328results about How to "Improve determination efficiency" patented technology

The invention relates to the technical field of battery detection, in particular to a new energy vehicle battery fault intelligent detection system which comprises a voltage change analysis module, an internal resistance micro-analysis module, a current response monitoring module and a fault diagnosis integration module. According to the invention, by refining voltage monitoring and internal resistance analysis, the capability of early recognition of battery performance degradation and faults is remarkably improved, the early warning of the faults is more accurate by recognizing abnormities through an advanced data processing technology and refining fluctuation analysis, the risk of false alarm and missing alarm is reduced, and the internal resistance data is analyzed by introducing a fractal theory. Microscopic changes of battery aging can be more accurately captured, early detection of the aging trend is realized, pulse current testing and current response data analysis are combined, evaluation of battery performance stability is further enhanced, comprehensiveness and depth of a detection result are ensured, and detection accuracy is improved. And the accuracy of battery fault detection and the efficiency of determining the fault type are greatly improved.

The invention provides a method and a device for determining distributed keys in a distributed database and electronic equipment, which can be applied to the technical field of distributed databases. The method comprises the following steps: analyzing a plurality of initial structured query statements from a coding file of a distributed database; screening out a plurality of structured query statements of a preset statement type from the plurality of initial structured query statements under the condition that the plurality of initial structured query statements are not executed; according to the query tree of each structured query statement, redistribution costs of a plurality of candidate keys related to each structured query statement are determined, the structured query statement comprises at least one database table, and each database table comprises at least one candidate key; summarizing the redistribution cost of the same candidate keys of the same database table in the plurality of structured query statements to obtain the total redistribution cost of each candidate key in each database table; and taking the candidate key with the highest total redistribution cost in each database table as a distribution key of the database table.

The invention provides a laser-induced coloring temperature field prediction method, device, equipment and medium, and belongs to the technical field of laser marking coloring, and the method comprises the steps: constructing a laser-induced coloring photo-thermal response physical model; a neural network model with time and space positions as input and temperature as output is constructed, a loss function of the neural network model is constructed based on the photo-thermal response physical model, iterative optimization is performed on the neural network model based on the loss function and a training set, and a temperature prediction model with embedded physical information is obtained; and obtaining target time and a target spatial position of a laser-induced coloring process under a target process parameter combination, and determining a predicted temperature field under the target process parameter combination based on the target time, the target spatial position and the temperature prediction model embedded with the physical information. According to the method, the photo-thermal response physical model is taken as priori knowledge, so that the determination efficiency and precision of the predicted temperature field are improved.

The invention discloses an insulating layer aging evaluation device, method and equipment based on a region of interest of a cable laying environment, and belongs to the technical field of electric power facilities. The device comprises a cable parameter acquisition module used for acquiring the anti-aging parameter of the cable; the attention region feature acquisition module is used for acquiring a target feature extraction result of the cable in the attention region; the aging analysis module is used for inputting the anti-aging parameter and the target feature extraction result into an aging analysis model and determining a relative aging coefficient of the region of interest; and the alarm module is used for determining the aging degree of the region of interest according to the relative aging coefficient, and generating aging alarm information under the condition that the aging degree reaches a preset aging degree threshold. According to the technical scheme, the aging condition of the region of interest relative to the normal region can be determined by obtaining the anti-aging parameter of the cable and the target feature extraction result in the region of interest, so that the efficiency and accuracy of determining the aging speed of each region of the cable are improved.

The invention relates to the technical field of ecological restoration, in particular to a cylindrical permeation grouting range determining method and system considering the tortuosity of a porous medium, and the method comprises the following steps: collecting porous medium characteristic data and underground water pressure at a selected grouting point position; meanwhile, Bingham cement grout characteristic data are collected, and grouting parameters are set; the tortuosity of the porous medium is considered, and then the seepage velocity of Bingham cement grout is determined based on a rheological equation of Bingham fluid and a mechanical analysis equation of an infinitesimal body in the grouting pipe; and under the condition of the cylindrical diffusion boundary, a cylindrical permeation grouting range solving model is constructed based on the seepage velocity and the unit time grouting amount calculation formula, and the cylindrical permeation grouting spatial diffusion range quantitative index is solved according to the grouting parameters so as to determine the cylindrical permeation grouting range. The grouting quality and reliability in the ecological restoration project can be improved, the construction requirement under the complex ecological engineering environment is met, and effective restoration and sustainable development of an ecological system are achieved.

The invention discloses an adaptive scheduling method based on a hydraulic model and an AI algorithm and a related device, and the method comprises the steps: carrying out the water prediction based on the current water consumption through employing an SARIMAX model, obtaining the predicted water consumption, selecting a scheme from a scheme library based on the current water consumption, the predicted water consumption and the current working condition information of a water plant, and obtaining a first scheme set, determining a second scheme set based on the first scheme set and a genetic annealing algorithm, determining a first result set by using a pipe network hydraulic model based on the second scheme set, selecting schemes from a scheme library based on the first result set to obtain a third scheme set, and determining a fourth scheme set based on the third scheme set and the genetic annealing algorithm, based on the first result set and the fourth scheme set, a pump room hydraulic model is used for determining a second result set, a water supply scheduling scheme is determined based on the first result set, the second result set and a target function, and the target water supply scheduling scheme is used for self-adaptive water supply scheduling. The safety and the stability of water supply dispatching can be improved.

The invention provides a driving track determination method and device, a terminal and a storage medium, and belongs to the technical field of vehicles. The method comprises the following steps: acquiring state data of a target vehicle; creating an initial behavior decision tree based on the state data; based on at least one of a first heuristic rule and a second heuristic rule, pruning the initial behavior decision tree to obtain a target behavior decision tree, the first heuristic rule being used for representing that the number of behavior changes of the target vehicle in the future time period does not exceed a preset number of times, and the second heuristic rule being used for representing that the number of behavior changes of the target vehicle in the future time period does not exceed a preset number of times; the second heuristic rule is used for representing that the target vehicle meets a lane changing condition; and for each behavior sequence in the target behavior decision tree, based on a plurality of behaviors in the behavior sequence and the state data, fitting the moment in the future time period and the vehicle position to obtain a driving track corresponding to the behavior sequence. According to the technical scheme, the driving track of the target vehicle can be quickly determined.

The invention discloses an equipment control method and related equipment. The method comprises the following steps: acquiring data for expressing a target control intention for target equipment; based on the data, determining an equipment control mode matched with the data by querying a pre-defined mapping relationship; the mapping relation comprises a mapping relation between data used for expressing different control intentions for the target equipment and corresponding equipment control modes; and controlling the target equipment according to the equipment control mode. The invention further provides an equipment control device, equipment, a computer readable storage medium storing the computer program and a computer program product. According to the scheme provided by the invention, when the target equipment control mode is determined, the query of the mapping relation is relatively simple and easy to realize, so that the problems of relatively long time for determining the equipment control intention and relatively low efficiency in the equipment control mode adopted in the prior art can be solved, and good user experience is ensured.

The invention discloses a video processing method and device, equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring a plurality of sub-lens segments in a target video; obtaining modal feature information of a plurality of modals of each sub-lens section in the plurality of sub-lens sections; on the basis of the modal feature information of the multiple modals of every two adjacent sub-lens segments in the sub-lens segments, obtaining the relevance of every two adjacent sub-lens segments in the sub-lens segments in each of the multiple modals; and obtaining plot demarcation points of the target video based on the relevance of every two adjacent sub-lens segments in each sub-lens segment in each of the multiple modes.

The invention relates to a model training method and device, a performance prediction method and device, equipment, a vehicle and a medium, and the method comprises the steps: obtaining a test data set which comprises a plurality of groups of test sample data, sequentially inputting each group of test sample data into a preset initial model, so as to obtain a first prediction performance parameter corresponding to each group of test sample data, acquiring simulation performance parameters corresponding to each group of test sample data, determining prediction precision of a preset initial model according to the first prediction performance parameters and the simulation performance parameters, and determining a target vehicle performance prediction model according to the prediction precision and the preset initial model, the target vehicle performance prediction model with high vehicle performance prediction precision can be effectively obtained, the vehicle performance corresponding to the vehicle design parameters can be predicted through the target vehicle performance prediction model, the determination efficiency of the vehicle design parameters can be effectively improved, the time cost required by the vehicle from design to machining can be effectively shortened, and the vehicle performance prediction efficiency is improved. And the design cost of a high-performance vehicle can be reduced.

The invention discloses a heat treatment method and device for a magnetic material, a storage medium and computer equipment, relates to the technical field of vacuum sintering, and mainly aims at improving the special treatment effect on the magnetic material and improving the heat treatment efficiency. Comprising the following steps: in response to a heat treatment signal of a target magnetic material, obtaining material attribute information and heat treatment demand information of the target magnetic material and heat treatment furnace attribute information of a target heat treatment furnace; determining a material feature vector of the material attribute information, a demand feature vector of the heat treatment demand information and a heat treatment furnace feature vector of the heat treatment furnace attribute information; performing fusion processing on the material feature vector, the demand feature vector and the heat treatment furnace feature vector to obtain a heat treatment fusion feature vector; the heat treatment fusion feature vector is input into a preset treatment mode prediction model for heat treatment mode prediction, and a target heat treatment mode is obtained; and controlling the target heat treatment furnace to perform heat treatment on the target magnetic material based on the target heat treatment mode.

The invention provides a vehicle clutch state determination method and device, computing equipment and a storage medium. Wherein it is determined whether the vehicle satisfies a condition of calculating a semi-linkage state; if it is determined that the vehicle meets the condition for calculating the semi-linkage state, the engine rotating speed, the hand brake state, the gear state and the GPS speed of the vehicle are obtained; and determining whether the clutch state of the vehicle is in a semi-linkage state or not according to the obtained engine rotating speed, the hand brake state, the gear state and the GPS speed of the vehicle. According to the technical scheme, the determination cost of the clutch state can be reduced, and the determination efficiency of the clutch state can be improved.

The invention relates to a controllable voltage source arc extinction method, control equipment and a computer storage medium, and the method comprises the steps: S1, obtaining three-phase voltage change data outputted after the fault of a power distribution network occurs when the power distribution network has a grounding fault; s2, generating three phase voltage increment matrixes in one-to-one correspondence with the three phase lines according to the three-phase voltage change data; s3, performing sorting conversion on each phase voltage increment matrix to obtain three multi-dimensional data matrixes in one-to-one correspondence with the three phase voltage increment matrixes; s4, performing similarity analysis according to the three multi-dimensional data matrixes to obtain a first similarity coefficient capable of representing the similarity of the phase A and the phase B, a second similarity coefficient capable of representing the similarity of the phase B and the phase C and a third similarity coefficient capable of representing the similarity of the phase A and the phase C; and S5, determining a fault phase according to the first to third similarity coefficients. The fault phase determination method can be simplified, and the fault phase determination efficiency can be improved.

The invention discloses a potential traffic consumption user determination method and system based on interaction information. The method comprises the following steps: identifying traffic associated data of a user based on the interaction information; preprocessing the traffic associated data to obtain standard traffic data of the user, and constructing a multi-dimensional user vector of the user; obtaining package data of a current to-be-promoted traffic package, and constructing a multi-dimensional package vector of the current to-be-promoted traffic package; calculating the vector similarity between the multi-dimensional user vector and the multi-dimensional package vector of the user based on a preset similarity algorithm; and when the vector similarity is greater than a preset similarity threshold, determining that the user is a potential consumption user of the current to-be-promoted traffic plan. According to the technical scheme, the efficiency and accuracy of determining the potential traffic consumption users can be improved.

The invention discloses a confidence coefficient threshold determination method and device and electronic equipment. The method comprises the steps of obtaining a target recognition frame area of a to-be-recognized object in a frame selection target image; and based on the target identification frame area, determining a target confidence threshold for identifying the to-be-identified object, the target confidence threshold being determined based on different confidence corresponding to different identification frame areas corresponding to different shooting parameters. The confidence threshold is automatically determined based on different shooting conditions, the determination efficiency and accuracy of the confidence threshold are improved, and the accuracy of object recognition is improved.

The embodiment of the invention provides a domain name resolution path determination method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring an internet protocol address IP of a target server; generating a prefix part of the second-level domain name according to the IP address of the target server; splicing the prefix part with the secondary domain name to determine a detection domain name of the target server; controlling the client to send an analysis request for the detection domain name to a target server, so that the target server sends a request data packet to an authoritative server; receiving all request data packets sent by the authoritative server, and screening all request data packets according to the detection domain name to obtain a first target data packet; judging whether a source address in the first target data packet is consistent with a target server IP; and if the source address is consistent with the IP of the target server, determining that the analysis path is composed of the client, the target server and the authoritative server. The method is used for achieving the effect of comprehensively restoring the recursive analysis path.

The present specification discloses a method and device for positioning a geomagnetic adaptation area for geomagnetic navigation, specifically comprising: determining a geomagnetic feature map corresponding to the target area according to the geomagnetic information map corresponding to the target area. The geomagnetic feature map is input into a scale division model, and a geomagnetic feature map corresponding to the geomagnetic information map at each image resolution is generated by the scale division model. For each scale feature map, a candidate geomagnetic adaptation area in the target area at the corresponding image resolution is determined. According to each candidate geomagnetic adaptation area, the geomagnetic adaptation area of ​​the target area is determined. Compared with the current technology of manually determining the geomagnetic adaptation area, the method of the present specification is more intelligent and more automated. While the efficiency and accuracy of determining the geomagnetic adaptation area are improved, the consumption of human resources and time costs is also greatly saved, so that the execution efficiency of subsequent geomagnetic route planning based on the geomagnetic adaptation area is also improved.

The invention relates to the technical field of image processing and digital medical treatment, and particularly discloses a dichotomy-based image compression processing method and device, equipment and a storage medium. Obtaining a screen resolution and a picture display demand of the user equipment; determining an initial parameter range of compression parameters of the to-be-compressed picture based on the screen resolution and a picture display requirement; performing dichotomy search in the initial parameter range, and updating the initial parameter range until the latest parameter range meets a preset condition, thereby obtaining a target compression parameter; and based on a preset compression strategy and the target compression parameter, compressing the to-be-compressed picture to obtain a compressed picture. According to the method, the initial parameter range of the compression parameters can be determined according to the screen resolution of the user equipment and the picture display requirement, the parameter range is effectively reduced, the target compression parameters are searched through the dichotomy, the determination efficiency of the target compression parameters is improved, and then the picture compression processing efficiency is improved.

The invention relates to the technical field of artificial intelligence, and provides a 6S violation detection method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a plurality of to-be-detected images; inputting the plurality of to-be-detected images into a target detection model, and determining a predicted violation image from the plurality of to-be-detected images; inputting the prediction violation image and the target prompt instruction into the first multi-mode large model to obtain a violation detection result output by the first multi-mode large model; wherein the first multi-modal large model is obtained by performing fine adjustment on the initial multi-modal large model based on the 6S violation sample image and the violation label corresponding to the 6S violation sample image, and the violation label is obtained by inputting the 6S violation sample image and the violation positioning prompt word corresponding to the 6S violation sample image into the second multi-modal large model. According to the invention, the detection efficiency of 6S violation detection can be improved.

The invention discloses a function time consumption determination method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps that in the process of compiling an application program, first logic codes are inserted into a plurality of function methods included in the application program respectively, the first logic codes are used for determining running time consumption of the function methods, and the function methods are code blocks used for executing different tasks of the application program; in the process of running the application program after compiling, if a first function method in the multiple function methods is run, obtaining running time consumption of the first function method in a mode of reflecting the first function method through a first logic code inserted in the first function method; wherein the mode of reflecting the first function method refers to re-running the first function method. According to the method, the function time consumption determination efficiency is improved.

The application discloses a network coverage quality information determination method and device, equipment and a storage medium, which are applied to the Internet of Vehicles technical field. The method comprises the following steps: acquiring a first analysis data set of N vehicle terminals in a to-be-evaluated area; dividing M pieces of terminal data of each vehicle terminal based on position information corresponding to a time stamp, so as to obtain at least one scene data group; for each scene data group, screening target terminal data based on cell information of an access network service, so as to obtain a second analysis data set; clustering each piece of terminal data in the second analysis data set according to position information of the vehicle terminal; and determining network coverage quality information of a target area according to reference signal receiving power in each piece of target terminal data. In this way, the OTT data of the vehicle terminal, the access cell information and the POI data can be used to identify and check a scene to which terminal data belongs, and the accuracy of the determined network coverage quality information is improved.

The invention discloses a kind of fully connected network control method and device based on OVS, the method includes: when it is determined that all interactive nodes have started OVS service, determine the target root node and non-root node from all interactive nodes, as the central logical node of the target acyclic tree topology to be constructed; according to the node port of spanning tree algorithm and target root node, determine the node topology parameter of each non-root node, the node topology parameter of each non-root node is used to determine the communication path for the non-root node to perform data interaction with the target root node; according to the node topology parameter of target root node, spanning tree algorithm and each non-root node, build target acyclic tree topology and when there is target data to be interacted, according to the target acyclic tree topology and the local node where the target data is located, transmit the target data to the predetermined target interactive node. It can be seen that the implementation of the present invention can improve the processing efficiency of network node failure while improving the connectivity reliability of the network.

The present disclosure provides a network security risk assessment method, device, equipment and medium, including: obtaining security log data of the target network environment; obtaining various target indicator data related to the network risk from the security log data; statistically quantifying each of the target indicator data to obtain each quantitative data; determining the indicator weight corresponding to each of the target indicator data based on the sigmoid function characteristics and the preset indicator upper limit value of each of the target indicator data; wherein the sigmoid function characteristic is a function characteristic that the corresponding function value tends to 1 when the independent variable reaches a certain value; using the preset sigmoid function and based on each of the quantitative data and the indicator weight corresponding to each of the quantitative data to determine the comprehensive risk of the target network environment, and obtain the risk assessment result of the target network environment. It can improve the determination efficiency of the indicator weight and effectively control the numerical range of the comprehensive risk of the network environment, thereby improving the user experience.

The invention relates to the technical field of steel pipe posture positioning, in particular to a steel pipe posture determination method and device, electronic equipment and a storage medium. Carrying out the edge feature extraction of the first pipe end image through a difference and non-maximum elimination mode, and obtaining a first edge image; converting a plurality of edge pixel coordinates in the first edge image into a plurality of edge world coordinates according to an internal reference matrix describing imaging characteristics of the camera and an external reference matrix describing relative attitudes of the camera and a world coordinate system; and finally, fitting the plurality of edge world coordinates through a three-dimensional elliptic equation to obtain the posture of the steel pipe. The posture of the steel pipe is determined through image analysis, contact with a tool fixture is not needed, the efficiency of the determination process is higher, and the speed of positioning the posture of the steel pipe is increased.

The embodiment of the invention provides a fault diagnosis method and circuit of a memory, electronic equipment and a readable medium, and relates to the technical field of integrated circuits, in the method, a test circuit sequentially executes data comparison operation on tested units in the memory according to data comparison operation corresponding to a preset test algorithm. After one-time data comparison operation is executed, a fault capturing circuit generates a single-time fault characteristic value corresponding to target comparison operation under the condition that a comparison result represents that the detected unit has a fault; the target comparison operation is a data comparison operation that the comparison result represents that the tested unit has a fault, and the single fault feature value is used for representing identification information of the target comparison operation; and after all data comparison operations corresponding to the preset test algorithm are executed, identifying the fault type of the tested unit based on all the single fault feature values. Therefore, the fault type of the tested unit can be identified based on all the single fault characteristic values, and then the fault type is determined.

This invention discloses a method, apparatus, storage medium, and terminal for predicting membrane performance based on a joint model. The method includes: obtaining the actual condition parameters required to generate a PVDF-Ni membrane under orthogonal array conditions; inputting the actual condition parameters into a pre-trained membrane performance prediction model; wherein the membrane performance prediction model is a joint model constructed based on an RSM model and an ANN model; and outputting the predicted flux and predicted rejection rate corresponding to the actual condition parameters. Because this application uses an RSM model and an ANN model to construct an RSM-ANN joint model, and uses existing data to train the RSM-ANN joint model to obtain a pre-trained membrane performance prediction model, the pre-trained membrane performance prediction model can predict membrane performance with fewer experimental parameters, thereby improving the efficiency of membrane performance determination and saving significant manpower and resources.

The invention relates to a medical image generation method and device, computer equipment and a storage medium. A target signal evolution curve graph of a scanned object in magnetic resonance fingerprint imaging is obtained; and obtaining a quantitative image of the scanned object according to the target signal evolution curve graph and a preset target quantitative prediction model. In the embodiment of the invention, since the sample weighted image has the quantitative value consistent with that of the gold standard quantitative image, the sample weighted image is utilized to train the quantitative prediction model to obtain the target quantitative prediction model, and the quantitative image is obtained through the target quantitative prediction model, so that the influence of factors such as a magnetization transfer effect in an MRF scanning process can be avoided; and a quantitative image obtained based on an MRF technology is different from a gold standard quantitative image. Moreover, the sample weighted image is used as a gold standard for quantitative prediction model training, a large number of gold standard quantitative graphs do not need to be obtained, and the determination efficiency of the target quantitative prediction model is improved.

The present invention discloses a method, device, storage medium and equipment for determining the height of crops. The method comprises: obtaining point cloud data of a target area; obtaining first position information of at least one vegetation-covered area in the target area, wherein each vegetation-covered area corresponds to a crop; for each vegetation-covered area, based on the first position information of the vegetation-covered area and the second position information of the point cloud data, determining vegetation point cloud data corresponding to the vegetation-covered area from the point cloud data; for each vegetation-covered area, determining the height of the corresponding crop based on multiple elevation values ​​corresponding to the vegetation point cloud data. The present invention solves the technical problem of low efficiency in determining the height of crops.

The application relates to a server change information determination method and device, computer equipment and a storage medium. The application relates to big data and artificial intelligence technology means. The method comprises the following steps: acquiring three-dimensional structure image information of a server room server, feature identification information of all servers contained in the server room server, and current state information of the servers, and collecting real-time change image information of the server room server; the change image information is image information corresponding to a change operation on the server; a feature image of the server contained in each change image information is extracted, and target servers corresponding to each change image information are identified based on the three-dimensional structure image information of the server room server, the feature identification information of the servers, and the feature image of each change image information; and change information of each target server is determined based on the current state information of each target server. The method can improve the determination efficiency of the server change information.

The invention discloses a diagnostic protocol execution method, device and equipment and a readable storage medium, which are applied to the technical field of vehicle diagnosis, and comprise the following steps: determining a first initial diagnostic protocol communicating with a vehicle electronic control unit; when it is determined that the initial diagnosis protocol cannot be matched with the set diagnosis function, optimization is carried out in all diagnosis protocols according to the initial diagnosis protocol, and a target optimal diagnosis protocol is determined; determining whether the target optimal diagnosis protocol is a protocol for realizing a set diagnosis function; and when the target optimal diagnosis protocol is the protocol for realizing the set diagnosis function, determining to execute the set diagnosis function based on the target optimal diagnosis protocol. Compared with the prior art that all diagnosis protocols need to be traversed, optimization can be carried out based on the initial diagnosis protocol, the target optimal diagnosis protocol can be rapidly determined, and the execution efficiency of the diagnosis protocol is improved.