5results about How to "Improve update process" patented technology

This invention discloses a fluid flow drag-reducing electrolyzer, comprising an electrolyzer frame and two electrodes, two guide plates, and a diaphragm installed and tightly fitted together within the frame. The electrolyzer frame has an inlet at its bottom and an outlet at its top. The two electrodes are symmetrically distributed on both sides of the diaphragm; each electrode is flattened by rolling. The two guide plates are symmetrically distributed on both sides of the diaphragm and located outside the corresponding electrodes. Each guide plate has multiple guide grooves arranged radially along its diagonal and parallel lines near the corresponding electrode. By optimizing the electrode thickness and its internal fluid channel design, this invention reduces the flow resistance of the electrolyte in the electrode region, improves electrolyte renewal efficiency, and enhances the overall operating performance of the electrolyzer.

The application provides an automatic construction and updating method of an industrial manufacturing field large model knowledge base, and belongs to the technical field of industrial artificial intelligence. The application automatically extracts time-overlapping scheduling instance pairs from a task arrangement system scheduling log, and requires that the tool wear segment coding sequences of the two instances in the entire overlapping period are completely consistent, thereby fundamentally avoiding parallel operation mis-matching caused by tool life segment changes, and significantly improving the physical equivalence and reliability of the candidate parallel operation mode. Meanwhile, the rule conflict detection is performed by fusing metadata labels and blood relationship attributes of upstream source entries, so as to identify task source priority, trigger type and other deep business semantic conflicts that cannot be found by traditional methods based on equipment or time dimensions, thereby greatly improving the safety and process compliance of the knowledge base storage content.

The invention discloses a causal federation element reinforcement learning intelligent decision-making method and system for people-benefiting insurance claim settlement, and relates to the field of insurance intelligent claim settlement, and the method comprises the steps: building and adaptively generating a regional causal knowledge graph based on a multi-dimensional policy text; a causal federation element reinforcement learning framework is adopted, through element strategy network initialization, and federation learning is utilized to carry out fine adjustment on small samples in an encryption mode on the premise that data does not go out of a domain, so that local intention recognition model adaptation is realized; according to the claim consultation text of the user, performing intention recognition in combination with neural symbol double-track reasoning and knowledge graph causal chain matching; and training the decision tree, and generating a visual report through anti-factual reasoning to assist in decision making. According to the method, the user intention recognition accuracy and the rule interpretability are enhanced, the response adaptation efficiency of policy dynamic updating is improved, privacy is guaranteed on the premise that data are not out of a domain, small sample learning is achieved, then the people-benefiting insurance claim settlement processing efficiency and the customer satisfaction degree are optimized, and the operation cost is reduced.

The invention relates to the technical field of hard alloy column tooth passivation, and particularly discloses a hard alloy column tooth passivation machine tool which comprises a frame body, an inner cylinder is rotationally arranged at the upper end of the frame body, a cylinder cover is hinged to the upper end of the inner cylinder, a clamping assembly is arranged on the bottom wall of the inner cylinder, a liquid storage tank is arranged on one side of the frame body, and a water pump is arranged on one side of the liquid storage tank. The water inlet end of the water pump communicates with the liquid storage tank, the water outlet end of the water pump communicates with the middle of the bottom wall of the inner cylinder, and an electrolytic passivation mechanism is arranged on the inner bottom wall of the inner cylinder; the cylindrical teeth are placed in the inner cylinder, the clamping assembly can stably clamp the cylindrical teeth, then the cylinder cover is closed, the water pump is started, the water pump on one side of the frame body pumps electrolyte in the liquid storage box into the middle of the bottom wall of the inner cylinder, and at the moment, the electrolytic passivation mechanism can make the polished ends of the cylindrical teeth generate uniform passivation films; and the scraping effect and scraping efficiency of the passivation film are improved, so that the passivation effect of the column teeth is improved, the corrosion resistance of the column teeth is improved, and the service life of the column teeth is prolonged.

This invention discloses a method for dynamic monitoring of forest resources and automatic database updating based on multi-source remote sensing data, belonging to the field of forestry informatization. This method addresses the inconsistencies in resolution, imaging time, and band coverage of multi-source remote sensing data by dynamically generating multi-scale grids to achieve spatial alignment and fusion of data. Utilizing temporal residual discriminative convolutional networks and sparse attention mechanisms, it intelligently detects changes in forest resources, achieving efficient and automatic attribute inversion. The system also includes automatic differential database updates and multi-version management to ensure information synchronization and reliability. Combined with external climate and fire data, it provides alarms for abnormal changes and suggestions for auxiliary intervention, forming an intelligent closed loop from monitoring to management. This method improves the automation, intelligence, and precision of forest resource monitoring and is suitable for large-scale, dynamic forest resource management scenarios.