14 results about "Incremental search" patented technology

An application receives user input of a search query by way of a search interface. The application determines a task based on the search query, and divides the task into a plurality of sub-tasks, at least some of the plurality of sub-tasks divided for parallel processing by different compute components. The application receives publication of partial results from the different compute components as those partial results are completed by their respective compute components. The application inputs the partial results into a reducer to create an aggregate partial result, and generates for display the aggregate partial result within the search interface, where the aggregate partial result is updated in real time as further partial results are published.

A method, a computer readable medium, and an apparatus for audio error concealment are provided. The apparatus may receive a plurality of audio frames. The apparatus may receive a first audio frame after the receiving of the plurality of audio frames. The apparatus may detect a second audio frame being lost in transmission. The second audio frame is transmitted after the plurality of audio frames and before the first audio frame. The apparatus may identify an audio segment within the plurality of audio frames that best matches a reference audio pattern of the plurality of audio frames. The identified audio segment may be received before a last audio frame of the plurality of audio frames. The apparatus may reconstruct the second audio frame based on audio data received subsequent to the identified audio segment.

The application relates to a large model-based code search method, which comprises the following steps: obtaining a target code library to be searched; performing reasoning analysis on code segments in the code library through a code understanding intelligent agent, taking extracted semantic information as IOF data; converting the IOF data into a feature vector, storing the feature vector into an initialized vector database, and constructing a mapping index of an IOF field to an original code segment; analyzing the semantics of a user query through a query understanding intelligent agent and generating initial search metadata; performing preliminary search in the vector database based on the search metadata to obtain a candidate list; constructing an iterative search loop containing an evaluation intelligent agent, the evaluation intelligent agent judging the matching degree of the current candidate list and the query, if a termination condition is not reached, re-generating search metadata and performing incremental search; when the termination condition is met, performing semantic reordering on the accumulated candidate IOF data through a reordering intelligent agent, and finally outputting recommended code segment results.

The present invention proposes a mobile robot motion planning method based on obstacle-surrounding path optimization and biased sampling, comprising the following steps: step S1, constructing a node set, an edge set, and a sampling point set not added to the search tree; step S2, constructing a queue and; step S3, if the processing of the batch of sampling points is completed, pruning is performed; step S4, if the processing of the batch of sampling points is completed, biased sampling is performed; step S5, if the optimal value of the queue is not greater than the optimal value of the queue, edge pre-expansion is performed; step S6, removing the edge with the minimum value; step S7, if the edge helps to improve the path quality, it will be added to the search tree; step S8, when the path meets the requirements, the path solution is returned, otherwise it returns to step S3 to continue; step S9, completing the path planning; compared with BIT*, the algorithm of the present invention can converge to the optimal solution faster and improve the exploration efficiency, and has advantages in incremental search path planning.

This disclosure belongs to the field of power system technology, specifically relating to a feature selection and integration method and system for large-scale wind power grid connection, including: acquiring multi-dimensional feature data containing wind power grid connection response features; performing incremental search on the acquired multi-dimensional data features based on preset optimal correlation and redundancy evaluation criteria to construct multiple nested candidate feature subsets; calculating the classification accuracy of the constructed multiple nested candidate feature subsets; recording the candidate feature subset with the highest classification accuracy, verifying the dimension of the recorded candidate feature subset, obtaining the optimal candidate feature subset, and completing feature selection and integration.

An application receives user input of a search query by way of a search interface. The application determines a task based on the search query, and divides the task into a plurality of sub-tasks, at least some of the plurality of sub-tasks divided for parallel processing by different compute components. The application receives publication of partial results from the different compute components as those partial results are completed by their respective compute components. The application inputs the partial results into a reducer to create an aggregate partial result, and generates for display the aggregate partial result within the search interface, where the aggregate partial result is updated in real time as further partial results are published.

The invention discloses a vehicle semantic map matching and positioning method and device based on space-based remote sensing images, and belongs to the field of vehicle autonomous positioning. The method comprises the following steps: firstly, performing multi-scale cutting on a space-based remote sensing image to construct an image pyramid, identifying roads and buildings by using a deep learning model, and constructing a lightweight semantic map through vectorization extraction; an upper layer matches a vehicle track with a road center line vector through adaptive sliding window matching, and a track feature detection function and an incremental search mechanism are introduced to realize rapid coarse positioning; and the lower layer takes the coarse positioning result as the center, the laser point cloud is matched with the building contour vector by adopting a simplified ICP algorithm in the candidate area, only translation is estimated by fixed rotation, and finally, RANSAC conversion is performed once to realize accurate positioning. According to the method, the problem of quick and accurate positioning in a non-cooperative area, a strange scene and a satellite denial condition is solved.

The application discloses a kind of power system transient voltage stability evaluation method based on intelligent feature selection belonging to the technical field of power system transient voltage stability evaluation.The method comprises: based on SMRMR, the feature is initially screened;Convert mutual information value into SU value, obtain the redundancy between any two features and the correlation between each feature and category based on SU value, then use incremental search to select the approximate optimal feature defined by MRMR;Based on QIBSO, the approximate optimal feature selected in step 1 is searched and selected;Based on the composite screening framework, the transient voltage stability is evaluated;From the time sequence dimension and the space dimension, the original feature is constructed, and the feature subset selected in step 2 is used as the input of machine learning model to evaluate the power system transient voltage stability online.The method can greatly reduce the dimension of feature subset, improve the evaluation accuracy and reduce the calculation time of online evaluation.

The application relates to a transformer oil paper insulation fault diagnosis method, and the specific steps comprise the following steps: establishing an initial feature space and calculating the intra-group redundancy and inter-group correlation of the initial feature space; adopting an incremental search optimization algorithm to calculate the feature quantity sorting of the maximum correlation and minimum redundancy under a standard function difference, eliminating the features within a preset range at the rear of the feature merit sorting, obtaining a first feature selection threshold m1 and a first feature space; evaluating the importance of the feature quantity of the first feature space through a pre-trained GBDT model, eliminating the feature quantity with low importance, obtaining a second feature selection threshold m2 and a second feature space.

This invention discloses a dynamic collision avoidance path planning method and system for multi-robot task allocation, relating to the field of robotics. The method includes: acquiring multimodal perception data; constructing a sensory control spatiotemporal knowledge graph, using a graph neural network to predict infection risk, and generating a dynamic risk heatmap; based on the heatmap, using multi-agent reinforcement learning to optimize task allocation and outputting the execution sequence of each robot; fusing local sensor and global dynamic obstacle information to construct a spatiotemporal grid map, redefining costs based on risk, and planning paths using incremental search to control robot movement. This addresses the technical problem of simultaneously achieving efficient collaborative task allocation, real-time dynamic collision avoidance, and proactive infection risk avoidance for multiple robots in complex, dynamic hospital environments with strict infection control requirements. It achieves the technical effect of improving global task execution efficiency, reducing human-robot-object collision risks, and enhancing hospital infection control capabilities through the fusion of sensory control spatiotemporal graphs and reinforcement learning.

The invention discloses a biased VSP missing data reconstruction method and device, electronic equipment and a storage medium. The method comprises the following steps: sorting biased VSP data into a plurality of common detection point gathers; selecting a common detection point gather, giving an initial shot point coordinate position and a shot point coordinate increment, searching for header coordinate information of the common detection point gather, and constructing a sparse sampling operator; tau-p transformation is adopted as a reconstruction operator, and irregular missing traces are reconstructed through convex set projection iterative calculation; and repeating the steps S2-S3 to complete the reconstruction of the irregular missing channels of the rest common detection point gathers. According to the method, data can be effectively complemented, and the influence of insufficient underground illumination caused by missing data can be relieved.

The invention relates to the field of dynamic search, and discloses a webpage dynamic search method and device and a storage medium. The method comprises the following steps: receiving a search keyword input by a user; judging whether the typing interval duration is greater than a preset minimum time threshold value or not; if the time duration is not greater than the preset minimum time threshold, continuously receiving search keywords input by the user, and judging whether the overall input time duration is greater than a preset maximum waiting threshold; if not, re-judging whether the typing interval duration is greater than the preset minimum time threshold or not; if the waiting threshold value is greater than the preset maximum waiting threshold value, generating a search request based on a preset Vue component and all search keywords; performing search processing on the search request to obtain incremental search data; and rendering and updating the preset front-end page to generate a new front-end page. According to the embodiment of the invention, the system resource consumption is reduced, and the stability in various front-end environments is improved.

The invention provides a medicine logistics quality management system and method, and relates to the technical field of logistics quality management, and the method comprises the steps: obtaining a target transportation node of medicine logistics transportation, the real-time state data of a transported medicine, and target transportation state standard data; based on a reverse incremental search algorithm, according to the target transportation node of the corresponding medicine logistics transportation, obtaining a plurality of initial transportation paths of transportation; according to the real-time state data and the target transportation state standard data, obtaining a transportation medicine state evaluation index corresponding to the initial transportation path; a plurality of initial transportation paths corresponding to medicine logistics transportation are further optimized and split according to the transported medicine state evaluation index, and a main transportation scheme and a standby transportation scheme corresponding to the medicine logistics transportation are obtained; according to an actual transportation scheme, logistics transportation quality indexes of different nodes of the corresponding transportation path are calculated, and according to the logistics transportation quality indexes, the corresponding medicine logistics transportation state is evaluated.

An application receives user input of a search query by way of a search interface. The application determines a task based on the search query, and divides the task into a plurality of sub-tasks, at least some of the plurality of sub-tasks divided for parallel processing by different compute components. The application receives publication of partial results from the different compute components as those partial results are completed by their respective compute components. The application inputs the partial results into a reducer to create an aggregate partial result, and generates for display the aggregate partial result within the search interface, where the aggregate partial result is updated in real time as further partial results are published.