117 results about "Time response" patented technology

The invention relates to the technical field of distributed response, in particular to a distributed message dynamic response method based on websocket. The method comprises the following steps: constructing a distributed message service cluster to configure a websocket communication module, message middleware and a client for each service node, and providing a unified service access point to the outside through an Nginx load balancer, so as to automatically register and subscribe a global control theme to the message middleware and form a hierarchical theme subscription structure; when the client initiates a connection request, the connection is distributed and a secure channel is established; the client sends a service request message, packages the service request message into a standardized message format, and associates session information of the client at the same time; and receiving the session message, performing intelligent filtering, generating a response result, and pushing the response result to the client in real time. According to the invention, efficient processing and real-time response of messages in a distributed environment can be realized.

The invention relates to the field of geographic information systems, and discloses an agent-based automatic address governance method and device and a medium, and the method comprises the steps: obtaining a to-be-governed address through a data perception and preprocessing agent; inputting the address to be governed into a master control agent; the main control agent analyzes the address to be governed and gives an analysis result; according to the analysis result, selecting a tool execution agent to process the address to be treated; and outputting the governed address, and storing all data by adopting a memory and interaction agent. According to the method, the analysis accuracy, the semantic understanding depth and the robustness of the LLM in processing complex and non-standard addresses containing confusion information are greatly improved, meanwhile, the requirement for manual intervention is greatly reduced, the efficiency of processing mass address data is remarkably improved, and the real-time response speed is remarkably increased.

The invention provides a storage resource dynamic allocation method and system based on artificial intelligence, and relates to the technical field of storage resource dynamic allocation, and the method comprises the steps: obtaining the real-time response delay, data transmission bandwidth and node computing power data of each storage node in the current stage of a target task, and carrying out the cooperative processing of the data, thereby achieving the dynamic allocation of storage resources. Obtaining a storage resource real-time performance data packet containing the real-time load state of each storage node; analyzing the data packet based on an artificial intelligence model corresponding to the task stage to obtain a storage resource allocation target value; through a dynamic allocation optimization algorithm, a resource scheduling strategy is formulated according to a target value, a real-time control signal is generated, and dynamic allocation and scheduling of storage resources among storage nodes are executed accordingly, so that the dynamic allocation and scheduling of the storage resources among the storage nodes can be realized based on an artificial intelligence-based storage resource dynamic allocation method, and the dynamic allocation and scheduling of the storage resources can be realized through data co-processing, AI analysis adaptive to a task stage and the dynamic optimization algorithm. Accurate and dynamic allocation and scheduling of storage resources meeting target task requirements are realized.

The invention discloses an adjustable resource unified data external characteristic modeling, regulation and control method and system oriented to various transaction scenes. The method comprises the following steps: collecting real-time data of an internal adjustable resource of a virtual power plant; the climbing time, the duration, the response capacity and the responsible frequency are quantized and defined as a group of external characteristic parameters, an adjustable resource data external characteristic model is constructed, adjustable resources are classified according to the external characteristic parameters of the model, and an adjustable resource characteristic library is established; in combination with the response characteristic and the load state of each adjustable resource, generating an optimal regulation and control strategy meeting the regulation and control requirements, and allocating a corresponding regulation and control instruction to each adjustable resource; each adjustable resource adjusts power output according to the regulation and control instruction, and meanwhile, the calling cost of each adjustable resource is calculated; in combination with the real-time state and the adjustment cost minimization target, the regulation sequence and proportion are optimized; according to the method, the economy and flexibility of the virtual power plant in multi-scene regulation can be effectively improved, and meanwhile, the accuracy of power grid frequency modulation response and the system stability are enhanced.

The invention belongs to the technical field of information security, and particularly relates to a super-threshold data set intersection method and system for security information processing. The method comprises the following steps: S1, carrying out casual key value pair storage OKVS encoding and decoding between each participant and other participants; s2, each participant constructs a hash table according to a decoding result and elements of the participant; and S3, sending the constructed hash table to a specified party, summarizing information in the hash tables of all participants by the specified party, and finally obtaining a super-threshold intersection result by using a secret sharing scheme. The method has the characteristics that the hardware and operation and maintenance cost can be reduced, the data security is enhanced, and the calculation efficiency is improved, so that the industrial control requirement of short-time response is met.

The invention discloses a multi-modal KV cache retrieval method and system based on a hybrid architecture, relates to the technical field of data processing, and aims to solve the technical problem that in the prior art, due to the adoption of a full-online computing architecture and lack of a unified cross-modal representation framework, the computing efficiency and the modal fusion effect are difficult to consider at the same time. By constructing a hybrid processing architecture of offline pre-calculation and online processing, multi-modal data is subjected to unified fragmentation coding and KV cache and semantic fingerprints of the multi-modal data are pre-calculated in an offline stage, and cache fragments are intelligently assembled and position codes are dynamically remapped based on a user query intention in an online stage; therefore, online repeated calculation of multi-modal content is fundamentally avoided, coherent alignment and efficient fusion of cross-modal semantics are achieved, the real-time response capability, the cache reuse rate and the multi-modal generation quality of the system are remarkably improved, and high-concurrency scenes can be dynamically adapted.

The embodiment of the invention relates to the technical field of information, and discloses an interface verification and test method and device based on a large model, a medium and a product, and the method comprises the steps: obtaining a to-be-tested interface document, analyzing the interface document through a first large model, constructing a test request parameter based on a request parameter definition, acquiring a real-time response message by calling a real interface; performing semantic comparison on a response example in the document structure information and the real-time response message by using the second large model to obtain a corrected interface document; comparing the parameter constraint condition in the corrected interface document with the verification logic in the business logic code snippet by using a third model to generate a logic verification passing result; and on the basis of the corrected interface document and a logic verification passing result, a Mock rule and an automatic test case script are generated by utilizing the fourth model, so that the maintenance cost and the false alarm rate of the automatic test script are reduced, and the automatic test efficiency is improved.

The invention provides an AI dialogue device and method for financial analysis, and belongs to the technical field of artificial intelligence. The device comprises an intention recognition module used for recognizing a financial intention queried by a user; the task scheduling module is used for activating the processing unit according to the intention; the tool calling module is used for calling an external tool to obtain information; the concurrent execution module is used for executing calling of a plurality of external tools in parallel; the result fusion module is used for integrating multi-source information; the reply generation module is used for generating a final reply; and the streaming output module is used for gradually transmitting the final reply to the client in the form of data stream. According to the method, the total data acquisition time is shortened by concurrently executing multiple tool calls, and part of content is displayed to the user in advance through streaming output before the final reply is completely generated, so that the waiting time perceived by the user is remarkably shortened, and the real-time response experience of the system is optimized while the professional property of financial analysis is ensured.

The invention discloses a safety protection method and device based on cross-cloud cooperative verification and terminal equipment, and the method comprises the steps: collecting the safety event data of a plurality of public clouds in real time, and generating an environment threat coefficient; dynamically generating feature weight vectors of different security feature dimensions in the service data flow based on the environmental threat coefficient and the real-time response time; calculating a basic threat score based on the feature weight vector, and superposing a vulnerability compensation value calculated based on a machine learning model gradient magnitude to generate a final threat score; when the final threat score exceeds a security threshold, an antagonism test sample is generated in a sandbox environment according to a highest attack level standard, and a real-time defense strategy is generated and executed based on the test sample. The global threat situation perception and defense can be realized by constructing a ''cross-cloud dynamic scoring-sandbox game verification-model real-time feedback'' framework, and the technical problem that the information security protection system in the prior art cannot realize the perception and defense of the global threat situation is solved.

The invention discloses a high-concurrency time series data processing method and device for an anti-unmanned aerial vehicle system. According to the method, a lock-free hash table is adopted in a cache space to cache time sequence data, lock overhead is reduced through lock-free cache design and CAS atomic operation, the batch writing throughput is high, the conflict probability is low, multi-thread high-concurrency reading and writing are supported, thread competition and blocking caused by a traditional cache mechanism are thoroughly eliminated, and the concurrent processing capacity is improved; meanwhile, the expenditure of dynamic memory allocation is reduced through batch writing, and the memory utilization rate is increased; through quick positioning of a compound key, priority query of a hotspot data index structure and a lock-free reading mechanism, the query delay of hotspot data is extremely low, the delay of related query in the future is further reduced through a data preloading mechanism, and the real-time response capability is improved; based on a dynamic elimination mechanism of an elimination score, hotspot / recent data can be reserved preferentially, the resource utilization rate is ensured, the cache hit rate is remarkably improved, and the access frequency of the TSDB is greatly reduced.

The application discloses a dynamic real-time transaction scheduling method and system, which breaks the limitation of pre-defined transactions and periodic scheduling, and enables real-time transactions to be dynamically scheduled according to actual requirements without pre-defined transactions through twice priority sorting, ensures that the transactions are completed before the deadline, and significantly improves the flexibility and real-time performance of the system; on the basis of the double loop structure of the database working thread, a multi-version concurrent access strategy and a shadow node strategy based on priority inheritance are introduced, so that the real-time database system can operate more efficiently under complex transaction load, and the real-time response capability is further enhanced; priority allocation and blocking management of the transaction are performed by using the characteristics of the real-time operating system, so that the real-time performance of the real-time operating system is not damaged in the transaction scheduling process, and the efficient response capability of the system is maintained; and the application also provides a system for implementing the method.

The invention relates to the technical field of power system dispatching, and discloses a power load dispatching optimization method considering dynamic response reliability, which comprises the following steps: collecting and classifying user historical and real-time load data; based on the response proportion, the peak clipping contribution degree and the forgetting factor, establishing a reliability coefficient model for interruptible, transferable and reducible loads; in combination with real-time response performance, a user dynamic response reliability calculation model is constructed, and quantitative indexes are obtained; establishing a scheduling optimization model which takes optimal response reliability and lowest scheduling cost as multiple targets and considers capacity and capability constraints; and finally, solving by adopting a hybrid intelligent algorithm to obtain an optimal scheduling scheme. According to the method, the uncertainty of user response is dynamically quantified, and the reliability index is introduced into a decision, so that economy can be considered on the premise of ensuring scheduling reliability, priority calling of high-reliability resources is realized, and the flexibility and stability of power grid operation are improved.

The invention provides a multi-agent collaborative decision-making and disambiguation method and system. The method comprises the following steps of: registering a dependency relationship between a task context and a concerned event triggering condition to the collaboration center, updating a dynamic dependency view through the collaboration center, analyzing knowledge updating time through the collaboration center, and generating a task context identifier set of the intelligent agent; constructing a fact set based on the task context identifier set, and inputting the fact set into a rule inference engine to execute rules in a collaboration rule base to generate a strategy so as to obtain a collaboration strategy; according to the method, the problem of efficiency bottleneck of event routing in the distributed intelligent system is solved from the system architecture level, and the real-time response capability and expansibility of the system in a high-concurrency scene are greatly improved on the premise of ensuring decision consistency.

The application relates to the technical field of big data statistics, and specifically discloses a short video recommendation method based on big data statistics, which comprises the following steps: S1: obtaining the total number of short videos watched by a user in a sampling period, and dividing the same short videos according to short video labels; S2: obtaining the number of times of logging in a platform and the single online duration in the sampling period, and calculating the mean value and the dependence coefficient of the single online duration; S3: dividing the sampling period into a front interval and a rear interval, and sequentially calculating the trend coefficients of the same short videos in the front interval and the rear interval; S4: correcting the trend coefficients to obtain corrected coefficients; and S5: calculating the trend difference values of the same short videos, and analyzing the watching trend of the same short videos by the user based on the trend difference values. The application can analyze the preferences of the user and predict future trends, establish a flexible and real-time response mechanism for the change of the preferences of the user, realize the long-term development of the platform, and maintain the market competitiveness.

The invention discloses a communication sensing time slot allocation method and system based on a potential game. According to the invention, frequency spectrum hardware sharing of radar sensing and wireless communication is realized through system initialization, a time allocation mode is dynamically selected based on a 5G NR frame structure, and the time allocation mode comprises a segmentation mode and an aggregation mode, so that time slot resources are flexibly divided; constructing a non-cooperative potential game model, taking a vehicle as a participant, defining a utility function which takes mutual information maximization of a radar system as a target and is fused into communication capacity constraint, and ensuring collaborative optimization of perception and communication performance; and in combination with greedy initialization and a random search strategy, distributed algorithm iteration is executed, so that the calculation complexity is remarkably reduced, and the real-time response capability is improved.

The invention particularly relates to an unmanned aerial vehicle cluster downloading data load balancing algorithm based on micro-service, which comprises the following steps of: replacing periodic synchronization by combining multi-round sampling and instant calculation, and ensuring that average response time can reflect the real-time state of the micro-service; and the optimal micro-service node is dynamically screened by monitoring the micro-service response state in real time, so that the efficient distribution of the data downloaded by the unmanned aerial vehicle in the micro-service cluster is realized. On the basis, a real-time response time decision and hot registration dynamic management are deeply combined, so that not only is the optimality of data distribution ensured through response time, but also the capacity expansion cost is reduced through hot registration. According to the invention, the technical problems of inaccurate response time perception, dependence on manual intervention on capacity expansion and shrinkage, long-term resource occupation of fault nodes and encumberment of overall data flow in a mass unmanned aerial vehicle data downloading scene in the existing load balancing scheme are solved; the method is suitable for scenes requiring massive unmanned aerial vehicle collaborative operation, such as regional emergency monitoring, large-scale training and urban air traffic management.

The invention discloses a dialogue generation method and device, a customer service system, a storage medium and a program product, and the method comprises the steps: receiving request data inputted by a user, and carrying out the data preprocessing of the request data; performing intention analysis and emotion detection on the preprocessed request data to obtain user intention information and a user emotion state; performing data search on the user intention information to obtain problem analysis data; generating an initial reply text according to the user intention information and the question analysis data; and adjusting the initial reply text based on the emotional state to obtain a dialogue text. By adopting the embodiment of the invention, the intention and the perception emotional state of the user can be accurately analyzed, and multi-modal interaction is realized by fusing multi-element information, so that real-time response and efficient solution of questions of the user are realized.

This allows operators to respond to users with minimal waiting time. [Solution] The information processing system (10) comprises a central control unit (12), an operator terminal (16), a user terminal (18), and an automated response device (20). Prior to the operator of the operator terminal responding to the user of the user terminal, the automated response device automatically responds to the user for a predetermined period of time. The automated response device sequentially asks the user questions about several items that need to be confirmed and obtains answers from the user. When it obtains answers from the user, it decides whether to include an icebreaker in the next question based on the remaining time and the number of items that need to be confirmed. If there is sufficient time remaining, the next question, which includes an icebreaker, is sent to the user terminal.

The application discloses a kind of high concurrency time series data processing method and device for anti-UAV system.The application uses lock-free hash table to cache time series data in cache space, lock-free cache design and CAS atomic operation reduce lock overhead, batch write throughput is high, conflict probability is low, support multi-thread high concurrency read-write, completely eliminate thread competition and blocking caused by traditional cache mechanism, improve concurrent processing capability;At the same time, batch write reduces the overhead of dynamic memory allocation, improves memory utilization;Through composite key fast positioning, hot data index structure priority query and lock-free reading mechanism, the query delay of hot data is extremely low, data preloading mechanism further reduces the delay of future related query, improves real-time response capability;Based on the dynamic elimination mechanism of elimination score, hot data / recent data can be preferentially retained, ensure resource utilization, significantly improve cache hit rate, greatly reduce access frequency to TSDB.

The invention provides an electronic contract multi-identity authentication method and device of a mobile terminal, equipment and a medium, and the method comprises the steps: determining whether to transmit an identity verification code to user equipment according to the response identity data and response behavior data of the user equipment to first identity authentication information; determining whether the user equipment passes the first identity authentication according to the input behavior data when the user equipment inputs the identity verification code; determining whether the user equipment passes the second identity authentication or not according to a real-time response behavior made by the user equipment for the second identity authentication information and the waiting response duration; determining whether the user equipment passes the third identity authentication according to a video frame sequence of the user equipment corresponding to the third identity authentication information and a shooting waiting time length; and if the user equipment passes the third identity authentication, determining that the multiple identity authentication of the user equipment is successful, and displaying an electronic contract to the user equipment. Therefore, the problems of false use and signing-for-another of the electronic contract are effectively avoided.

The invention discloses a buoy type platform based on an intelligent material and a structure self-recovery method thereof, the platform adopts an isosceles triangle-shaped buoy type structure, and the method comprises the following steps: S1, collecting platform structure real-time response data; s2, constructing a response driving type attitude offset function; s3, acquiring an excitation temperature rise condition required by the shape memory alloy execution unit to execute recovery change; s4, calculating offset recovery stress of the platform structure; and S5, recovering the platform structure, and detecting the recovered platform structure in real time. According to the method, the shape memory alloy execution unit and the functionally graded material are arranged, the response quantity corresponding to the float-type platform is used as input data, the closed-loop control method from float-type platform structure deviation risk identification to self-recovery is constructed, deviation data can be obtained in real time, deviation structure self-recovery is carried out, regular manual inspection is not needed, and the operation efficiency is improved. And the offset trend of the platform structure can be monitored in real time, and the problem of lack of an automatic monitoring and dynamic adjustment mechanism is effectively solved.

The invention discloses a 360-degree video edge caching joint bit rate allocation method based on double time scales, and belongs to the technical field of 360-degree video streaming and edge caching. The method comprises the following steps that: in a long-time scale period, an edge server collects and analyzes historical request data of a user, calculates a comprehensive value priority for candidate video slices according to long, medium and short-term popularity of the slices, and further generates an optimal caching strategy which takes effect in a next period. In a short time scale period, according to the caching strategy, the edge server processes the real-time requests of the user and distributes bit rates to all concurrent requests fairly and efficiently. Through a self-adaptive optimization mechanism combining long-term planning and real-time response, the high cache hit rate of high-value slices can be ensured in different storage spaces, the data request quantity to the cloud is reduced, the pressure of a return link is relieved, and the comprehensive experience quality of a user is remarkably improved.

The invention discloses a computer system fault detection method and system based on artificial intelligence, and relates to the technical field of fault detection.When the system operates, a first data set, a second data set and a third data set are obtained by collecting traffic system and urban infrastructure data, and key features are extracted from the collected data; the data processing module is used for storing the data, reserving information beneficial to fault detection, transmitting the information to the data processing module, training a machine learning model by using historical data, calculating a computer equipment operation state index Jtss and comprehensively evaluating the operation state of the traffic facility, continuously monitoring the real-time state, inputting the data to the machine learning model, detecting potential faults and responding to the system state change in real time. Once an abnormality is detected, an alarm is generated and a notification is sent to related city management personnel, so that actions are taken in time to solve problems, the time from fault discovery to response is shortened, the negative influence of the fault on urban traffic and infrastructure is adjusted, and system operation feedback information is collected regularly.

The invention provides a retrieval processing method, device and equipment based on multi-source knowledge base data. The method comprises the following steps: acquiring multi-source heterogeneous data; standardizing the data format and the target term of the multi-source heterogeneous data to obtain standard data; performing repeated entity identification on the standard data, and removing repeated entities in the standard data to obtain target data; obtaining an entity relationship in the multi-source heterogeneous data according to the multi-source heterogeneous data, and constructing a knowledge graph; and obtaining a user target question, and querying in the target data and the knowledge graph to obtain a target output result. According to the scheme, the multi-source data can be managed in a unified manner, the cross-database retrieval accuracy of the data is improved through the knowledge graph, and the real-time response capability of the data is improved.

The invention discloses a business processing time prediction method and device, a storage medium and electronic equipment, and relates to the technical field of information, the method comprises the steps of firstly obtaining dynamic feature data and static feature data, the dynamic feature data comprising processing equipment information and processing object information of a to-be-processed task; constructing a time prediction model according to the integrated learning model and the time sequence analysis model, and inputting the dynamic and static feature data into the time prediction model to obtain prediction processing time; and determining the target prediction time of the to-be-processed task according to the M prediction processing times. According to the method, dynamic and static feature data are comprehensively covered through dynamic and static multi-source data fusion, and the time prediction model can analyze the dynamic feature data based on the time sequence and can perform model optimization in real time according to the integrated learning model, so that the service processing time is predicted more accurately, and the service processing efficiency is improved. The prediction precision of the service processing time is improved, and the real-time response capability is enhanced.

This specification provides one or more embodiments of a data query method, apparatus, electronic device, and storage medium. The method includes: during a data query of queried data based on the compilation result of a data query language, in response to the end of a data query for the current data unit, obtaining a first query time for the current data unit, and swapping the order of a first predicate and a second predicate in the compilation result of the data query language, wherein the queried data includes multiple data units; in response to the end of a data query for the next data unit, obtaining a second query time for the next data unit; in response to the first query time being greater than or equal to the second query time, retaining the order of the first predicate and the second predicate in the compilation result; and in response to the first query time being less than the second query time, restoring the order of the first predicate and the second predicate in the compilation result of the data query language.

The invention discloses a secure transmission method and device, equipment, a medium and a product, and the method comprises the steps: obtaining an access request of a client and a current randomized tag pre-distributed to a web application in a server, and triggering the updating of the current randomized tag through a network attack association feature; scheduling a pre-trained target detection model based on the access request, and determining a security detection result of the access request; if the security detection result is secure, sending the access request to a server, and receiving a response result fed back by the server; and performing behavior analysis on the response result according to the current randomized tag, determining security feedback content and feeding back the security feedback content to the client. By dynamically updating the current randomized tag, the randomness of the defense form is enhanced, the method does not depend on the attack mode of an attacker, novel attacks or attack variants can be dealt with in real time, double attack detection of security detection and behavior analysis is carried out on the access request, and the detection capability and defense capability of the attacks are improved.

The application provides a multi-agent collaborative decision-making and disambiguation method and system. The method comprises the following steps: registering the dependency relationship between the task context and the event trigger condition concerned by the agent to the coordination center, updating the dynamic dependency view through the coordination center, analyzing the knowledge update time through the coordination center, and generating a task context identifier set of the agent; constructing a fact set based on the task context identifier set, inputting the fact set into a rule reasoning engine, executing the rules in the collaborative rule base to generate a strategy, and obtaining a collaborative strategy; and distributing the collaborative strategy to the corresponding agent and executing a cleaning process at the end of the task generation period. The application solves the efficiency bottleneck of event routing in a distributed intelligent system from the system architecture level, greatly improves the real-time response capability and scalability of the system in a high-concurrency scenario while ensuring decision consistency.

The application discloses a data processing method applied to an intermittently working terminal, and comprises the following steps: executing a first program segment; calculating a first check code corresponding to a first address interval, wherein the first address interval is an address interval used when the first program segment is executed; acquiring a second check code corresponding to a second address interval, wherein the second address interval is an address interval except the first address interval in a third address interval, and the third address interval is an address interval used when a program to which the first program segment belongs is executed; determining a third check code according to the first check code and the second check code, and storing the third check code in a non-volatile memory, so as to check data in a volatile memory after power supply is restored. According to the scheme, the calculation of the check code does not need to be performed on the whole address interval of the saved data, the energy consumption and time for calculating the check code can be reduced, the terminal can continuously operate, and the real-time response performance of the terminal is ensured.

The invention discloses an electric power task allocation and optimization method and system, and belongs to the technical field of electric power Internet of Things, and the method comprises the steps: obtaining a calculation task generated by a business terminal; extracting a feature vector T of the calculation task through an edge access point or an edge node controller; periodically broadcasting the resource state vector S of each edge node, and quickly matching the feature vector T of the task with the resource state vector S of the peripheral available edge node based on the resource state of the edge node of fuzzy logic; modeling a feature vector T of the task and a resource state vector S of a peripheral available edge node into a dynamic system, and performing dynamic cooperative task allocation based on an improved gravitational search algorithm; and unloading the task to the target edge node for execution according to the distribution result. The method has the advantages that network and load changes are responded in real time, the multi-dimensional quality requirement of power business is accurately met, and the task allocation and optimization effect with the optimal global efficiency of the edge cluster is achieved.