4results about How to "Improve refined management" patented technology

The application discloses a Chinese sturgeon breeding behavior prediction method, which comprises the following steps: step 1, obtaining and uniformly formatting Chinese sturgeon breeding field monitoring data; step 2, calculating Chinese sturgeon breeding behavior evaluation indexes; step 3, constructing a Chinese sturgeon breeding behavior evaluation model coupled with multiple factors; step 4, identifying key factors and threshold intervals affecting Chinese sturgeon breeding behavior; and step 5, predicting the evolution law of Chinese sturgeon breeding activities under the comprehensive action of multiple factors and putting forward breeding field operation scheduling and protection and restoration strategies. The application solves the problems of the existing Chinese sturgeon breeding monitoring and evaluation means, such as difficulty in unifying multiple source data, difficulty in quantitatively evaluating breeding behavior, difficulty in identifying key factor thresholds, and insufficient prediction and decision support.

The present application provides a kind of based on molecular management's radial flow fixed bed reactor device potential analysis method, the method comprises: obtaining molecular level reaction process model;Molecular level reaction process model includes molecular composition model, molecular reaction dynamics model, catalyst deactivation model and radial flow fixed bed reactor model;Using molecular level reaction process model, the reaction process of actual radial flow fixed bed reactor device is simulated, and product composition property and device energy consumption prediction result are obtained;Based on prediction result, the production potential of actual radial flow fixed bed reactor device is quantitatively analyzed, and quantitative analysis result is obtained, to based on quantitative analysis result and production target, the process parameters of actual radial flow fixed bed reactor device are adjusted and optimized.The present application can improve the raw material utilization rate and product value of production device, provide guidance for the production strategy of device upgrading and efficiency improvement, and be beneficial to improve the scientific and fine management of production.

The present application relates to the technical field of power load prediction, in particular to a power load prediction method, system and scheduling method. Based on the processing of regional historical power consumption data, user historical power consumption data and user historical power consumption sequence, the power load prediction method can realize the acquisition of cycle prediction, trend prediction and fluctuation prediction by constructing user cycle model, user trend model and user fluctuation model, and then complete the power load prediction of the to-be-predicted region. The power load prediction method does not need to consider parameters such as regional economic framework and regional environmental change, but returns to the essence that the user is the minimum power consumption unit and the daily power consumption behavior of each user is related to the work and rest rules, so it can be better applied to the power load prediction of smaller areas, and is conducive to improving the fine management of current power load prediction.

The application belongs to the field of airport management, and relates to a smart video inspection method and system based on a multi-modal large model, which comprises the following steps: 1, based on unstructured text in airport data, a structured knowledge graph is constructed, and a high-dimensional semantic vector is obtained based on nodes of the structured knowledge graph; 2, feature extraction is performed on various data including monitoring video to generate multi-modal joint feature representation; the multi-modal joint feature representation comprises space-time information and rule context; 3, based on the high-dimensional semantic vector and the multi-modal joint feature representation, it is judged whether an abnormal event occurs in the terminal building; 4, if an abnormal event occurs, a structured instruction is generated based on the abnormal event, and the terminal building is optimized in a closed loop based on the structured instruction; based on the existing video monitoring environment and data of the airport, an integrated intelligent system is provided for intelligent inspection of the terminal building, and automation, refinement and closed-loop management of the inspection are realized.