; in an emergency shutdown working condition, fully closing the variable nozzle ring, fully opening the bypass valve, idling the high-speed drive motor, keeping the throttle at a purge opening degree and stopping the system after the purge is completed, so that on-line surge suppression, pressure overshoot control and energy recovery are coordinated, and the system safety and energy utilization rate are improved.