61 results about "Temporal complexity" patented technology

The invention discloses a semi-supervised flotation working condition recognition method based on spatial-temporal feature fusion, and belongs to the field of industrial process monitoring. The method comprises the steps that flotation froth videos are collected and preprocessed to obtain a data set of a preset proportion; constructing a student model fused with spatial-temporal characteristics to predict each working condition category; a teacher model is constructed, and index moving average of student model parameters is used for updating so as to maintain stability and guide learning of the student model; and calculating supervision loss based on the labeled training set, calculating consistency loss based on the unlabeled training set, and performing semi-supervised training on the model by minimizing the total loss. According to the method, a spatial-temporal characteristic representation model is embedded into a semi-supervised learning framework, foam state evolution characteristics are fully represented, and high-precision working condition recognition is realized by using limited labeled samples; through the spatio-temporal feature fusion method of the cross additive attention mechanism, mutual enhancement of spatio-temporal features is realized, the time complexity is reduced, and the calculation efficiency is improved.

A system comprising a game execution unit configured to execute a game, wherein executing the game comprises rendering a plurality of image frames for display to a player of the game, a game information obtaining unit configured to obtain information about the execution of the game, including obtaining information, corresponding to an image frame currently being rendered, a complexity estimation unit configured to estimate a spatial and / or temporal complexity of the image frame being rendered in dependence upon the obtained information, a parameter selection unit configured to select one or more encoding parameters in dependence upon the estimated spatial and / or temporal complexity, and an encoding unit configured to encode the video of the game being executed using the selected encoding parameters, the encoded video comprising the plurality of image frames for display to the player.

This invention discloses a fast beam alignment method based on the simplex method. It achieves rapid beam alignment between communication devices operating on highly mobile platforms through two stages: preprocessing and simplex processing. The preprocessing stage introduces a hierarchical search approach, providing a more reasonable initial solution for the subsequent beam alignment algorithm, effectively reducing the likelihood of the simplex algorithm getting stuck in local optima. Compared to previous beam alignment methods, this significantly reduces the overall algorithm's time complexity and implementation complexity, while maintaining the same order of magnitude of angular error, demonstrating superior performance.

The application provides a Petri net supervisory control method and a controller applied to a complex manufacturing system, and the method comprises the following steps: obtaining system information of the complex manufacturing system, and constructing a Petri net model of the complex manufacturing system according to the system information; constructing a reachable graph of the Petri net model according to the Petri net model; taking the current state and resources of each device as input, and predicting transition enabling values of each device in all reachable states through a trained neural network model; and performing supervisory control on the complex manufacturing system according to the transition enabling values of each device in all reachable states. For the complex manufacturing system, the application can avoid the state explosion problem caused by the calculation of the reachable graph of the complex manufacturing system, greatly reduce the time complexity and calculation complexity caused by the calculation of the reachable graph, and directly realize the deadlock control of the complex Petri net and has high behavior permissibility.

The application relates to a fine image classification method, which is characterized by the following steps: constructing a decomposition dictionary learning model, constructing a self-adaptive local order preserving constraint model, constructing a classifier model, constructing a target function, solving the target function and constructing a classification method model. The application can not only adaptively capture the local geometric structure information of atoms and the high-order rank information features of the neighborhood of each decomposition atom in the decomposition dictionary learning process, but also can measure the contribution of multi-view data to the representation of an object through the distance between atoms, enhance the discrimination performance of the decomposition coefficients and the decomposition dictionary. Furthermore, the decomposition coefficients and the class label matrix of the fine image are used to construct a classifier model, the classifier parameters are constrained by a norm, the robustness of the classifier learning model is enhanced, the time complexity of the algorithm is reduced, and the classification performance of the adaptive local order preserving constraint multi-view decomposition dictionary learning algorithm is improved.

The invention provides an aircraft cockpit man-machine interaction task complexity obtaining method and device. The method comprises the steps that man-machine interaction tasks needing complexity evaluation are determined; performing step decomposition on the task according to a flight manual; drawing a task action flow chart according to the specific steps of the task; determining input and output nodes, the number of the input and output nodes, an action type, a time type and a decision type of each node; calculating task step logic complexity; calculating task step scale complexity; calculating task step operation complexity; calculating task step time complexity; task step decision complexity is calculated; calculating a weight factor of each complexity in the total complexity; and calculating the total complexity. According to the method, the task complexity and the expected man-machine interaction behavior in the flight process can be quantitatively described, and the problem of relatively high subjectivity in the previous model workload evaluation work is solved.

This invention relates to the field of game data processing technology, specifically to a method and system for determining the validity of grids in a match-3 game. The method includes the following steps: parsing the acquired game layout configuration data to determine geometric boundary features; traversing each scan line using a scan line algorithm to extract continuous valid intervals; constructing a compact index list containing only valid units based on the valid intervals; and generating interactive objects based on this index list. This invention introduces a discrete topology mapping mechanism to directly locate valid interactive areas, eliminating redundant calculations for invalid empty areas in the traditional full matrix traversal mode. This significantly reduces the time complexity and memory space consumption of logic initialization, solves the technical problem of low efficiency in constructing irregularly shaped layouts, ensures rapid construction and accurate response of game logic in complex terrain scenes, and effectively improves the frame rate stability and user interaction smoothness.

The invention discloses a Chinese character braille conversion method and system oriented to embedded equipment. The method comprises the following steps: firstly, linearly storing a Chinese character pinyin library according to a GB2312 coding sequence, wherein each Chinese character pinyin data record adopts a fixed-length L byte; secondly, analyzing an area code byte Qh and a bit number byte Q1 from the GB2312 code; calculating a physical offset address of the Chinese character pinyin data according to the area code byte Qh and the bit number byte Q1, and adding the physical offset address with the initial physical address to obtain a final physical address; directly reading the Chinese character pinyin data with the fixed length of L from the final physical address; and finally, converting the Chinese character pinyin data into 6-bit braille codes, converting the 6-bit braille codes into 8-bit data through bit splicing and regrouping, and outputting the 8-bit data to an 8-bit data latch to drive braille dot matrix display. According to the method, traversal searching is replaced by direct address calculation, the algorithm time complexity is improved, and the method is suitable for an embedded environment and has the advantages of being high in efficiency and low in resource occupation.

The present application relates to the technical field of surveying and mapping geographic information, and discloses a method and system for detecting error continuous surfaces based on geographic areas, which comprises the following steps: obtaining a plurality of interest surface sets of the same category in a target geographic area; obtaining the minimum circumscribed rectangle of all interest surfaces in the interest surface set; performing a primary judgment of error continuous surfaces on the circumscribed rectangle by comparing the distance from the midpoint of the circumscribed rectangle to the corner point with the distance from the midpoint of the circumscribed rectangle to the origin point, extracting all error continuous surfaces to construct an initial error continuous surface set; performing a secondary judgment of error continuous surfaces according to the positional relationship between the circumscribed rectangles in the initial error continuous surface set, deleting non-error continuous surfaces in the secondary judgment, and completing the update of the error continuous surface set. The present application reduces the time complexity of the algorithm and can meet the demand for rapid detection of large-scale data sets.

The invention relates to a text error correction method based on an improved dictionary tree. The text error correction method comprises the following steps: 1) constructing the improved dictionary tree: constructing an optimized dictionary tree by using error words; 2) searching wrong words by using the dictionary tree: querying a text to be processed by using the constructed dictionary tree; and 3) post-processing: performing comparison processing on wrong words and correct words. The method has the advantages that the method is reasonable in design, a short mode is used, the time complexity is the length of the query character, the length of the character to be processed can be reduced in a sliding window mode, and the query efficiency can be effectively improved under the condition that part of repeated words are processed; a dictionary tree is optimized, jumping is carried out according to a preprocessing table when mismatching is encountered, and query can be reduced; in the process of processing correct word pairs of wrong words, candidate positions and corresponding correct words can be accurately output.

Embodiments of the present application provide a target object tracking method and device, equipment and computer readable storage medium, relating to the technical field of artificial intelligence. The method comprises: receiving a target tracking request; in response to the target tracking request, performing feature extraction on an initial template, a current cumulative template and a to-be-tracked region corresponding to a to-be-tracked image respectively, and correspondingly obtaining initial feature embedding, current cumulative feature embedding and to-be-tracked feature embedding; performing cross-correlation processing on the template aggregated feature embedding and the to-be-tracked feature embedding obtained by feature extraction, to obtain a similarity between each sub-region and a target object; determining a tracking result of the target tracking request in at least two sub-regions according to the similarity, and outputting the tracking result. Through the embodiments of the present application, long-range changes in the appearance of the target object can be captured at a relatively low time complexity, and the tracking performance and accuracy of the target object are improved.

The invention discloses a hardware event group scheduling method for a computer processor performance monitoring unit. The method comprises the following steps: S1, acquiring an event group set and the number of counters; s2, performing descending sorting on the event groups according to the number of events by using a non-incremental sorting strategy; s3, initializing an empty round; s4, iteratively distributing the event group to an existing round or creating a new round; and S5, outputting the round set of the existing round or the new round obtained in the step S4 as a scheduling scheme of the event group on a performance monitoring counter, and the method has the advantages that a hardware event group scheduling problem is converted into a one-dimensional boxing problem, and a non-incremental sorting strategy and an iterative greedy distribution strategy are utilized, so that the time complexity of a hardware event scheduling process is remarkably reduced, and the scheduling efficiency is improved. A low-overhead and high-precision performance data observation scheme is constructed, on the premise that accuracy is guaranteed, efficient execution of large-scale performance analysis tasks is achieved, and performance monitoring efficiency and system performance observation precision are improved.

This invention discloses a method, apparatus, and medium for solving variable quantum linear problems in subspaces. The method includes: determining the system of linear equations to be solved, constructing a variable quantum circuit and a Krylov subspace, and using the generalized minimum residual method and the variable quantum circuit to calculate an approximate solution of the system of linear equations to be solved in the subspace. This addresses the shortcomings of existing technologies and can reduce the time complexity and computational load of solving linear problems.

This application discloses a retrieval-enhanced ship trajectory prediction method and system based on a frozen TrAISformer and hierarchical adaptive kNN, belonging to the field of intelligent shipping. Addressing the limitations of traditional deep learning models in generalization when facing new routes, new ship types, or seasonal changes, as well as the high cost of updating parameters for pre-trained large models and the difficulty in effectively utilizing historical similar trajectories, this method proposes a solution: acquiring AIS data and generating standardized sequences, inputting the encoded parameters of a frozen TrAISformer model; performing multi-attribute retrieval and aggregation scoring in a four-level hierarchical adaptive kNN library ("ship type-region-season-time"); and finally, outputting predictions by dynamically adjusting weights based on confidence and scenario complexity through an adaptive weighted fusion mechanism. This method avoids catastrophic forgetting, significantly reduces retrieval time complexity, supports online dynamic updates to adapt to new scenarios, and greatly improves prediction accuracy while reducing computational costs.

The invention relates to the technical field of air combat intelligent aid decision making, in particular to an aid decision making recommendation model adaptive method and system based on a Bayesian neural network, and is particularly suitable for man-machine collaborative decision making in a 2V2 air combat game scene. By designing a self-adaptive framework and an incremental learning algorithm, the model can be dynamically updated based on real-time data in the use process of a user, so that the recommendation accuracy and robustness are improved. The method comprises the following steps: constructing an incremental learning algorithm of a Bayesian neural network, analyzing the time complexity and the space complexity of the incremental learning algorithm, evaluating the real-time performance of the incremental learning algorithm in an online reasoning process, and researching the robustness performance under the condition of data uncertainty. The method can be widely applied to strategy selection in an intelligent recommendation system, an auxiliary decision-making platform and a multi-agent game.

The application relates to the technical field of artificial intelligence, and provides an article recommendation method and device, computer equipment and a storage medium, the method comprises the following steps: obtaining historical click data containing user clicks on articles; calculating the similarity between each two clicked articles according to the historical click data; each two clicked articles comprise a first article and a second article; optimizing the articles with each similarity through a preset optimization algorithm, and screening the second articles corresponding to the first article and meeting a preset similarity; obtaining click data corresponding to the first article selected by a user, and recommending the second articles corresponding to the first article to the user according to the click data. The application can reduce the time complexity and space complexity in the recall process, and improve the operation efficiency of article recommendation.

The invention discloses a power station equipment and measurement data association method based on a BiLSTM-CRF algorithm, and relates to the technical field of power station equipment data processing.The method comprises the steps that multi-source data of power station equipment is obtained in an acquisition and input mode, preprocessing including abnormal value and missing value processing, format standardization and space-time alignment is carried out, and the data of the power station equipment is obtained; obtaining a standardized intermediate data set; inputting the standardized intermediate data set into a power enhancement language model, identifying an equipment entity, a measurement type and a semantic relationship, and outputting an entity tag sequence; according to the method, a four-dimensional knowledge graph is constructed on the basis of an association relationship between entity tag sequence identification equipment and measurement points, and time complexity is optimized from a square level to a linear logarithm level through an optimization recursive algorithm, so that automatic association of primary equipment, secondary equipment and the measurement points of a plant station is realized. According to the invention, the problems of long time consumption and easy mismatching and mismatching omission caused by dependence on manual configuration of power station equipment and measurement data association are solved.

An encoding system configured to encode video of a game being executed, the video being encoded for transmission to a client device operated by a player of the game. The system includes a game execution unit that renders a plurality of image frames for display to the player and a game information obtaining unit configured to obtain information about the game including audio and / or text information associated with an image frame being rendered. A complexity estimation unit then estimates a spatial and / or temporal complexity of the image frame being rendered in dependence upon the obtained information and a parameter selection unit selects one or more encoding parameters in dependence upon the estimated spatial and / or temporal complexity. An encoding unit then encodes the video of the game being executed using the selected encoding parameters, the encoded video comprising the plurality of image frames for display to the player.

The invention relates to the technical field of surveying and mapping geographic information, and discloses an error continuous surface detection method and system based on a geographic region, and the method comprises the steps: obtaining a plurality of interest surface sets of the same category in a target geographic region; obtaining a minimum bounding rectangle of all interest surfaces in the interest surface set; comparing the distance from the midpoint of the external rectangle to the angular point with the distance from the midpoint of the external rectangle to the original point, performing initial judgment on the error continuous surfaces of the external rectangle, and extracting all the error continuous surfaces to construct an initial error continuous surface set; according to the position relation between the external rectangles in the initial error continuous surface set, secondary judgment of the error continuous surfaces is carried out, non-error continuous surfaces in the secondary judgment are deleted, and updating of the error continuous surface set is completed. According to the method, the algorithm time complexity is reduced, and the requirement of large-scale data set rapid detection can be met.

The application provides a delay calibration method and device in an infectious disease space collection population model, and belongs to the technical field of infectious disease transmission modeling and risk assessment; the application adopts a delay time discretization method to convert continuous distribution into a discrete probability vector; an infected person allocation algorithm based on matrix operation and a time axis translation algorithm based on matrix operation are designed; the efficiency is significantly improved, and the time complexity is reduced from to; experimental verification shows that the processing speed of a 100-million-population city is at least improved by 7 times, and the processing speed of a single 100-million-population city can be improved by more than 10 times; the whole algorithm is based on matrix operation under a determined dimension variable, so it is easier to use GPU to accelerate operation, and then the algorithm can be extended to a real-time epidemic monitoring and early warning system in the future.

The invention provides an sEMG hand joint motion continuous estimation method based on sparse attention and distillation, and relates to the technical field of motion continuous estimation methods, comprising the following steps: data acquisition and preprocessing; inputting projection and position codes; projecting the sEMG signal subjected to law normalization from 12 dimensions to 128 dimensions through a linear layer, adding the sEMG signal with a position coding vector, and endowing the sEMG signal with position information; the projected data are processed on the basis of a model architecture fusing a ProbSparse self-attention mechanism, attention distillation and copy stacking, and continuous angle values of hand key joints are output; 150-dimensional data obtained after copy stacking is processed through a regression head, and the 150-dimensional data is mapped into 22 pieces of hand joint angle data. By adopting the method, the time complexity is reduced from O (L) to O (L log L), the space complexity is optimized to O (L log L), the calculation efficiency during long sequence sEMG data processing is improved by more than 20%, and the hardware resource consumption is reduced by 30%.

This application relates to a file query method, apparatus, computer device, storage medium, and program product. The method includes: obtaining a file identifier to be queried; determining a query hash value corresponding to the file to be queried based on the file identifier and at least one preset hash function; and determining a query result for the file to be queried based on preset element values ​​at each bit of a preset bit array and the query hash value. The preset element values ​​include a first element value and a second element value, where the first element value is the element value corresponding to a whitelisted file. This allows for the determination of whether a file to be queried is a whitelisted file using a fixed number of hash calculations and bit array accesses, reducing the time complexity of file queries and improving file query efficiency. Furthermore, using a bit array to store the element values ​​corresponding to whitelisted files also saves storage space.

The application discloses a SQL injection prediction model training method and system, a storage medium, and a SQL injection prediction model training method and system, and a storage medium, wherein a new SQL injection loss function is constructed, a SQL type balance factor, a SQL difficult sample focusing parameter and a smooth hinge loss are coupled, a first-order partial derivative and a second-order partial derivative of the loss function are calculated, the first-order partial derivative and the second-order partial derivative of the loss function are substituted into information gain, a decision tree structure is constructed, a decision tree model is trained, optimal SQL injection features and optimal split nodes are obtained, and an optimal decision tree structure and a corresponding SQL injection prediction model are constructed. The application can reduce the time complexity of model training, avoid overfitting or underfitting of the trained model, and improve the accuracy of machine learning SQL injection detection.

The invention provides a dynamic evolution-based network abnormal user identification method and device, equipment and a storage medium, and the method comprises the steps: constructing a'basic feature-content feature-social feature 'multi-dimensional quantitative portrait through the refined preprocessing of the full-dimensional data of a multi-platform user; based on an improved XGBoost algorithm, fusing the multi-dimensional features to output a user comprehensive credible value; constructing an attribute social knowledge graph, introducing five dynamic evolution factors including a trend factor, a periodic factor, a random factor, an autocorrelation factor and an external variable factor, and realizing dynamic behavior capture in combination with a hierarchical time complexity optimization strategy; the individual credible value is calibrated through confidence propagation and social association fusion, the propagation probability is calculated in combination with total time complexity attenuation, and finally, accurate identification of individual and group anomalies is realized through an anomaly score.

The present invention belongs to the field of multi-label spatial dataset sample search and discloses a hash-based similarity measurement method for multi-label spatial datasets. The method includes data preprocessing: mapping the coordinates of points in the spatial dataset to plane coordinates within the outer bounding box, and calculating the density of data points with each label within each grid to obtain a density matrix; quasi-multi-channel image generation: mapping the density values ​​to "color channel values" under the corresponding channels and calculating the composite channel values; hash string generation: using mean hashing, difference hashing, and perceptual hashing methods to generate hash strings for each dataset to obtain hash string tuples; and similarity calculation: calculating the Hamming distance between hash strings to obtain the similarity between multi-label spatial datasets. The present invention balances algorithm accuracy and efficiency, maintains low time complexity, and accurately and quickly measures the similarity between multiple labeled spatial datasets.

The present invention discloses a method, apparatus, device, and computer-readable medium for trajectory compression, and relates to the field of computer technology. A specific implementation of the method includes: among the trajectory points of a driving trajectory, screening out the retained trajectory points of the driving trajectory according to the degree of deviation of the trajectory points from the road; determining the retained trajectory points as key trajectory points based on the driving duration of the retained trajectory points, where the driving duration is the time interval from the previous trajectory point of the retained trajectory point to the next trajectory point of the retained trajectory point; and adding the starting point of the driving trajectory, the key trajectory points, and the ending point of the driving trajectory to the compressed trajectory to compress the driving trajectory. This implementation can reduce the time complexity of compressed trajectory data, thereby reducing compression time.

This invention belongs to the field of protocol reverse engineering technology and proposes a method and apparatus for reverse analysis of unknown industrial control protocols. It involves forming a set of message fragments based on network packets; the packets and message fragment sets constitute a dataset; a heterogeneous message graph is constructed based on the dataset; the heterogeneous message graph is input into a neural network model for message graph feature extraction to perform message clustering and train the neural network model; the dataset to be clustered is input into the trained neural network model for clustering; within the same message cluster, the Needleman-Wunsch algorithm is used to infer the syntax format and mark field boundaries. This invention reduces the time complexity of message clustering; it jointly optimizes feature extraction and clustering; and it provides the model with finer-grained and more reasonable analysis units.

An encoding system is configured to encode video of a game being executed for transmission to a client device operated by a player of the game. The system comprising a game execution unit configured to execute the game which involves rendering a plurality of image frames for display to the player and a game information obtaining unit configured to obtain information about the execution of the game. The information obtaining unit obtains information, corresponding to an image frame currently being rendered, from one or more intermediate rendering buffers and a complexity estimation unit estimates a spatial and / or temporal complexity of the image frame being rendered in dependence upon the obtained information. A parameter selection unit selects one or more encoding parameters in dependence upon the estimated spatial and / or temporal complexity and an encoding unit encodes the video of the game being executed using the selected encoding parameters wherein the encoded video comprises the plurality of image frames for display to the player.