287 results about "Target Response" patented technology

The invention provides a cue word attack detection method and system of a large language model and electronic equipment, and relates to the technical field of text process.The method comprises the steps that a to-be-processed text block in an original text is determined; performing heuristic semantic analysis on the text block to obtain a first suspicious text block and a first risk score thereof; performing semantic analysis on the first suspicious text block and the context information thereof through a first language model to obtain a second suspicious text block and a second risk score thereof; performing structured verification of the attack intention on the second suspicious text block according to a preset meta prompt word through a second language model to obtain an attack intention verification result; the attack intention verification result comprises a third suspicious text block and a third risk score thereof; and executing a target response action on the original text based on the first risk score, the second risk score and the third risk score. According to the method, the efficient processing requirement of the long text can be considered, and the detection accuracy of complex attacks can be improved.

Disclosed in the present invention are a method and apparatus for synthesizing spatially cross-correlated multi-point ground motions fitting a response spectrum. The method comprises: using an influence matrix method to obtain ground motion acceleration time histories fitting a target reaction spectrum with high precision, and calculating a Fourier amplitude spectrum and a phase spectrum thereof; and considering a calculation relationship between a power spectral density function and the Fourier amplitude spectrum, taking the power spectral density function of the obtained time histories as an initial value, using a random vibration theory and Cholesky decomposition to obtain spatially cross-correlated multi-point ground motion time histories, further taking into account a phase spectrum of the ground motion time histories fitting the target reaction spectrum with high precision, and performing correction and iteration to obtain spatially cross-correlated multi-point ground motions fitting a response spectrum. The present invention overcomes the shortcomings in current multi-point ground motion time history synthesis techniques, such as the difficulty in ensuring good fitting to a target response spectrum and the non-stationarity of synthesized ground motions, helping to improve the reliability of dynamic response analysis results for large-scale engineering structures under the action of multi-point ground motions.

The invention discloses an automatic extraction method for semiconductor device model parameters, and the method comprises the steps: obtaining a multi-target response through the key parameters of a semiconductor device model, and constructing and training an agent model to predict a target response mean value and uncertainty parameters; constructing a multi-objective optimization collaborative circulation framework assisted by an agent model; generating a candidate parameter population in key parameters according to a position updating mechanism of a multi-objective optimization algorithm, predicting candidate parameters by using a trained proxy model, selecting the candidate parameters according to a prediction result to carry out real simulation evaluation, adding an obtained real sample into a non-dominated file, and updating the file based on a non-dominated relationship. Adding a training set dynamic updating agent model into the real sample, generating a potential search trajectory, selecting a representative representative Pareto approximate solution from the potential search trajectory, and updating the position of the population and the direction of the next-generation search trajectory according to the representative solution selected from the file; and terminating the circulation, outputting the solution set in the file, and checking.

Provided are a model distillation method and apparatus. The method comprises: acquiring a fixed training dataset, wherein the fixed training dataset comprises a plurality of training text sequences; guiding, by means of a teacher model, a student model to generate target response text sequences on the basis of the training text sequences, so as to correct semantic differences between response text sequences output by the student model and response text sequences output by the teacher model; on the basis of the plurality of training text sequences and a target response text sequence corresponding to each of the plurality of training text sequences, obtaining a target training dataset; and on the basis of the target training dataset and the teacher model, performing distillation training on the student model. In the present application, semantic differences between outputs of the teacher model and outputs of the student model are marked and evaluated one by one at a sequence level, and errors are identified and corrected, such that the student model is guided to generate more reliable and diversified samples, thereby improving the training effect of the student model.

The application discloses a display panel driving method, a driving device and a readable storage medium, and relates to the technical field of display, which is characterized in that: an initial response square wave signal is converted based on a current display temperature to obtain a target response square wave signal; a target duty cycle in the target response square wave signal is used to determine a calling requirement, so as to determine a response duration corresponding to a normal output display picture of a liquid crystal display device at the current display temperature; a target response duration parameter table meeting the calling requirement is called; and the display panel at the current display temperature is driven according to the target response duration parameter table, so that the reaction speed of various pixel points to an input display signal at various temperatures is effectively accelerated, and the adverse situation that an animation picture is still blurred and ghosted due to the fact that different temperatures cannot be considered is avoided.

The invention belongs to the technical field of water traffic transportation safety and navigation mark navigation aiding, and mainly relates to a navigation mark anti-collision early warning method based on multi-sensor fusion, and the method comprises the steps: constructing a multi-sensor fusion architecture integrating an AIS terminal, a laser radar and an AI camera, and achieving the omnibearing monitoring and precise recognition of a ship in a navigation channel; a grading response mechanism is adopted, corresponding functions are dynamically started according to the real-time distance between the ship and the navigation mark, and targeted response from early warning to emergency warning is achieved; a legal evidence chain packaging mechanism is introduced, a unique ID is generated for each early warning event, formatted evidence is stored in an associated mode, and integrity and traceability of data are ensured; through a dynamic energy supply strategy, an equipment operation mode is intelligently adjusted according to a storage battery voltage threshold value, and continuous and stable work of the system under the conditions of cloudy and rainy days, night and the like is guaranteed; according to the invention, the accuracy, timeliness and reliability of navigation mark collision early warning information are effectively improved.

The invention discloses a flora prediction and petroleum pollution remediation method based on machine learning. The method comprises the following steps: collecting multiple groups of experimental data of a diesel oil pollution sample treated by a microbial agent, extracting environmental factors, microbial community characteristics and target response variables to construct a training data set after missing value processing, abnormal value detection and standardized pretreatment, and importing the data set into a preset machine learning model to obtain a training result; carrying out feature learning, classification training and hyper-parameter optimization by adopting a GridSearchCV method in combination with 10-fold cross validation; evaluating the correlation between a target response variable classification result and the features through a multivariable Pearson's correlation matrix, and constructing an optimal test set; and finally, selecting an optimal prediction model according to a preset index. According to the method, the model training quality is improved through data preprocessing and correlation analysis, efficient flora prediction and algorithm application evaluation are achieved by means of multiple machine learning algorithms, scientific support is provided for petroleum pollution remediation, and remediation accuracy and efficiency are improved.

The invention relates to a fine-grained target real-time image segmentation method and system based on a dynamic state modeling network, and belongs to the technical field of intelligent image processing. The method comprises the following steps: extracting multi-scale detail features by using a lightweight backbone network; through a dual-scale two-dimensional selective scanning module, the features are divided into a thin branch and a thick branch, and local scanning and global scanning are executed respectively; a dynamic cross-scale feature selection and aggregation module is adopted, redundancy is suppressed through reweighting and statistical filtering, and key target responses are highlighted; at a decoding end, local details and global semantics are fused through jump connection and an edge extractor; and finally, introducing a form-guided pseudo label hierarchical supervision strategy, and improving the structure learning ability of the model by using a coarse-to-fine morphological prior. According to the method, the segmentation precision, the boundary integrity and the tiny target recall rate of the fine-grained target under the scenes of ore separation, industrial defect detection, pavement crack recognition and the like are remarkably improved.

The invention relates to an interface adaptation method and system for reconstruction and integration of a complex information system module. The method comprises the following steps: acquiring a protocol mapping rule and constructing a rule base; monitoring and receiving a calling request which is sent by a source module through a transmission layer protocol and carries source module side interface protocol format data; analyzing the request, stripping a source module side transport layer protocol header to extract application layer data, and packaging the application layer data into an internal general data model; performing structure mapping, data conversion and dynamic logic processing on the model through a rule execution engine according to a request mapping rule of a rule base, reconstructing the model into target request data according to a target module interface format, and sending the target request data to a target module through a target side transport layer protocol; receiving target response data, stripping a transport layer protocol header of the target response data, analyzing the target response data to the internal general data model, and performing reverse conversion according to a response mapping rule to enable the data to conform to a source side interface format; and packaging the back-to-source module side transport layer protocol back to the source module. By adopting the method, the adaptation flexibility and the maintenance efficiency can be improved.

The invention relates to the technical field of artificial intelligence and medical information processing, and discloses a user session response system and method based on health data, equipment and a medium. The system comprises a session semantic recognition module, an entity information extraction module, an archive data alignment module, a health classification tree construction module, a data hierarchical matching module and a response text generation module. The method comprises the following steps: recognizing consultation semantics contained in a health consultation session of a target user; determining a target session text in the health consultation session according to the consultation semantics; performing data alignment on the medical entity information in the target session text according to the historical health file, constructing a structured health file based on a data alignment result, and generating a health state classification tree; performing classification matching on the consultation semantics by utilizing the health state classification tree to obtain a target health state classification; and generating a corresponding target response text based on the target health state classification, and pushing the target response text to the target user side. According to the invention, the healthy session response accuracy can be improved.

The invention discloses a large model deployment and service method and device for realizing intelligent customer service based on container arrangement, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the steps: constructing a standardized container mirror image which comprises an inference engine, a model acceleration library and a model encryption and decryption assembly and is adaptive to an intelligent customer service scene; establishing a graphic processing unit resource management system in the container arrangement cluster; storing model data of the intelligent customer service model to a target storage system, and determining a mounting mechanism corresponding to the model data; generating a container arrangement and deployment file based on a graphic processing unit resource management system, the operation demand of the standardized container mirror image and a mounting mechanism corresponding to the model data; and submitting the container arrangement deployment file to a container arrangement platform, so that the container arrangement platform carries out intelligent customer service model deployment, and the deployed intelligent customer service model is utilized to receive a user request and return a corresponding target response. According to the method, the deployment complexity is reduced, and the model deployment efficiency and stability are improved.

The embodiment of the invention provides a data synchronization communication method and device, equipment and a storage medium, and the method comprises the steps: responding to an interface calling request, configuring a target shared memory of the interface calling request, and the target shared memory comprises target calling information; after the reference information of the target shared memory is sent to a second thread corresponding to the primary layer, entering a blocking waiting state, so that the second thread performs processing based on the reference information to obtain target response information and notifies the first thread to end the blocking waiting state; and after the blocking waiting state is ended, obtaining target response information from the target shared memory, and feeding back target result information. According to the scheme, lightweight and efficient synchronous interface calling can be realized, and the communication efficiency is improved.

Provided are an intelligent design method and device for a thick-plate joint of longitudinal and cross members of an aluminum alloy vehicle frame. The intelligent design method includes: establishing a finite element model of a vehicle frame, analyzing static performance and fatigue performance of the vehicle frame under bending and torsion conditions, and selecting a connection joint of longitudinal and cross members with weak static performance and fatigue performance on the vehicle frame as a submodel; with connection parameters of the submodel as design variables, obtaining, by simulation, sets of training samples and a corresponding target response data set; establishing forward and inverse mapping relationships between design variables of a connection joint of longitudinal and cross members and target responses; and then on the basis of fully training the neural network model, obtaining an optimal layout scheme of connection joint fasteners of longitudinal and cross members by prediction and optimization.

The invention provides a code vulnerability coping strategy generation method and related equipment. The method comprises the following steps: in response to a log recording instruction, generating a target log query statement according to the type of the log recording instruction; wherein the target log query statement is used for querying logs related to log4j vulnerability attack behavior characteristics; executing the target log query statement to obtain a target log query result; according to the target log query result, judging whether the log recording instruction contains a suspected log4j vulnerability attack execution behavior or not; if yes, link identification is carried out on the log4j vulnerability attack based on the target log query result, and a target attack link is obtained; and according to the target attack link, generating a target coping strategy for the log4j vulnerability attack. The network security defense capability can be improved.

The invention belongs to the technical field of computers, and particularly relates to a system fault response method, a system fault response device and electronic equipment. The method comprises the following steps: acquiring a fault injection event; mapping the fault injection event according to the fault injection model to obtain a fault score corresponding to the fault injection event; mapping the fault injection event according to a strategy matching model to obtain a target response strategy and a strategy matching score corresponding to the target response strategy; updating model parameters of the fault injection model or the strategy matching model according to a numerical relationship between the fault score and the strategy matching score; and generating a response strategy for a real system fault detected by the transaction management system according to the strategy matching model after the model parameters are updated. According to the invention, system fault response intelligence and automation can be realized.

The invention discloses a voice interaction-oriented end-cloud collaborative large model reasoning scheduling method and device, and relates to the technical field of artificial intelligence and man-machine interaction. The method comprises the following steps of: after responding to a user voice instruction, constructing an environment state vector by acquiring a terminal network state parameter and a terminal operation state parameter; the method comprises the steps that firstly, a voice instruction is obtained, then the voice instruction is analyzed and preprocessed to obtain task feature vectors, reasoning path decision is conducted based on the two vectors to generate an end-cloud cooperative reasoning path scheduling scheme, then path reasoning is executed according to the scheme to obtain an initial response result, and finally a target response result is determined according to a path starting state corresponding to the initial response result. The method optimizes the stability of the response quality, and ensures that the response result meeting the user demand can be output in a weak network scene or a complex instruction scene through adaptive screening and integration of inference results of different paths. The problem of poor stability and reliability of user voice interaction experience caused by insufficient balance capability in the prior art is solved.

This application relates to a high-reliability anti-modeling APUF circuit and a battery passport anti-counterfeiting device. The high-reliability anti-modeling APUF includes multiple cascaded dual-path units, at least one feedforward decision module, at least one inter-stage connection structure, and an arbitration module. The input of the feedforward decision module is connected to the output of the first dual-path unit. The feedforward decision module is used to generate a first path selection signal based on the pulse signal output by the first dual-path unit. The inter-stage connection structure is located between the second and third dual-path units. The inter-stage connection structure is used to determine the inter-row crossover transmission mode of the pulse signal in the third dual-path unit based on the first path selection signal. The arbitration module includes multiple first arbitrators and an XOR gate. The XOR gate is connected to each first arbitrator and is used to XOR the arbitration results output by each first arbitrator to obtain the target response result. This APUF improves the reliability of battery passport anti-counterfeiting.

The application provides a vehicle control method and a vehicle, and belongs to the technical field of vehicle control. The vehicle control method comprises the following steps: obtaining a traffic risk level of a road section in front of the vehicle and current state information of the vehicle, and the vehicle is provided with an active suspension; determining a target response strategy based on the traffic risk level and the current state information; and controlling the vehicle to execute the target response strategy, wherein the target response strategy comprises a height adjustment strategy of the active suspension. Thus, different traffic risk levels are divided according to the road conditions of the road section in front of the vehicle, and different target response strategies are provided in combination with the current state information of the vehicle, for example, direct traffic, traffic after height adjustment, or detouring in the case that there is still a risk of scratching after adjustment. Therefore, the vehicle intelligently and objectively controls the corresponding target response strategy based on different traffic risk levels and the current state of the vehicle, timely and effectively prevents scratching during vehicle driving, and improves vehicle safety.

This application provides a method, apparatus, electronic device, and storage medium for determining responses to questions, belonging to the technical field of question response determination, and applicable to scenarios in financial, medical, health, and elderly care insurance application systems. The method includes: responding to a question input by a user, performing semantic and compliance constraints on the question, and generating a structured control vector corresponding to the question; inputting the structured control vector into multiple perturbation decoding heads, and generating candidate response sequences corresponding to the business semantic distribution of the question and each perturbation decoding head based on the structured control vector; wherein the business semantic distributions of the multiple perturbation decoding heads are different; and determining the target response sequence for the question based on the candidate response sequences. This application improves the diversity and accuracy of responses by constructing a structured control vector through pre-generation semantic and compliance constraints, and by generating candidate responses in parallel using perturbation decoding heads with differentiated business semantic distributions.

The application belongs to the technical field of component fatigue test loading node load determination, and particularly relates to a component fatigue test loading node load determination method, which comprises the following steps: determining a component fatigue test loading node; equivalently taking each loading node as a plurality of loading points, wherein one loading point corresponds to a plurality of loading nodes; determining loading loads corresponding to each loading point under each working condition; constructing a component fatigue test finite element model; constructing a component theoretical state finite element model; taking the loading loads of each loading point corresponding to each working condition as variables, taking a theoretical total load and a total moment as equality constraints, taking a control section error as inequality constraints, limiting the upper and lower limits of the loading loads of each loading point, taking a target response error under the component fatigue test and the theoretical state finite element model as a target variable, obtaining the loading loads of each loading point, and further obtaining the loading loads of each loading node.

The invention provides a battery pack positioning and tracking method, system and device and a medium, and relates to the technical field of battery pack management, and the method comprises the steps: dividing an operation region into a plurality of sub-regions according to the region characteristics of the operation region of an electric tool; in response to a battery pack searching request sent by a user terminal, acquiring signal intensity values of wireless signals emitted by the battery pack and received by the signal receivers; according to the signal intensity value, determining a target sub-region of the battery pack in the operation region and environment characteristics of the target sub-region; obtaining the disengagement duration of the battery pack disengagement from the electric tool and the residual electric quantity when the battery pack disengages from the electric tool; and on the basis of the separation duration, determining a target response module in a running state in a plurality of response modules in the battery pack in combination with the environmental characteristics and the residual electric quantity, and generating a tracking plan of the target response module. The method has the technical effects that the positioning accuracy of the battery pack is improved, and the actual industrial application requirement is met.

The invention relates to a partial discharge signal identification method, device and equipment, a medium and a program product. The method comprises the following steps: acquiring original partial discharge pulse data of to-be-detected equipment; inputting the original partial discharge pulse data into a pre-trained partial discharge signal enhancement model to obtain enhanced partial discharge pulse data; matching the enhanced partial discharge pulse data with a standard pulse signal to obtain candidate partial discharge pulse data; acquiring response feature information of the to-be-detected equipment; and inputting the candidate partial discharge pulse data and the response feature information into a partial discharge identification model, respectively executing feature extraction to obtain a to-be-detected partial discharge pulse feature and a response distribution feature, and obtaining a target response identification result of the to-be-detected device based on the to-be-detected partial discharge pulse feature and the response distribution feature. By adopting the method, multi-dimensional features such as a topological structure and an operation state of the equipment can be fused, the identification accuracy is high, and the anti-interference capability is strong.

The application provides a millimeter wave radar clutter point removal method and device based on spectrum matching, a medium and a program product. The method comprises the following steps: acquiring a multi-channel echo signal, constructing a measured angle spectrum reflecting the energy distribution of each direction through beam forming and angle traversal processing; determining each effective target angle of the measured angle spectrum; based on the geometric structure parameters of the millimeter wave radar array and the effective target angle, weighting and superimposing each target response based on a theoretical echo signal model to obtain a theoretical angle spectrum; performing spectrum matching analysis on the theoretical angle spectrum and the measured angle spectrum, performing point-by-point translation processing on the theoretical angle spectrum along the angle axis, and calculating the cross-correlation coefficient distribution of the two at different angle offsets; when the cross-correlation reaches a maximum value at zero angle offset and is greater than a threshold value, it is determined that the corresponding measured angle spectrum is effective, otherwise it is regarded as a clutter point and removed. The application realizes accurate identification of real targets by using the change characteristics of the cross-correlation coefficient at different angle offsets.

The invention relates to a database connection method and device, computer equipment, a medium and a program product. The method comprises the following steps: acquiring connection request information and global singleton object data from a client, and obtaining a mapping relationship between an elastic public network address and a virtual private cloud address; obtaining an original response result which corresponds to an original main node confirmation command of the client and comprises address information of the replica set node; under the condition that it is determined that the connection request needs to be subjected to elastic public network address replacement according to the connection request information and the global singleton object data, a virtual private cloud address in the original response result is replaced with a corresponding elastic public network address according to the global singleton object data, and a target response result is obtained; and sending the target response result to the client, and establishing connection between the client and each node of the replica set according to address information in the target response result. By adopting the method, the database connection flexibility can be improved on the basis of ensuring the security isolation of the cloud database.

This application provides a method, apparatus, and device for data processing, as well as a computer storage medium. The method relates to the field of intelligent response technology and is applied to an intelligent response system, which includes machine response and human response. The method includes: acquiring input data received by the intelligent response system; the input data includes input data from the questioner and input data from the human responder; performing keyword detection on the input data based on a preset keyword set to obtain corresponding target detection results; the target detection results include the overall distribution information of target key data in the keyword set within the input data; if, based on the target detection results, it is determined that target key data exists in the input data, then obtaining the order of appearance of the target key data based on the overall distribution information; based on the order of appearance and combined with a preset response data set, outputting corresponding target response data to the source of the input data respectively.

Embodiments of the present application provide a service providing method, system, gateway, device and storage medium, the method comprising: a gateway in a first transmission network acquires a preset performance index met by a second transmission network, and in the first transmission network, determines a target response subject whose real-time performance index meets the preset performance index. Then, the identification information of the target response subject is fed back to the second transmission network, so that the target response subject responds to a service acquisition request. It can be seen that in the above method, the gateway can acquire the preset performance index met by the second transmission network, that is, the network capability of the second transmission network is opened to the first transmission network. Then, the gateway returns the information identification of the target response subject in the first transmission network to the second transmission network, which is equivalent to opening the network capability of the first transmission network to the second transmission network, that is, the mutual opening of the capabilities between the two transmission networks can be realized by means of the gateway.

The invention provides a measurement knowledge intensive retrieval enhancement generation method and system. The method comprises the following steps: constructing a multi-level measurement knowledge base structured index; constructing a vector database based on a structured knowledge base corresponding to the structured index; and encoding a user query, performing similarity matching on the encoded query and the vector database, and inputting a matching result into the large language model to obtain a target response result. According to the method and the device, when the new rule is metered to be released, the new rule is analyzed into the semantic unit, the structured index and the coding vector update database are supplemented, the large model can generate the response based on the new knowledge, the large model does not need to be retrained, and the problem that knowledge update is lagged in a traditional method is solved.

The invention provides an ISAC near-field channel robust beam forming optimization method and device based on MMSE estimation. The method comprises the following steps: carrying out system modeling and signal configuration on an ISAC system; accurately modeling a near field communication channel by adopting a spherical wave model, calculating to obtain an SINR (Signal to Interference plus Noise Ratio) of a user, and introducing an outage probability constraint; establishing a sensing model under a far-field condition, and estimating a target response matrix by adopting an MMSE criterion to obtain a sensing MSE; introducing an enhanced waveform to improve the perception DoF, and updating the SINR; an enhanced covariance matrix is introduced, the minimum perception MSE is used as an optimization target, the outage probability constraint, the total power constraint and the positive semi-definite constraint updated according to the updated SINR are used as constraint conditions, and an ISAC near-field channel robust beam forming optimization problem is constructed; a non-convex problem is converted into a convex form through combination of semi-definite relaxation SDR and an optimization framework of a spherical boundary and S-lema, and a beam forming optimization matrix is solved and obtained by obeying the constraint of a linear matrix inequality LMI. According to the invention, beam forming can be optimized.

The invention discloses a vehicle control method and device, equipment, a storage medium and a program product. The method comprises the steps of determining a target vehicle of a current vehicle to-be-simulated driving experience; obtaining the current driving operation of the current driver received by the current vehicle; a target response parameter corresponding to the current driving operation is obtained through a driving model corresponding to the target vehicle, the driving model is obtained through imitation learning according to the sample driving operation and a sample response parameter, and the sample response parameter is obtained through conversion of an original response parameter of the target vehicle responding to the sample driving operation; the driving feedback of the current vehicle responding to the sample driving operation according to the sample response parameter is similar to the driving feedback of the target vehicle responding to the sample driving operation according to the original response parameter; and controlling the current vehicle to respond to the current driving operation according to the target response parameter. The driving experience of the vehicle can be enriched.

The application relates to the technical field of circumferential road paving topology reconstruction, and particularly discloses a circumferential road paving topology reconstruction method for a grounding grid drawing missing working condition, which injects a pulse sequence signal carrying a unique pseudo-random code feature, accurately extracts a target response from a strong interference background by using cross-correlation operation, and improves detection anti-interference capability; meanwhile, a conductor intersection point or a branch point is pre-judged by using external stray current information, and the requirement for detection equipment resolution is reduced; a preliminary conductor path diagram is generated by connecting path tracking coordinate points, and a topology node to be verified is identified based on an interference field intensity diagram; finally, a branch path is confirmed by multi-directional detection, and a complete grounding grid topology structure diagram is generated; the method aims to solve the problems of grounding grid drawing missing or inconsistency with the actual due to historical reasons or poor data management, and has high precision, high efficiency and high safety, and provides a solid data basis for grounding grid operation and maintenance.