162results about How to "Improve search efficiency" patented technology

The invention discloses a multi-unmanned aerial vehicle cooperative search method based on dynamic region division and a multi-constraint virtual force field, and aims to solve the problems of low search efficiency, unbalanced load, difficulty in guaranteeing the motion safety of multiple unmanned aerial vehicles and the like in multi-unmanned aerial vehicle coverage search. Firstly, a task area, an unmanned aerial vehicle kinematics model and a sensor sensing model are constructed; then, dynamic region division is carried out based on a weighted Voronoi diagram, the search progress of the unmanned aerial vehicle, the responsibility region area and the obstacle distribution condition are comprehensively considered, and self-adaptive balancing of task loads is achieved; and selecting a target point based on a utility function, and finally designing a multi-constraint virtual force field control method consisting of target attraction, obstacle avoidance force, regional barrier force and exploration force, generating an expected speed meeting speed constraint and obstacle avoidance requirements, and realizing stable and efficient coverage search. The result shows that the multi-machine collaborative search efficiency can be effectively improved, and the method is suitable for disaster search, routing inspection monitoring, autonomous detection in a complex environment and other scenes.

The invention discloses a ship pipe fitting workshop scheduling method, system, equipment and medium based on a large model assisted evolutionary algorithm, and relates to the technical field of ship pipe fitting workshop production operation, and the specific steps are as follows: establishing a hybrid flow workshop scheduling model, adopting a multi-dimensional coding and decoding structure to code a workshop scheduling scheme, generating an initial population, and establishing a hybrid flow workshop scheduling model; and guiding the individuals to carry out iterative evolution by using a search operator sequence generated by the large model based on a historical evolution effect or a randomly generated search operator sequence, and outputting an optimal scheduling scheme with the shortest completion time. According to the method, modeling and solving of a multi-resource collaborative complex scheduling problem are realized, and the problem of insufficient scheduling scheme quality caused by neglect of transportation processing coupling or low algorithm search efficiency in an existing method is solved. By introducing a large-model intelligent guiding mechanism, the evolutionary process has adaptive optimization ability, and the feasibility of a scheduling scheme is ensured through a complete coding and decoding framework.

The application relates to the technical field of human resource management, in particular to a medical staff scheduling system based on medical staff skills, which comprises a standard skill input and classification device, which is used for inputting the working skills of each department, dividing the same working skills of each department into general skills, and dividing the special working skills of each department into special skills; a department patient input device, which obtains the treatment information of patients in each department ward, extracts the predicted workload of each patient in the next scheduling cycle, and counts the predicted workload of each department; the predicted workload comprises the execution times of each general skill and the execution times of each special skill; the system realizes cross-department dynamic scheduling by constructing a hospital-level skill resource pool and a demand prediction mechanism, standardizes the general skills into shared resources, and enables medical staff to flexibly support departments with high demand peaks.

The invention provides an object management method and device of an automatic storage management system, a medium and a product. The object management method of the automatic storage management system comprises the following steps: detecting that the number of objects contained in a target directory reaches a preset threshold value, and splitting the objects in the target directory into a plurality of logical directories according to name sizes; and establishing an index for the target directory, wherein the index of the target directory maintains the maximum value and the minimum value of the object name in the target directory and the maximum value and the minimum value of the object name in each logical directory. When a to-be-searched target object is received, judging whether the target object is in the target directory according to the name size of the target object and the index of the target directory, if so, positioning a target logical directory in which the name size of the target object is located according to the index of the target directory, checking whether the target object exists in the target logical directory, and if so, executing the step 2; and obtaining a target object, and if not, outputting prompt information. The search range is reduced, and the search efficiency is effectively improved.

A kind of detection method and device of fake APP, terminal, the method includes: determining training data;Keyword extraction is carried out to the brief introduction of each pair of target APP and the brief introduction of suspected APP, and the data vector of each keyword is determined;Determine the weight value of each keyword, and the data vector of each keyword in the target APP is weighted based on the weight value Operation is carried out to obtain target APP data vector, and obtain suspected APP data vector;The vector comparison result of target APP data vector and suspected APP data vector is calculated, the absolute value of the vector comparison result is determined as first data vector, and the square of the vector comparison result is determined as second data vector;Obtain the training text vector of the pair of target APP and suspected APP;Training fake detection model.The present application can enhance the association between keywords in model training phase, reduce the misjudgment rate.

The application belongs to the field of workshop scheduling, and particularly discloses a semiconductor wafer probe test scheduling method and system based on an improved genetic algorithm, which adopts double-layer process-machine coding, and combines auxiliary resource taboo coding as an individual, effectively converts a complex scheduling problem into a coding form through an innovative coding and decoding strategy, and avoids traversal search on all selectable auxiliary resources; global-local hybrid search is carried out through the improved genetic algorithm, on the basis of machine level exchange with the traditional critical path-key block, search on the auxiliary resource immediately preceding work is increased, and neighborhood exploration is carried out based on a load balancing strategy, so that the search efficiency and solution quality are improved. The application can quickly and efficiently solve the semiconductor wafer probe test scheduling scheme, effectively improve the equipment utilization, speed up the scheduling efficiency, and break through the bottleneck of traditional scheduling.

The application relates to a bundle search processing method and device, computer equipment and a storage medium. The method comprises the following steps: performing bundle search on a word table based on a current to-be-matched object and a current bundle width to obtain a current search result, wherein the current search result comprises a plurality of target words which are matched successfully with the current to-be-matched object and the number of which matches the current bundle width; performing width attenuation on the current bundle width according to a bundle width attenuation mode matched by the number of executed bundle searches to obtain a bundle width for next bundle search; taking each target word as a to-be-matched object for next bundle search, and iteratively performing bundle search until the bundle width obtained by attenuation is equal to a bundle width threshold value, and taking the search result at this time as a target to-be-matched object, and performing bundle search on the word table based on the bundle width threshold value to obtain a target search result. By adopting the method, the search efficiency can be improved while ensuring the search effect in an ultra-long sequence scene.

This application discloses a low-altitude defense platform deployment system and method. The system includes: a data acquisition module for acquiring relevant data of the defense area and information on available platforms; a capability quantification module for uniformly quantifying the capability parameters of each platform to obtain standardized capability descriptions; an AI agent search module, comprising multiple parallel-working AI agents and a shared memory area; each AI agent iteratively executes the generation of candidate deployment schemes, calculation of constraint violations, and evaluation of comprehensive performance scores, and updates the locally optimal deployment scheme based on the evaluation results, exchanging scheme information through the shared memory area to guide subsequent searches; and a scheme determination module for determining the globally optimal deployment scheme when termination conditions are met. This application improves the comprehensive protection effectiveness and planning efficiency of heterogeneous defense platform deployment schemes through capability quantification and multi-agent parallel collaborative search, achieving automated global optimization deployment under complex constraints.

The application relates to the chip technical field, in particular to a target timing path acquisition method, electronic equipment and medium, the method comprises the following steps: S1, generating an original label database and an original timing margin database based on original timing constraint information of chip design; S2, generating a search label database and a search timing margin database based on search timing path constraint information and the original label database; S3, determining a candidate search path endpoint based on the search label database, the search timing margin database and target user constraint information; S4, performing one or more operations of path pruning, deduction and filtering based on the search label database and the search timing margin database, and generating a candidate subgraph and a candidate original path by tracing back from the candidate search path endpoint; and S5, splicing the candidate original path and the corresponding candidate subgraph to generate a target timing path. The application improves the search efficiency and accuracy of the target timing path.

The present disclosure provides a message processing method and device, equipment and storage medium, comprising: in response to receiving a to-be-processed message, extracting quintuple information from the to-be-processed message; matching the quintuple information with the index key of the session table to determine the type of the to-be-processed message, wherein the index key of the session table is constructed based on the quintuple information of the established session; in response to the type of the to-be-processed message being a first packet, matching the quintuple information with the index key of the association mapping table to determine whether the to-be-processed message is an associated session of the main session, wherein the index key of the association mapping table is constructed based on the IP address and port information obtained by parsing the application layer of the control channel message of the multi-channel protocol, and the main session is the session of the control channel; in response to the to-be-processed message being an associated session of the main session, performing forwarding processing on the to-be-processed message.

The invention relates to a display device and a personalized recommendation reason generation method. The display apparatus includes: a display configured to display a user interface; an audio output device configured to output sound; the controller is configured to display a search result page in response to a multimedia content search operation triggered by a target user; in the process that the target user carries out multimedia content search for the search result page, target multimedia content is selected; a personalized recommendation reason of the target multimedia content is obtained, and the personalized recommendation reason is generated based on the user portrait data of the target user and the media asset data of the target multimedia content; and controlling at least one of the display and the audio output device, and displaying the personalized recommendation reason. By adopting the display equipment, the conversion rate of a multimedia content search function can be improved.

A configuration command lookup method, measuring instrument, test system, and program product are disclosed, relating to the field of electronic test and measurement instrument technology. The configuration command lookup method, applied to a measuring instrument, includes: acquiring pre-stored function association mapping information, which includes multiple parameter status items of the measuring instrument and their corresponding parameter identifiers; responding to a configuration operation performed by a user; acquiring parameter status items that have changed during the configuration operation, and determining the parameter identifier corresponding to the changed parameter status item based on the function association mapping information; acquiring a pre-stored parameter mapping table, which includes each parameter definition item in the measuring instrument, its corresponding configuration command, and parameter identifier, wherein the parameter identifier corresponding to the parameter definition item corresponds one-to-one with the parameter identifier of the parameter status item; searching for the parameter identifier of the changed parameter status item in the parameter mapping table, and determining the configuration command for the changed parameter status item based on the parameter identifier.

This invention relates to the field of battery state prediction technology and discloses a method for predicting the health status of UAV power batteries. The key technical points of this method are: data acquisition and quantum encoding; quantum feature extraction; construction of a quantum-heuristic deep learning model; model training and optimization; and health status prediction and assessment. Through quantum encoding, a quantum-heuristic model architecture, and a dynamic optimization mechanism, this method overcomes the limitations of traditional methods in modeling complex nonlinear relationships and local optimization, providing a high-precision and robust solution for the health management of UAV power batteries, and has significant engineering application value.

The application relates to a water and fertilizer integrated control strategy recommendation method and system based on multi-objective optimization, multiple groups of water and fertilizer test treatments are laid out, irrigation amount, nitrogen, phosphorus and potassium amount, yield and auxiliary parameters are collected to form water and fertilizer samples, water and fertilizer vectors are constructed and relative yield is converted, sample sets are established by cleaning abnormal values and unifying units, and water and fertilizer limits are stored; a root zone effective water and nitrogen coupling enhancement feature is constructed, an improved Matern kernel function Gaussian process proxy model with a fractal dimension scale and a threshold penalty is introduced, and a multi-objective function is built relying on posterior prediction; the proxy model is used as a rapid evaluator, multi-objective continuous ant colony optimization is adopted, pheromone is updated through population initialization, elite archive maintenance, covariance matrix sampling and stress-free maintenance day constraint, and a Pareto front strategy set is obtained through iteration; finally, the model and the optimization algorithm are deployed to a field system, and executable water and fertilizer prescriptions are output cycle by cycle. The application can accurately adapt to field water and fertilizer demand, improve quality, increase efficiency, save water and save fertilizer.

The application belongs to the technical field of optical three-dimensional measurement, and discloses a two-division iteration sub-pixel matching method and system for phase structured light three-dimensional measurement, which comprises the following steps: obtaining a phase map; performing legality marking and pixel-level initial matching on the phase map; determining a sub-pixel search area based on the pixel-level initial matching; and performing sub-pixel matching point search based on the sub-pixel search area by using a two-division iteration method to obtain a sub-pixel matching point. The application can improve the precision of binocular matching in phase structured light three-dimensional measurement, thereby improving the precision of three-dimensional reconstruction.

The application provides a method for searching exposure time and a quantum efficiency measuring system, comprising: a data processing module configured to configure fixed parameters of an image acquisition module and wavelengths of a wavelength configuration device; the image acquisition module is controlled to determine a candidate exposure time set according to a search step and an initial value of exposure time; after the wavelengths of the wavelength configuration device are configured, single-band light configured by the wavelength configuration device is received through an optical fiber bundle; a target exposure time is selected from the candidate exposure time set multiple times; images are captured multiple times under the environment of the wavelength of the wavelength configuration device; if the images do not occur light cutoff and satisfy a preset image saturation constraint condition and an image linearity constraint condition, the target exposure time is taken as a set of exposure times corresponding to the current wavelength; and a set of exposure times corresponding to the wavelength of each wavelength configuration device is searched until a set of exposure times corresponding to the wavelength of each wavelength configuration device is searched. The method is used to accurately search for exposure time meeting the linearity requirement.

The application discloses a photovoltaic power generation system parameter optimization method, device and equipment and a computer readable storage medium. The method comprises the following steps: acquiring various system parameters of a photovoltaic power generation system and photovoltaic power generation system characteristics of the photovoltaic power generation system under the various system parameters, wherein the system parameters are adjustable system parameters of the photovoltaic power generation system; determining target activation values of the various system parameters according to the various photovoltaic power generation system characteristics and at least one characteristic constraint; and selecting target system parameters from the various system parameters according to the target activation values and the various photovoltaic power generation system characteristics. The application realizes a scheme for optimizing the parameters of the photovoltaic power generation system by using the target activation values determined according to the photovoltaic power generation system characteristics and the characteristic constraint, and improves the parameter optimization effect of the photovoltaic power generation system.

The embodiment of the invention relates to the technical field of federated learning and information security, in particular to a federated multi-target scheduling method and system for industrial control crowdsourcing testing, which is characterized in that sensitive data such as ability, experience and the like of a tester are only reserved at a local terminal by constructing a framework combining local feature coding and federated model training, so that the test efficiency is improved, and the test efficiency is improved. Outward transmission is not carried out; only the model update quantity after the privacy enhancement processing such as gradient cutting and differential privacy noise injection is uploaded to the federated matching learning server, and only the model update quantity after the privacy enhancement processing is uploaded to the federated learning server, so that the leakage risk of concentrated data storage is avoided from the source, the requirements of privacy regulations such as GDPR and the like are completely met, and the reliability of the system is improved. Compared with traditional privacy technologies such as homomorphic encryption, the method has the advantages that the calculation and communication overhead is greatly reduced, the design of local matching degree calculation is matched, the task matching response speed is greatly increased, and the real-time requirement of industrial control system testing is met.

The invention discloses a laying hen lossless data processing method based on improved XGBoost, and relates to the technical field of data processing, discrete feature numeralization is realized through adaptive tag coding, abnormal value detection and non-linear mapping correction are combined, a robustness purification feature set is constructed, and a layer lossless data processing method based on the improved XGBoost is obtained. The problems that a traditional method is sensitive to sensor noisy points and lacks an effective data cleaning mechanism are solved, and prediction precision reduction caused by extreme sample interference is avoided. And performing nonlinear expansion on the purification features by using a polynomial kernel, and accurately capturing a coupling relationship between the features. The global optimal hyper-parameter optimization of the XGBoost integrated regression model is driven by high-dimensional features, so that the parameter optimization efficiency is improved, local optimum is avoided, the method adapts to a multi-source heterogeneous and high-noise nonlinear data scene of laying hen breeding, the processing precision and generalization ability of the model are remarkably improved, reliable data support is provided for accurate management and quality monitoring of laying hen breeding, and the method is suitable for large-scale popularization and application. And efficient landing of the intelligent breeding technology is promoted.

This invention discloses a hardware acceleration method and accelerator for Transformer based on mixed-precision quantization and Huffman coding. The acceleration method includes: using a genetic algorithm to obtain several configuration schemes for mixed-precision quantization of Transformer network layers; performing mixed-precision quantization on each Transformer network layer based on each quantization configuration scheme to obtain a corresponding KL divergence; training a multilayer perceptron to obtain a quantization configuration prediction network using the quantization configuration scheme and the corresponding KL divergence as the output label and input feature, respectively; receiving a user-set target KL divergence value, using the quantization configuration prediction network to obtain the corresponding quantization configuration scheme, and performing mixed-precision quantization on each network layer based on the quantization scheme; and using Huffman coding to encode and compress all quantization weights before on-chip storage. This invention can reduce storage and computational overhead while maintaining model accuracy.

The application discloses a kind of urban renewal scheme simulation methods based on digital city design.Cities three-dimensional model, plot boundary, road network, population distribution and public facilities distribution data are obtained and unified processing is carried out to form city digital data set;Based on data set, volume rate, road connectivity, green space ratio and building density are calculated and feature grid structure is constructed;According to planning constraints, candidate urban renewal scheme is generated and mapped to feature grid;Urban operation simulation is carried out to candidate scheme to obtain traffic operation, environmental impact and public service accessibility index;Statistical test method is used to screen the competition to obtain the reserved scheme;Then, the elite scheme file is updated through feature grid search mechanism;Urban renewal elite scheme set is output and urban renewal scheme simulation result is generated, to realize the simulation and evaluation of urban renewal scheme.

The application relates to a quantum symmetric encryption key searching method, device, equipment and medium. The method converts an initial quantum state into an initial key superposition state based on an H gate and a rotation gate, encodes a plaintext using ground state encoding to obtain a plaintext quantum state, encrypts the plaintext quantum state using a quantum encryption circuit constructed by a preset symmetric encryption algorithm to obtain a ciphertext quantum state, constructs a loss function according to a result of measuring the ciphertext quantum state and real ciphertext of the plaintext, adjusts a rotation angle parameter of an initial rotation gate to make the loss function meet a preset condition, determines the rotation angle parameter of the rotation gate at this time, converts the initial quantum state into a search key superposition state in combination with the H gate, determines a key appearing most frequently in a result of measuring the search key superposition state as a searched key, realizes encryption and measurement in a quantum computing mode, and optimizes parameters in a loss function mode, so that the complexity of quantum computing and the occupation of quantum resources are reduced.

This invention discloses a network path optimization method and system. The method includes: adjusting the adaptive weights of the heuristic function in the underlying model LPA* algorithm to intelligently change the magnitude of the heuristic function's influence with iteration; simultaneously, introducing a bias p in the K-value calculation to improve the algorithm's search efficiency; and performing unbalanced allocation of initial pheromones for the ant colony algorithm based on the initial path calculated by the underlying model. The upper-layer model applies the ACO algorithm to plan fiber optic network paths on a grid map to obtain the globally optimal network path. This invention, through the design of a hierarchical algorithm, provides the ant colony algorithm with prior information including pre-selected paths, enhancing the traditional ant colony algorithm's ability to guide pre-selected areas in path planning. This enables faster search for feasible paths, effectively solving the problems of slow search speed and susceptibility to local optima in the traditional ACO algorithm, and significantly improving the overall performance of the fiber optic network planning system.

The invention discloses a search agent training method and device and a storage medium, and the method comprises the steps: collecting a current state vector under the condition that a search agent carries out the key sign search of any sample cardiovascular three-dimensional diagram; inputting the current state vector into a search agent, and outputting an action instruction through the search agent; the observation window is controlled to execute the action instruction, an experience tuple is collected and stored in an experience playback pool, and the experience tuple comprises the current state vector, the action instruction, the instant reward value and a next moment state vector; and performing iterative training on the search agent based on an experience tuple stored in the experience playback pool, so that the trained search agent can output an action instruction sequence enabling the observation window to quickly cover a key sign area according to the state vector.

This invention provides a method, system, and electronic device for image recognition in the forestry and fruit industry, belonging to the field of intelligent agriculture technology. The method first determines the hyperparameters to be optimized and initializes the snow goose population; in the migration exploration phase of iterative optimization, a lead goose is selected from multiple candidate individuals using a probabilistic strategy to guide the position update; in the foraging and development phase, the position is updated using the complementary solutions of elite individuals; finally, the model is updated based on the optimal configuration obtained through optimization, and the forestry and fruit images are recognized. This invention effectively maintains population diversity by selecting the lead goose using a probabilistic strategy, enhances local development accuracy using the complementary solution update mechanism, avoids the algorithm getting trapped in local optima, and significantly improves the accuracy and reliability of image recognition in the forestry and fruit industry.

Embodiments of the present disclosure relate to a method and apparatus for recommending application functions, a device and a storage medium. The method for recommending application functions comprises: in response to a triggering operation on a target page of an application, determining, based on user behavior data of a target user in a historical time period, function use information of the target user on a search function module in the application; if the function use information is greater than a preset information threshold, displaying a function label of the search function module at a function display position of the target page; the function label is used to trigger the search function module. According to the embodiments of the present disclosure, personalized recommendation of the search function is realized according to the use of the search function in the application, so that users who prefer the search function can more conveniently see and use the search function at the function display position of the target page, thereby shortening the search operation path and improving the search efficiency.

The invention discloses a diesel engine cylinder cover mechanical property mapping method, and belongs to the technical field of internal combustion engine structural strength analysis. The method comprises the following steps: acquiring microstructure node data based on casting simulation, and converting the microstructure node data into a node mechanical property field through a material model; after a mixed mapping strategy is adopted, target grid integration point coordinates are determined, source units are traversed in a source grid, whether the target grid integration points are located in the spatial range of the target grid integration points or not is judged, and confirmation is carried out according to the volume coordinate relation; performing high-fidelity interpolation on the integral points in the source units by adopting a shape function; for integral points which cannot be positioned, a k-d tree-based nearest neighbor node averaging method is adopted; and finally, writing the heterogeneous mechanical property field on the integral point into a structure analysis result. The method breaks through the precision and robustness bottlenecks of cross-scale and cross-grid data transmission, solves the problem that the material is difficult to couple with a stress field due to non-uniform material performance distribution, and provides a reliable data basis for high-precision fatigue life prediction of the cylinder cover.

The application relates to an optimal design method of a modular axial flux permanent magnet synchronous wind generator, and belongs to the field of wind power generation. The generator comprises a stator and a rotor; torque pulsation and torque density are used as optimization targets, and stator slot depth, rotor permanent magnet thickness and rotor permanent magnet pole arc coefficient are used as to-be-optimized design variables; constraint conditions of the design variables are determined, a Latin hypercube sampling experiment is carried out, a DNN proxy model of the optimization target and the to-be-optimized design variables is established; a Bayesian optimization algorithm is used to optimize hyperparameters of the proxy model, and optimal hyperparameters are obtained; the proxy model adopting the optimal hyperparameters is trained to obtain an optimal proxy model, and based on the optimal proxy model, an NSGA-II optimization algorithm is used to optimize the to-be-optimized design variables, and finally, an optimal combination of the to-be-optimized design variables is determined. The application can reduce modeling errors, improve calculation efficiency, robustly process multi-target trade-off under complex parameter coupling conditions, and effectively improve the performance of the modular generator.

The application discloses an image classification method and device, a storage medium and a computer device. The method is applied to the computer device and comprises the following steps: in a self-defined image classification mode of an electronic album, in response to a triggering operation of a user on an update control of an image corresponding to a to-be-managed image category, updating the image in the to-be-managed image category, calling a training interface, obtaining a first image classification model corresponding to the self-defined image mode through the training interface, the model being pre-trained, and performing transfer training on all images of the to-be-managed image category according to the first image classification model, so as to obtain a first image classification model after transfer training. The classification of the updated image can be matched by using the first image classification model after transfer training, the classification accuracy is improved, finally, the to-be-classified images of the electronic album are classified by using the trained first image classification model, the image classification efficiency and accuracy are improved, and the image searching efficiency is further improved.

The application discloses a data balancing method and device, equipment and storage medium, and relates to the technical field of computers. The method comprises the following steps: performing hash processing on first samples and second samples in a data set, and mapping the first samples and the second samples into first hash buckets and second hash buckets; determining second samples matched with the first samples in the first hash buckets from second hash buckets adjacent to first hash buckets in the first hash buckets; searching in adjacent hash buckets in a counterfactual search process, reducing a search range, reducing a search amount, and improving search efficiency. Then, based on a feature relationship between the first samples and the second samples, third samples in the second samples are processed to obtain fourth samples. The labels of the fourth samples are consistent with the labels of the first samples, and data balancing is realized. Since the time required by the search process is shortened, the efficiency of data balancing is improved.