9 results about "Tree traversal" patented technology

A network device may receive parameters for a probe packet, and may generate the probe packet based on the parameters. The network device may provide the probe packet to multiple ingress packet forwarding components, and may generate probe packet copies at the multiple ingress packet forwarding components. The network device may generate ingress route metadata for the probe packet copies via filters provided in the multiple ingress packet forwarding components, and may provide the probe packet copies to multiple egress packet forwarding components. The network device may generate egress route metadata for the probe packet copies via filters provided in the multiple egress packet forwarding components, and may provide the probe packet copies, the ingress route metadata, and the egress route metadata to an application. The network device may utilize the application to generate a report, and may provide the report for analysis.

This invention relates to the field of data processing technology and discloses a method and system for order management in customized rice cake production. The method includes: generating a corresponding production task set based on the resource and process parameter dependencies of the order; encapsulating the process sequence and production resources in the task set into the root node of the order; extracting its unassigned processes; enumerating available resources to construct a resource state tree; traversing the path from the root node to the leaf node in the tree; accumulating the time cost of each node to obtain the total cost; selecting the path with the minimum total time cost as the optimal path node sequence; updating the order status accordingly; and finally outputting the order's driving management data. This process optimizes production scheduling through dynamic matching of resources and processes; this invention can improve the management accuracy and production execution efficiency of customized rice cake production orders.

The application provides a query expression automatic generation device for a search system, characterized by the following steps: selecting a training data set; preprocessing a query word; determining a query domain; generating a query condition; and constructing a query word tree according to the query condition, the query domain and information of an information source. The query expression automatic generation device for the search system can automatically learn and group by using a machine in the construction process of the query word tree, can realize automation, can construct a query expression based on the query word tree, can convert the construction problem of the query expression into a tree traversal problem, and greatly simplifies operation.

The application provides a glass deep processing process analysis system and method based on AI cloud data, the method comprising: performing semantic analysis and structured packaging on the obtained process query text in combination with a glass industry term library to obtain a structured query instruction; performing database table association, list matching and context enhancement on the structured query instruction based on a bidirectional mode link algorithm, and performing sentence optimization on the matching result after context enhancement based on a binary selection strategy to obtain a primary query sentence; performing logical self-correction on the primary query sentence based on a multi-round syntax tree traversal method to obtain a database query sentence; querying the original data set from the glass processing database by using the database query sentence, and performing multi-dimensional data analysis on the original data set based on a dynamic threshold anomaly detection algorithm and a mutual information algorithm to obtain an analysis result set; and generating an interactive report according to the analysis result set.

The application discloses a landslide susceptibility intelligent evaluation method based on feature stability guidance and cost adaptive tightening, which comprises the following steps: collecting and normalizing landslide sample data; calculating feature importance and sorting by random forest; traversing feature subset scale by gradient boosting tree, determining global optimal subset by cross-validation AUC; calculating feature stability coefficient, generating tightening priority queue; trying to remove features in turn by asymmetric cost-sensitive AUC measurement, and accepting if the performance decline is not more than the threshold; adaptively adjusting the threshold and re-tightening after the confrontation verification, recording the historical optimal subset; retraining the model to output the landslide probability. The application realizes feature stability guidance, asymmetric cost-sensitive tightening and self-evolution threshold closed loop, reduces redundant features while maintaining accuracy, and improves generalization and interpretability. The measured AUC reaches 0.897, which is 3.2% higher than that of the traditional GBDT, and the feature is reduced by 40%.

This application relates to a source coding method, apparatus, device, and medium. The method includes: obtaining the target bit probability and the source symbol probability of each source symbol; constructing a binary prefix code tree by recursively partitioning the Huffman algorithm based on the target bit probability and the source symbol probabilities; traversing the binary prefix code tree to obtain the binary prefix code of each source symbol, and constructing a Huffman codebook based on the binary prefix codes of each source symbol; and mapping the source symbol sequence to a compressed binary bit stream based on the Huffman codebook. This method enables probability shaping during source coding, thereby reducing efficiency losses.

In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a computing device. The computing device initiates discovery of Redfish-capable nodes in a data center. The computing device performs a Redfish tree walk for each discovered node to collect resource information. The computing device parses the collected resource information to generate cleaned data by removing non-essential data. The computing device stores the cleaned data in a database. The computing device provides a query interface for accessing resources across the data center using keyword-based searches.

The present disclosure provides a recall processing method and device, electronic equipment and computer readable storage medium, the method comprises: determining a and or not expression based on input information; establishing an inverted index according to the information set of the live room to be recalled; determining a target and or not merge tree based on the inverted index and the and or not expression; determining a minimum merge subtree based on the target and or not merge tree; determining the target live room to be recalled by traversing the minimum merge subtree. According to the recall processing method of the present disclosure, the purpose of obtaining recall results can be achieved without traversing the linked list completely, and the live room meeting the recall conditions can be efficiently and quickly retrieved.

The present application relates to big data processing technical field, especially to a kind of new energy system's full life cycle data analysis method and system, comprising: obtaining full life cycle data construction index key, generates initial B+ tree;Traversal leaf node sequence, try and incorporate to form test splicing target data set, calculate data similarity and merge to generate large granularity leaf node and reconstruct new B+ tree;Parse data retrieval request, based on each class sensor parameter sequence of target device set Average correlation and peak value synchronization rate are calculated, summing to obtain cross-device coupling coefficient;Extract discrete query time point to calculate local time span difference to obtain time distribution aggregation degree;Time distribution aggregation degree and cross-device coupling coefficient are weighted and fused to obtain adaptive optimization score, select optimal index strategy to extract target full life cycle data, obtain running state evaluation result.The present application effectively improves the retrieval efficiency of complex query.