5results about How to "Improve exception handling efficiency" patented technology

The application provides a multi-agent cooperative task state management and abnormal backtracking method and system, relates to the technical field of artificial intelligence, and comprises the following steps: obtaining interaction data, state data and execution logs, constructing an initial task knowledge graph based on an ontology model, establishing a bidirectional causal chain by using a Bayesian network to form a dynamic knowledge graph, analyzing state migration rules when an abnormality is detected, identifying a propagation node, constructing an abnormal propagation subgraph, generating an influence chain, determining a recovery priority and triggering state rollback. The method can quickly trace the abnormal source, effectively control abnormal diffusion, and improve system robustness and task recovery efficiency.

The invention belongs to the technical field of e-commerce informatization, and particularly relates to an informatization-based cross-border e-commerce business intelligent tracking management method and system, and the method comprises the steps: responding to business abnormality detection, and scheduling participants with independent data sovereignty; building a cross-participant federal causal atlas through a federal causal discovery module in a collaborative manner; dynamically configuring the business digital twinning model based on the causal relationship in the atlas, and generating a causal constraint enhanced digital twinning instance; encoding map structure features in a deep reinforcement learning agent, and taking an enhanced digital twinborn instance as an environment; and the operation agent outputs an intervention action sequence. According to the method, the problems of cross-border e-commerce data island, decision lag and lack of intelligent support are solved, privacy protection collaborative analysis of cross-domain data and active prediction and interpretable intelligent decision based on a causal mechanism are realized, and the overall toughness and decision efficiency of a supply chain are improved.

The embodiment of the invention discloses a parking fee reduction and remission abnormity processing method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining order information of a to-be-detected order; according to the order information and a pre-trained exception recognition engine, determining an exception reason of the to-be-detected order; and according to a preset processing mode corresponding to the abnormity reason, executing an abnormity processing flow, an abnormity identification engine performing multi-dimensional analysis on order information of a historical order to determine, and the historical order being a charging order which occurs before the to-be-detected order and is abnormal in parking fee reduction and remission. Therefore, according to the method, automatic identification of the abnormal reason of the to-be-detected order and timely processing of the order reduction and remission abnormity are realized based on the abnormity identification engine, and the abnormal reason identification and abnormity processing efficiency during parking fee reduction and remission abnormity can be improved.

The present application belongs to the field of temperature and pressure reducing equipment, and relates to data analysis technology, and is used for solving the problem that the temperature and pressure reducing actuator in the prior art cannot monitor parameters such as deformation and cracks of the pipeline thereof during operation, and in particular relates to a bimodal control box for a temperature and pressure reducing actuator and a control system thereof, which comprises a processor, the processor being communicatively connected with a deformation monitoring module, a crack monitoring module, an operation evaluation module and a storage module; the deformation monitoring module is used for monitoring the deformation of the pipeline of the temperature and pressure reducing actuator; a monitoring period is generated, the monitoring period is divided into a plurality of monitoring time periods, the pipeline of the temperature and pressure reducing actuator is marked as a monitoring object, and the deformation coefficient of the monitoring object in the monitoring time period is obtained; the present application can monitor the deformation of the pipeline of the temperature and pressure reducing actuator, so that the deformation coefficient is obtained through numerical calculation according to the deviation values of all monitoring points, and the deformation state of the monitoring object in the monitoring time period is fed back through the deformation coefficient.

The invention discloses a time-space correlation analysis-based single power battery anomaly detection method and system, and belongs to the field of battery anomaly detection. The method comprises the following steps: collecting state data of a single battery; the collected data are preprocessed; correcting the preprocessed data through a preset dynamic environment compensation model; performing space-time correlation feature extraction on the corrected data; meanwhile, according to the corrected data, self-adaptive threshold values of various battery monomer parameters are calculated through a machine learning model; performing abnormal mode matching in a preset abnormal mode feature library according to the time-space correlation features; and performing anomaly detection and graded early warning in combination with the space-time correlation features and the adaptive threshold. The abnormal detection accuracy of the single power battery is improved, and the safety and reliability of the battery system are improved.