824 results about "Target Response" patented technology

The invention discloses a knowledge base enhancement generation method and system based on hybrid retrieval and fact verification. The method comprises the following steps: receiving an original query of a user; performing intention analysis and rewriting on the query, identifying an intention type and generating a sub-query adapted to retrieval; executing mixed retrieval of vector retrieval, keyword retrieval and selectable knowledge graph retrieval based on the sub-query, and recalling related knowledge fragments; performing deduplication clustering, fact conflict recognition processing and correlation reordering on the knowledge fragments; according to the intention type and the reordered knowledge fragment, dynamically selecting a prompt template to construct an enhanced prompt; and sending the enhanced prompt into the large language model, and generating a target response with the reference source. According to the method, knowledge recall comprehensiveness is improved through mixed retrieval, knowledge reliability is ensured through fact verification, generation logicality is enhanced in combination with dynamic prompt construction, and response accuracy and credibility are improved.

The invention provides a multi-heat-source multi-material additive manufacturing optimization method and system based on machine learning, and relates to the field of additive manufacturing, and the method comprises the following steps: collecting process parameters, material physical properties and target response data in real time, and constructing a multi-source data set; on the basis, a multi-task learning model is trained, common features are extracted, target responses are synchronously predicted, a proxy target function is constructed through predicted values, if errors exceed a threshold value, experimental verification is conducted, and new data is fed back to update the model. And applying the weight coefficient to a multi-objective evolutionary algorithm, iteratively screening a Pareto candidate solution set, verifying a high-uncertainty solution, and updating the model to error convergence. And selecting and deploying an optimal parameter combination by using an entropy weight-TOPSIS method, and embedding an online learning mechanism to form closed-loop optimization. According to the method, multi-task learning and a self-adaptive evolutionary algorithm are combined, and efficient optimization of multi-heat-source multi-material additive manufacturing process parameters can be achieved.

The invention relates to the technical field of artificial intelligence, in particular to an agent-based question and answer method and device, equipment and a medium. The main agent obtains to-be-processed data input by a user for the to-be-executed task in the first dialogue round; determining a target intention of the to-be-processed data, determining a target response agent corresponding to the target intention in a plurality of response agents according to a pre-stored corresponding relationship between different intentions and the response agents, and sending the to-be-processed data to the target response agent; the target response agent processes the to-be-processed data based on a pre-configured large model of the target response agent, obtains a processing result and feeds back the processing result to the main agent; and the main agent receives and outputs the processing result, and the data to be processed are processed by using the large model, so that the question and answer accuracy is improved.

The invention relates to the technical field of data processing, and discloses a power grid fault early warning system based on machine learning and a related device, and the system is characterized in that an initial monitoring module identifies and identifies abnormal data points through monitoring the voltage, current and load of a power grid, and obtains an abnormal mode identification result; the load fluctuation analysis module positions the abnormal node according to the abnormal mode identification result to obtain abnormal node positioning information; the trend analysis and prediction module evaluates and predicts fault nodes and time according to the abnormal node positioning information to obtain a risk prediction result; the strategy formulation and response module formulates an operation instruction based on the risk prediction result to obtain a fault prevention measure; the fault simulation and test module performs virtual fault simulation by adopting fault prevention measures, and performs iterative optimization on a strategy to obtain a test evaluation result; and the fault early warning and optimization module optimizes a fault prevention strategy according to a test evaluation result, and a more accurate target fault early warning and a faster and more effective target response strategy can be obtained.

An interactive method based on a large model, a training method, and an intelligent agent, which relate to fields of artificial intelligence, speech recognition, speech interaction, deep learning, large models, and application scenarios of knowledge search, autonomous driving, intelligent customer service, intelligent speech control, smart e-commerce, AI healthcare. The interactive method includes: acquiring a request speech; performing a speech recognition on the request speech to obtain a speech recognition feature representing a request semantics; and processing the speech recognition feature using the large model to obtain a response text, where the response text includes response words arranged in sequence, a target response word among the response words is determined by processing the speech recognition feature and an associated response word feature using an attention fusion layer of the large model, and the associated response word feature is related to an associated response word arranged before the target response word.

The invention discloses a near-field flux-sensing integrated Bayesian Cramer-Rao bound beamforming optimization method, which aims at minimizing the Bayesian Cramer-Rao bound of an extended target response matrix, and constraint conditions comprise the maximum transmitting power of a base station, the minimum signal to interference plus noise ratio requirement of a communication user and the minimum energy efficiency of a system. Auxiliary variables are introduced, an original optimization problem is converted into an equivalent full-digital beam forming matrix optimization problem, and iteration is carried out by adopting a sequential convex approximation method until convergence is carried out to obtain a local optimal solution; aiming at the local optimal solution, constructing an optimization problem by using a method of approaching an equivalent full-digital beam forming matrix by using a hybrid beam forming matrix; and an analog beam forming matrix and a digital beam forming matrix are obtained through an alternate optimization method. According to the method, the Bayesian Cramer-Rao bound minimum transmitting beam design problem of the near-field communication and sensing integrated system is researched, and sensing of an extended target can be realized under the condition that the communication energy efficiency of the system is met.

The invention relates to the technical field of building construction monitoring, and discloses a construction progress real-time monitoring system based on BIM and Internet of Things, and the system comprises an Internet of Things data collection module which obtains real-time construction data through a sensor network and divides the real-time construction data into a spatial position flow and an equipment state flow; the BIM data integration module processes the two types of data streams to generate a first progress index and a second progress index; the progress deviation analysis module is combined with a preset progress reference model, and the progress indexes are fused and then mapped into a progress deviation value; the response decision module calls a preset scheme based on the deviation value to generate a target response strategy; the central processing unit is responsible for data transmission and logic verification. In addition, the system is further provided with a construction linkage module, an instruction output module and a progress storage module which are respectively used for optimizing resource scheduling, sending control commands and archiving data. According to the system, real-time monitoring, deviation analysis and dynamic adjustment of the construction progress are realized, and the intelligence and accuracy of construction management are improved.

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.

The invention provides a data processing method and device based on a multi-modal agent, and is applied to terminal equipment in an intelligent teaching system, and the method comprises the steps: obtaining a target teaching identity of a user and a target teaching scene where the user is located; determining and calling a reference agent corresponding to the target teaching scene as a target agent; collecting user request information input by a user through a target agent, and determining a target response result corresponding to the target application function based on data interaction operation between the target agent and the large model base; and after the target agent receives a target response result returned by the large model base, realizing a target application function according to the target response result. Therefore, the terminal equipment can match the intelligent agent corresponding to the teaching scene according to the user identity, and further provides the corresponding application function service, so that the scene adaptability is improved, and the intelligence and practicability of the teaching system are improved.

The invention relates to the technical field of servers, and discloses a workflow instance starting method, device and equipment and a service system. The method comprises the following steps: starting and sending an approval service request to a message queue, wherein the approval process is at least the same as the approval process of a second service; monitoring a response message fed back by the workflow service in real time in the message queue according to a preset association relationship, the preset association relationship including a corresponding relationship between each type of service and a theme; and when a target response message corresponding to the approval service request is monitored, analyzing the target response message, determining that the workflow instance corresponding to the approval service request is successfully started according to the content in the target response message, and executing the approval operation of each node in the workflow instance according to the workflow instance. According to the method, the starting of the approval process is more accurate and efficient. Moreover, the code change of one party does not affect the code of the other party, so that the code processing time is shortened, and the workflow instance starting and approval efficiency is improved.

The embodiment of the invention provides a multi-core network-on-chip transaction processing system, method, device, medium and product, the multi-core network-on-chip transaction processing system comprises a plurality of clusters, each cluster comprises four processing cores, a slave node and a master node, each processing core is provided with a cache, each slave node is provided with a slave node, and each slave node is provided with a slave node; the slave node is provided with a private cache, and the slave node comprises a four-stage pipeline architecture; the slave node is used for processing a request transaction through the four-stage pipeline architecture and generating a target response message or target response message data under the condition that the request transaction is received, and the four-stage pipeline architecture is constructed based on different clock periods and is used for periodically processing the request transaction.

A method of performing a task based on a large model and an electronic device are provided, which relate to artificial intelligence technology, and in particular to fields of voice interaction, deep learning, large model, etc. The method includes: acquiring a demand feature characterizing a demand intention; performing a task by using the large model according to the demand feature, to obtain a response text, in which a target response word is determined based on: determining a query feature for each attention subtask in the task based on an associated response word feature; and performing, based on the demand feature read from a storage unit as a value feature and a key feature shared by the plurality of attention subtasks, the plurality of attention subtasks by using a computing unit according to a plurality of query.

The invention discloses a near / span strike-slip fault seismic oscillation synthesis method for a bridge structure. The method comprises the following steps: step 1, selecting a near fault pulse type seismic record matched with a target response spectrum according to a bridge site and a wave selection principle; 2, rotating and changing the seismic record to parallel and vertical fault directions, and decomposing the seismic record into a high-frequency component and a low-frequency component by using a filter; and step 3, further decomposing the low-frequency component based on continuous wavelet variation, simulating a pulse component by using a pulse function, and introducing a particle swarm optimization algorithm to determine a fitting parameter. And 4, superposing the residual component, the artificial fitting pulse and the high-frequency component to obtain broadband near-fault seismic oscillation. And 5, selecting a pulse waveform with a slip effect and a directivity effect to replace the fitting pulse, extracting a sub-high-frequency component in the residual component, and finally superposing the sub-high-frequency component and the high-frequency component to obtain cross-fault seismic motion, thereby realizing accurate simulation of strike-slip fault ground motion.

The embodiment of the invention provides a distributed data service cluster access method and device, electronic equipment and a storage medium, and belongs to the technical field of finance and the field of medical services, and the method comprises the steps: obtaining a target business request from a target business scene and cluster configuration information of a distributed data service cluster; determining a target service cluster in a plurality of distributed data service clusters based on the target service request; searching a corresponding cluster access instance in a historical instance library according to the cluster configuration information; if the matched cluster access instance is found, determining the found cluster access instance as a target cluster access instance; if the cluster access instance is not found, creating a target cluster access instance according to the cluster configuration information; and performing data access on the target service cluster through the target cluster access instance to obtain target response data. According to the embodiment of the invention, the development complexity caused by environment change of the distributed data cluster can be reduced, so that the stability of data access is improved.

The invention relates to a multi-modal multifunctional composite metasurface design method and device and a medium, and the method comprises the steps: carrying out the parameterized sampling of the key size of a unit structure through Latin hypercube sampling, and generating a training sample set; electromagnetic simulation is carried out on the sampled structure to obtain two-state electromagnetic response data, and a mixed variable database is obtained; according to the target response, generating a plurality of groups of candidate structures through a generator in the improved conditional variation auto-encoder generative adversarial network, screening the candidate structures through a predictor, calculating a prediction comprehensive error, and selecting a preset number of candidate structures with the minimum prediction comprehensive error to perform full-wave simulation verification; and obtaining a simulation double-state response, calculating a simulation comprehensive error, and judging the current candidate structure according to a preset comprehensive error threshold value. Compared with the prior art, the method has the advantages of multi-state collaboration, low calculation cost, high degree of freedom and the like.

The invention relates to the technical field of electric power communication security, in particular to a power grid data secure transmission system and method based on quantum cryptography and a medium, comprising: a power grid data access module extracts identities of a power grid data request end and a target response end; the quantum key distribution module obtains an original shared key pre-stored by the two communication parties, and generates a quantum key according to the one-time session password and the original shared key; the communication security management module analyzes the shared key information from the quantum key received by the target response end to obtain analyzed shared key information, and performs communication security verification on the original shared key and the analyzed shared key information; and the power grid security communication module encrypts the to-be-transmitted power grid data when the communication security verification result is that the verification is passed, and transmits the power grid encrypted data to the target response end. Through cooperation mechanisms such as quantum key dynamic distribution and security verification, security protection of power grid data transmission is realized, and power grid data communication security is improved.

The invention discloses an interaction method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: carrying out the intention recognition of target demand information inputted by a user, and obtaining a target intention task; splitting the target intention task to obtain at least two sub-intention tasks; executing the corresponding sub-intention task by using the first target agent corresponding to each sub-intention task to obtain a sub-execution result corresponding to each sub-intention task; and generating target reply information fed back to the user based on the sub-execution results corresponding to the sub-intention tasks. In this way, the requirements of the user can be efficiently and accurately met.

The invention discloses a service execution method, device and equipment and a storage medium, the method is applied to request response service, and the method comprises the following steps: obtaining a request message of an interface calling request sent by a target terminal based on a first service instruction; analyzing a request path of the request message, and determining an interface identifier of a back-end interface to be called; based on a target verification configuration file corresponding to the interface identifier, verifying a to-be-verified parameter in the request message; under the condition that the verification is passed, generating a rule based on a dynamic parameter contained in a target response configuration file corresponding to the interface identifier, and randomly generating dynamic message data; assembling the fixed message data and the dynamic message data contained in the target response configuration file to obtain a first response message; and sending the first response message to the target terminal, so that the target terminal executes a second service instruction triggered based on the target response message. By utilizing the scheme of the invention, the service security can be ensured, and the interface request is flexibly and efficiently responded.

The invention relates to the technical field of artificial intelligence, can be applied to the medical field and the financial science and technology field, and discloses a dialogue method and device based on a memory scheduling framework, equipment and a medium, which are applied to a bank virtual customer service scene or an intelligent triage and pre-inquiry scene. Obtaining a target dialogue page from all dialogue pages of the current dialogue chain in the short-term memory queue; a target topic segment and a target dialogue page are retrieved from the medium-term memory module, and target feature information is retrieved from the long-term personalized memory module; constructing a structured cue word, and generating a target response based on the structured cue word; storing the newly constructed dialogue page in a short-term memory queue; if the short-term memory queue is full, removing the dialogue page from the head of the queue; updating the topic segment in the medium-term memory module based on the removed dialogue page; and updating the long-term personalized memory module according to the popularity of the topic segment in the updated middle-term memory module. The dialogue response accuracy is improved.

The invention discloses a model reasoning method and device based on a visual language model, and relates to the technical field of artificial intelligence. The method comprises the following steps: encoding a to-be-reasoned text and a to-be-reasoned image to generate an initial reasoning tree; based on the feasibility parameters of the reasoning action in the to-be-reasoned image and the state parameters of the current node, performing expansion updating processing on the initial reasoning tree to generate a target reasoning tree; based on the rationality parameters of all the end nodes in the target reasoning tree, determining candidate reasoning paths; and determining a target reasoning path according to the consistency parameter of the intermediate node and the rationality parameter of the end node in the candidate reasoning path, and finally outputting target response data through the target reasoning path. The reasoning efficiency and accuracy of the visual language model in a complex reasoning task can be improved.

The invention provides a service response method and system and a USB key device. The service response method comprises the following steps: in response to a service processing instruction, obtaining to-be-processed service information corresponding to the service processing instruction; performing information identification on the to-be-processed business information to obtain at least one business keyword; inputting the at least one business keyword into a pre-trained matching model to obtain a target business type of the to-be-processed business information; based on the target service type, determining a target response rule from at least one pre-stored service response rule, and calling the target response rule to perform service response on the to-be-processed service information; the service response rule is obtained from at least one service subsystem in advance. The method can reduce service function coupling, facilitates centralized response of services, and improves service processing speed.

The invention provides a scientific research question answering and reasoning all-in-one machine based on multi-agent cooperation and a control method, and relates to the technical field of artificial intelligence and multi-agent reasoning, and the all-in-one machine comprises a first agent which is used for carrying out the semantic understanding of a scientific research problem inputted by a user, and obtaining a semantic understanding result; performing semantic extension on the semantic understanding result according to a configured extension rule to obtain a first query request corresponding to the scientific research problem; the second intelligent agent is used for screening response information associated with the query request sent by the first intelligent agent from a pre-constructed scientific research knowledge base and sending the corresponding response information to the first intelligent agent; and the third agent is used for evaluating whether the target response information, the corresponding semantic understanding result, the first query request and the second query request meet the configured evaluation rule or not to obtain an evaluation result. The scientific research problem of the user can be accurately, comprehensively and reliably responded.

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 embodiment of the invention provides a communication method and device in a virtualized storage system, equipment and a medium. The method comprises the following steps: receiving an original request message for accessing a storage node sent by a virtual machine; acquiring a bottom network protocol stack type of the computing node; changing the internet protocol address type of the original request message according to the bottom layer network protocol stack type to obtain a target request message; sending the target request message to a storage node, and receiving an original response message returned by the storage node in response to the target request message; and changing the internet protocol address type of the original response message to obtain a target response message, and sending the target response message to the virtual machine. Through the embodiment of the invention, communication and interconnection between different protocols are realized, meanwhile, the problem that software of a client or a server needs to be modified is avoided, and the efficiency and the reliability of data transmission are improved.

The invention discloses a reaction yield prediction method and device based on a graph attention network, and the method comprises the steps: extracting set information data from an original data set, carrying out the cleaning of the set information data, and obtaining the cleaned information data; generating a training data set by using the cleaned information data; constructing a reaction yield prediction model based on the graph attention network and the quantum chemistry descriptors; training the reaction yield prediction model through the training data set to obtain a trained reaction yield prediction model; and inputting a target reaction into the trained reaction yield prediction model for prediction processing to obtain the reaction yield of the target reaction. According to the method, the influence of different reaction conditions on the reaction yield can be fully captured, and the yield prediction performance is improved.

The invention relates to the technical field of artificial intelligence, and discloses a dialogue response method and device based on artificial intelligence, equipment and a medium, and the method comprises the steps: obtaining the current input voice of a target user; a target response text and a target rhythm style vector of the current input voice are generated through the target multi-mode audio language model and a preset target context database, and the target context database comprises at least one piece of context data of a target user; the context data comprises dialogue information and rhythm style vectors corresponding to the dialogue information; inputting the target response text and the target rhythm style vector into a target style text-to-speech model for speech synthesis processing, generating a target response speech, and extracting a current speech rhythm style vector of the current input speech through the target style text-to-speech model, and updating the target context database according to the current voice rhythm style vector and the current input voice. The rhythm of the answer voice is more natural, and the response speed is improved.

The invention provides an optimization method of a radio frequency component, which comprises the following steps of: performing parallel calculation on target response by utilizing a plurality of lower confidence bound functions to obtain a plurality of candidate parameters; performing electromagnetic simulation on the plurality of candidate parameters to obtain simulation response data corresponding to the candidate parameters; on the basis of the simulation response data corresponding to the candidate parameters, the optimization result of the radio frequency component is determined from the candidate parameters, and the optimization method can improve the optimization efficiency of the radio frequency component, effectively utilize computing resources and reduce waste of the computing resources. The invention also provides electronic equipment, a program product and a base station antenna.

The embodiment of the invention provides an interaction method and device with a digital assistant, equipment, a storage medium and a program product. The method comprises the following steps: receiving first input information input by a first user through a first interactive interface of a first digital assistant; based on the first input information, a target digital assistant for the first input information is determined from a plurality of second digital assistants, and different digital assistants in the plurality of second digital assistants are used for executing different types of tasks; and presenting target response information for the first input information in the first interactive interface, wherein the target response information is obtained at least partially based on processing of the first input information by the target digital assistant. In this way, the target digital assistant for processing the input information can be automatically determined based on the input information of the user. In this way, the cost for the user to understand the digital assistant function and manually select the digital assistant needing to be used is remarkably reduced, and the user experience and convenience are improved.

The invention relates to the technical field of community emergency management, and discloses a community multi-mode emergency event grading response system. The multi-modal data acquisition module acquires and divides community multi-modal sensing data, the event feature extraction module respectively analyzes and generates event feature sets, the grading evaluation module fuses features to match emergency event grades, the response decision module calls a target response scheme according to the grades, and the central processing unit verifies related parameters to generate a final response instruction. The system is further provided with a resource scheduling module for optimizing emergency resource allocation, an instruction feedback module for triggering equipment response action, and a data archiving module for storing data to form an event record chain. According to the system, multi-modal data deep processing, accurate grading evaluation and intelligent response decision making are realized, the community emergency management efficiency and the intelligent level are improved, and the community safety is guaranteed.

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.