77 results about "Information gap" patented technology

The invention discloses an air-ground integrated big data fusion method for urban measurement, and relates to the technical field of data processing. The method comprises the following steps: acquiring space-land integrated big data of a city; uniformly calibrating the air-ground integrated big data to a city standard coordinate system to obtain low space-time deviation data; obtaining a first conflict entity and a second conflict entity based on the low space-time deviation data; correcting spatial positions of the first conflict entity and the second conflict entity in the low space-time deviation data to obtain a conflict-free big data model; and constructing a long-short-term memory network based on the conflict-free big data model. According to the method, the problem of low fusion precision caused by non-uniform space-time reference and large format precision difference of multi-source data is solved by integrating space-ground integrated big data such as urban space point cloud, a sensor network and a remote sensing image, and the data consistency and reliability are improved and information faults and semantic conflicts are avoided by eliminating space-time deviation and entity conflicts.

The invention relates to a whole-process management method for internet asset vulnerability governance. The method comprises the following specific steps of task configuration, scanning task creation and execution, vulnerability list generation and work order distribution, vulnerability repair and multi-stage auditing, and data statistics and archiving. The efficiency is obviously improved; the whole process is online, so that the vulnerability management period is greatly reduced; the manpower cost is reduced: repeated docking of a third-party security team is not needed, the workload of security operation personnel is reduced, and manpower loss of offline communication is avoided at the same time; work order records, approval traces and scanning logs are archived in the whole process, a complete basis is provided for safety audit, an assessment report of a person in charge can be directly used for performance assessment, and the problem that no data exists in assessment is solved; and the rectification sheet state can be synchronized to all cadres in real time, information fault is avoided, and superior leaders can monitor the treatment progress in real time through the data statistics module and intervene in lagging links in time.

Methods and systems for automatic detection and filling of information gaps in a reference database are described. Responsive to a user query in an ongoing chat session, a query embedding associated with the user query is obtained. A synthetic question embedding is identified from a vector database, based on a similarity to the query embedding. Responsive to determining that the similarity between the synthetic question embedding and the query embedding does not meet a similarity threshold, the ongoing chat session is monitored to detect an answer to the user query. A prompt is provided to a large language model (LLM) to generate and display a textual content corresponding to the user query, based on the detected answer, for automatically updating the reference database. The disclosed methods and systems effectively incorporate new or undocumented information that is not currently captured within the reference database, as gaps are identified.

The invention relates to the technical field of natural language processing, in particular to a verifiable large model retrieval enhancement generation system and method based on an evidence chain, and the method comprises the steps: receiving an initial query, recognizing the fuzziness and information gap of the initial query in combination with an associated retrieval document, and generating a supplementary query set; based on the initial query, the supplementary query and the corresponding retrieval document, generating candidate answers with references and verifying the information supportability of the candidate answers; for the candidate answers passing the verification, extracting support information and constructing a hierarchical attribution mapping relation; and integrating the information to form to-be-evaluated information, and if the current verified to-be-evaluated information meets a preset sufficiency condition, integrating the generated preliminary answer and the to-be-evaluated information to synthesize a target answer. The method effectively overcomes the defects that a traditional RAG system is fragmented in information integration, has one-sided fuzzy query and answer, is low in attribution efficiency and excessively depends on retrieval content, and has the advantages of answer comprehensiveness, verifiability and deployment lightweighting.

The invention relates to the technical field of power systems, and particularly discloses a park low-carbon planning method based on robust optimization, and the method comprises the steps: constructing a free carbon emission quota transaction model; constructing a deterministic low-carbon optimization planning model of the park integrated energy system by considering multi-energy complementation; quantizing the long-term uncertainty of the load growth rate by adopting a long-term uncertainty description method of the load growth rate based on an information gap decision theory; constructing a low-carbon robust planning model of the integrated energy system based on an information gap decision-making theory based on a free carbon emission quota transaction model and a park integrated energy system deterministic low-carbon optimization planning model constructed by considering multi-energy complementation; and solving the model to obtain a planning scheme. The method has the advantages that collaborative optimization of carbon quota distribution and multi-energy network topology is realized, carbon emission constraints of each year are constructed, and full-life-cycle carbon emission reduction is realized.

The invention belongs to the technical field of ocean forecasting and artificial intelligence crossing, and discloses a physical equation driven ocean wave spectrum intelligent forecasting method and system.The method comprises the steps that a spectrum balance equation is deconstructed and divided into a propagation item and a source item, and modeling is conducted on the propagation item and the source item; dividing the source item into different sub source items according to different physical mechanisms; source item subnets are constructed for different sub-source items, guide variables are embedded, and decoupling of a nonlinear physical process and construction of a high-fitting-degree multi-source driving expression mechanism are achieved; through multi-step ground pushing training and in combination with main peak offset constraint, energy conservation control and propagation gradient supervision, prediction strategy construction of long-term prediction stability and physical consistency is realized. For ship motion response and other engineering applications taking spectrum as input, the method avoids an information gap between single-element forecasting and spectrum-driven application, realizes seamless connection from environment forecasting to engineering calculation, and greatly improves the practicability of the application.

The invention discloses a reverse guidance type intelligent interaction method and system for realizing dynamic information assessment. The system comprises an information sufficiency assessor, an information sufficiency assessment device and a dynamic information assessment device, wherein the information sufficiency assessor is used for dynamically and quantitatively assessing and identifying key information gaps on the basis of an information entropy theory; the reverse questioning strategy generator is used for generating an optimal reverse guidance questioning sequence for supplementing a key information gap based on a Markov decision process model; the hierarchical problem decomposition engine is used for recursively decomposing a complex problem into a plurality of sub-problems by adopting a semantic tree decomposition technology, and fusing solution results of the sub-problems by utilizing an evidence theory fusion mechanism to form a problem solution; the personalized solution synthesizer is used for analyzing the cognitive level, learning style and attention characteristics of the user portrait, performing matching optimization on a problem solution and the user portrait, and calculating and measuring the semantic matching degree of the problem solution and the user portrait; and applying reinforcement learning to continuously optimize an output strategy according to user feedback to generate a personalized solution.

The invention discloses a method for identifying personnel intentions through guided communication, belongs to the technical field of man-machine interaction and artificial intelligence, and aims to solve the problems of low communication efficiency and poor user experience caused by difficulty in processing fuzzy and incomplete user input and neglecting a user interaction state in an intention identification system in the prior art. The method comprises the following steps: analyzing initial input of a user to obtain an initial intention; analyzing and generating an information gap list based on a preset intention-information element mapping library; interaction states such as emotion and uncertainty of the user are perceived and quantified in real time; the core lies in that the information gap and the user state are fused, 'what is asked '(the information gap) and'what is asked' (the user state) are dynamically combined, more intelligent and humanized guidance can be carried out, the accuracy and the communication efficiency of intentional D graph recognition in a complex or emergency scene are remarkably improved, and the man-machine interaction experience is optimized.

The invention belongs to the technical field of code generation, particularly provides a large model tool calling method and system based on demand awareness, and aims to solve the technical problems that an existing code generation system lacks an active tool calling capability and cannot automatically select a proper tool according to information loss. According to the method, an information demand identification model, a tool mapping knowledge graph and a self-adaptive scheduling strategy are constructed, so that a large language model can actively identify an information gap in the code analysis and generation process, and an external tool is automatically selected and called to obtain required context information. The core of the system comprises four modules, namely a demand awareness engine, a tool selection decision maker, a multi-modal information fusion device and an iterative optimization feedback mechanism. By introducing an information missing detection algorithm based on an attention mechanism and a hierarchical tool calling planning strategy, the system can realize intelligent processing from a single file to a warehouse-level code task, and the accuracy and availability of code generation are remarkably improved.

The invention relates to the technical field of construction of pollution site models, and particularly discloses a construction method and system of a conceptual model of a pollution site, an initial conceptual model of the pollution site is constructed by integrating multi-source heterogeneous data of the pollution site, a space-time coupling relation of pollution source-migration path-acceptor is described in a parameter matrix form, and the conceptual model of the pollution site is constructed. Then, further decomposing the field prior information model parameter matrix into independent units, taking feedback information of a benefit related party as a constraint condition, and performing panoramic semantic scanning query on the field prior information by utilizing a natural language processing technology and a semantic query algorithm; and key information gaps such as uncovered exposure paths in the site prior information are identified, so that the conceptual model of the polluted site is iteratively optimized. By means of the mode, intelligent recognition of key information gaps of the conceptual model of the polluted site can be achieved, dynamic adjustment and improvement of the conceptual model are guided, and the conceptual model better meets the actual situation and the requirements of interested parties.

The invention discloses a recursive deep text query method, system and device and a storage medium, and the method comprises the steps: firstly creating an initial query and initializing a hierarchical depth, executing a first-layer query, carrying out evolution processing, and then carrying out retrieval; if the information density is insufficient, sub-query is generated to execute second-layer query, and retrieval is performed after second evolution processing; if the second-layer retrieval is contradictory, third-layer query is executed, retrieval is performed after timeline query and information source tracing verification are passed, and a third-layer retrieval result is finally output; through multi-level query and targeted evolution processing, query can be optimized step by step, more information dimensions can be covered, information gaps can be filled up, and retrieval comprehensiveness and accuracy can be improved; and a third-layer verification mechanism can effectively check contradictions by means of timelines and source tracing, so that the accuracy and reliability of results are guaranteed, and better retrieval results are provided for users.

The application discloses an international trade intelligent customs declaration system and method, and relates to the technical field of international trade.The application comprises a data acquisition module for acquiring single certificate image data and associated form data of a batch to be declared; a multi-modal analysis and verification module for loading a trained multi-modal perception model; and the following steps: S1: acquiring single certificate image data and associated form data of a batch to be declared.The application has the advantages that single certificate information extraction and compliance logic verification are simultaneously completed in single semantic understanding, the recognition result directly carries a quantifiable and reliable verification conclusion, eliminating the information gap of the traditional separate architecture; at the same time, the maintenance work of creating fixed templates according to countries and single certificate types is eliminated, the application has self-adaptive capacity for format changes and unexpected abnormalities, and the model can be continuously optimized from the correction feedback of the customs officer, so that compliance conflicts can be effectively intercepted in the declaration preparation stage, and the single rejection rate and customs clearance time are reduced.

A method for assisting web page authors to create more comprehensive content, which in turn increases the search engine optimization ranking of the web page by utilizing available artificial intelligence engines to analyze the information gaps between the author's existing content and other related existing content located on the internet.

The application relates to the technical field of natural language processing, in particular to an evidence chain-based verifiable large model retrieval enhancement generation system and method, which comprises the following steps: receiving an initial query, identifying the ambiguity and information gap of the initial query in combination with associated retrieval documents, and generating a supplementary query set; generating a cited candidate answer based on the initial query, the supplementary query and the corresponding retrieval document, and verifying the information supportability of the cited candidate answer; extracting supportable information from the verified candidate answer and constructing a hierarchical attribution mapping relationship; integrating the above information to form to-be-evaluated information; if the to-be-evaluated information currently verified satisfies a preset sufficiency condition, integrating a generated preliminary answer and the to-be-evaluated information to synthesize a target answer. The application effectively solves the defects of the traditional RAG system, such as information integration fragmentation, one-sided query answering, inefficient attribution and excessive dependence on retrieval content, and has the advantages of comprehensive answer, verifiability and lightweight deployment.

The invention discloses an attendance abnormity real-time processing method and system, and relates to the technical field of attendance information processing, and the method comprises the steps: responding to a voice instruction input by a user, carrying out semantic analysis on the voice instruction, calling multi-source data associated with a to-be-queried target employee in real time based on the analysis content, and sending the multi-source data to the to-be-queried target employee; the multi-source data at least comprises employee identity data, time sequence attendance data, commuting feature data, scheduling data and business scene data; and extracting specified features of the multi-source data, and inputting the specified features into a pre-trained anomaly detection model to identify an attendance abnormal event of the target employee. The full-dimensional data complementation information gap is combined with the model accurate mining rule, the pain points of high misjudgment rate, more missed judgment, low efficiency and poor scene adaptation in the traditional single data and manual judgment mode are solved, and the labor intensive industry brings the values of recognition precision improvement, management efficiency optimization, business adaptation enhancement and employee experience improvement.

An apparatus for determining a hierarchical listing of information gaps for a user is provided. The apparatus includes a processor and a memory connected to the processor. The memory contains instructions configuring the processor to receive an instance of an identification datum from a user device, where the identification datum describes an output type from the user device at a time, receive a target status datum from a database connected to the processor, where the target status datum describes an optimal output type between a minimal output type and a maximum output type, and to classify the identification datum and the target status datum to categories representing identification data. The processor may identify an instance of a gap between identification data and display an input field to the user capable of displaying a hierarchical listing of information gaps based on a user-input datum.

The present application belongs to the field of comprehensive energy planning, and provides a kind of comprehensive energy system planning robust optimization configuration method and system.The method comprises, obtaining the resource condition and load demand parameter of comprehensive energy system, establish the IES optimization configuration model with the maximum internal rate of return as optimization target;Establish the uncertain set model of wind and light output and cold and heat load demand parameter, based on IGDT combined with IES optimization configuration model, construct IES robust optimization model facing investment income;Simplify IES robust optimization model, solve the maximum uncertainty fluctuation radius and the uncertain scene parameter of the corresponding worst scenario;Under the condition that the uncertain scene parameter is determined, the optimization configuration scheme of maximizing investment income is solved;According to different expected income deviation calculation forms IES optimization configuration scheme set, adopt fuzzy decision, select optimal scheme.Maximize the investment rate of return as optimization configuration target, and based on information gap decision, under the premise of reaching expected income, solve configuration scheme.

The invention belongs to the technical field of data processing, and discloses a policy service accurate pushing method and system for medium and small enterprises. Comprising the following steps of: constructing a matching rule base covering four types of conditions of regions, scales, industries and products by performing clause-level atomization disassembly and multi-dimensional knowledge expansion on enterprise industry and commerce information on policy texts, and realizing cross-dimensional consistency matching of policy conditions and enterprise characteristics; according to the method, construction of a logical dependency relationship graph is introduced, atomic judgment conditions are used as graph nodes, a core admission chain is identified through dependency strength weights and topological sorting, matching confidence is quantified based on path weights and a logical propagation algorithm, and enterprise policy applicability and information gaps are accurately identified; the method has intelligence and accuracy, deep semantic analysis and applicability evaluation can be carried out on policy terms, and personalized difference pushing is effectively achieved.

The invention discloses an automatic medical record generation method and system based on multi-modal data and active perception, and belongs to the technical field of data processing.The method specifically comprises the steps that multi-modal original data of a patient and a doctor are collected, a field evidence graph is constructed, a constraint set is generated according to a clinical ontology and a time sequence rule, and configuring a priority and a dynamic threshold for each medical record field, generating an additional collection action based on information gain, and performing iterative update on the field evidence graph, the iterative update being to control the additional collection action of a target field until the target field reaches the dynamic threshold or meets a constraint set. Performing constraint decoding on medical record fields in the iteratively updated field evidence graph to obtain each target field value, and outputting a medical record with an evidence fingerprint chain; according to the method, the multi-modal information required by the medical record can be comprehensively covered, the information gap can be dynamically found and actively supplemented in the acquisition process, and the logic consistency and the time sequence reasonability between the fields are ensured.

The dual random electrothermal coupling optimization scheduling method taking into account the uncertainty of thermal resistance and the uncertainty of wind power includes the following steps: Step 1: Considering that the pipeline damage factor in the actual electrothermal coupling scheduling will cause the thermal resistance to change, thereby affecting the system, establish the thermal resistance uncertainty constraint of the thermal network; Step 2: Based on the thermal resistance uncertainty constraint of the thermal network established in Step 1, consider the uncertainty of wind power and the impact of the uncertainty of thermal resistance of the thermal network in the electrothermal coupling scheduling system structure, and establish a dual random electrothermal coupling optimization scheduling model taking into account the uncertainty of wind power and thermal resistance; Step 3: Based on the optimization scheduling model established in Step 2, propose an information gap robust optimization solution strategy to obtain the optimal scheduling result. The present invention takes into account the changes in the heat loss characteristics of the thermal network caused by the uncertainty of thermal resistance and its impact on the reliability of the electrothermal coupling scheduling decision, which is more in line with actual working conditions. In addition, the information gap robust optimization solution strategy is used to ensure the economy and stability of the system optimization scheduling.

An apparatus for determining a hierarchical listing of information gaps for a user is provided. The apparatus includes a processor and a memory connected to the processor. The memory contains instructions configuring the processor to receive an instance of an identification datum from a user device, where the identification datum describes an output type from the user device at a time, receive a target status datum from a database connected to the processor, where the target status datum describes an optimal output type between a minimal output type and a maximum output type, and to classify the identification datum and the target status datum to categories representing identification data. The processor may identify an instance of a gap between identification data and display an input field to the user capable of displaying a hierarchical listing of information gaps based on a user-input datum.

The application belongs to the technical field of data processing, and relates to a robot whole-machine joint calibration method, a robot and a storage medium. By constructing whole-machine calibration state expression information, the robot camera, the chassis and the environment information are uniformly represented as the basic input of the joint calibration process, realizing centralized management of multi-source information and avoiding information fragmentation in module calibration. In the calibration process, the target calibration data is evaluated to determine the calibration information gap, and when the constraint is insufficient, a whole-machine motion strategy is generated and new joint calibration data is collected. Then, the joint calibration data is uniformly optimized, the correlation of multi-source data is comprehensively considered, and the independent calibration error accumulation problem is reduced. At the same time, a verification mechanism is introduced to evaluate the calibration result and judge whether the termination condition is met. If not, the calibration process is re-entered to form a closed-loop control. Therefore, the integrity, controllability and result reliability of the calibration process are improved.

The invention discloses a node processing method of a server cluster and electronic equipment, and relates to the technical field of automatic operation and maintenance, a first node is used as a fault source, a fault type is firstly judged, information containing a node identifier and a fault reason is transmitted based on the fault type, and the delay of passive waiting detection is avoided; the third node relies on the hardware-level communication advantage of the back plate of the case, the fault signal is quickly transferred when the first node cannot directly communicate, and fault information fault caused by the fact that the first node cannot actively send the fault signal is avoided; and the second node receives and processes the fault message from the first node or the third node, accurately locates the fault node and executes disconnection operation, so that slow response depending on heartbeat timeout is avoided. Time consumption is reduced in the whole process from active fault reporting to rapid disconnection execution, the processing efficiency of the fault nodes in the server cluster is remarkably improved, and fault response time delay is effectively reduced.

An apparatus for determining a hierarchical listing of information gaps for a user is provided. The apparatus includes a processor and a memory connected to the processor. The memory contains instructions configuring the processor to receive an instance of an identification datum from a user device, where the identification datum describes an output type from the user device at a time, receive a target status datum from a database connected to the processor, where the target status datum describes an optimal output type between a minimal output type and a maximum output type, and to classify the identification datum and the target status datum to categories representing identification data. The processor may identify an instance of a gap between identification data and display an input field to the user capable of displaying a hierarchical listing of information gaps based on a user-input datum.

The invention relates to the technical field of power grid side large-scale wind and light and energy storage configuration, in particular to a wind and light storage capacity distribution robust configuration method and system based on information gap decision, and the method comprises the steps: taking the lowest comprehensive cost as an objective function, and building a power grid side wind and light energy storage optimal configuration model considering inertia constraint; processing the data by using a multivariate time sequence density peak value clustering algorithm based on a principal component analysis method; uncertain factors in the optimal configuration model are considered, and a probability distribution fuzzy set based on a mixed norm is constructed; establishing a two-stage distribution robust optimization configuration model based on data driving, considering the uncertainty of wind and light output prediction, and converting the distribution robust optimization configuration model based on an information gap decision theory; and converting the distributed robust optimal configuration model into a mixed integer linear programming model by using a linearization technology, and solving the mixed integer linear programming model by using a column and number generation algorithm to obtain an optimal configuration and operation scheme of each device.

This application discloses a data processing method relating to the field of artificial intelligence, comprising: obtaining a first query corresponding to a first neural network and a second query corresponding to a second neural network; the first query is a query obtained by maximizing the information entropy of the query corresponding to the first neural network; the first neural network is a model obtained by compressing the second neural network; the first neural network and the second neural network are used for object detection; determining a first loss based on the first query and the second query; the first loss indicates minimizing the information difference between the second query and the first query; and updating the first neural network and the first query based on the first loss. This application improves the model accuracy of the compressed model by minimizing the information gap between the query queries of the student model and the teacher model, thereby minimizing the information gap between the student model and the teacher model.

The present invention discloses a bidirectional cross-modal image-guided point cloud restoration method with multi-scale progressive refinement, which relates to the field of computer vision technology for artificial intelligence drones or embodied robots, including: converting an incomplete point cloud into a depth map; based on a bidirectional interactive compensation module, compensating for the missing geometric depth information in the view image modality according to the depth map, and compensating for the missing texture and color information in the point cloud modality using the view image modality, to obtain a final enhanced feature representation; decoding the final enhanced feature representation based on a coarse point cloud generation module to generate a coarse point cloud; using a point cloud refinement module to refine the coarse point cloud, and guiding the fusion of global shape and local structure information through dual-stream features to gradually generate a predicted refined point cloud. The present invention bridges the information gap between point cloud and image modalities, enhances the accuracy of generating the overall shape and local details of the point cloud, and can reasonably generate a complete point cloud with a fine-grained semantic structure.

The invention provides a multi-sensor vehicle target detection and identification method for smart parking, and belongs to the technical field of smart traffic. According to the method, accurate detection of vehicle targets in a parking lot and parking space occupation state identification are realized through fusion of various sensor data and the like. The method comprises the following steps: firstly, performing multi-modal fusion feature tensor mapping alignment on data of each sensor to a unified coordinate system; then, according to the environment and sensor signal quality, dynamically and adaptively adjusting the weight, fusing multi-source information to obtain a vehicle detection result, and introducing a virtual sensor compensation mechanism to fill up information vacancy when sensor data is missing; and finally, carrying out space-time consistency optimization on a detection result to ensure continuous and stable vehicle state output. Compared with a traditional single sensor scheme, the method improves the accuracy and robustness of vehicle detection, can adapt to complex conditions such as illumination changes and sensor faults, and remarkably reduces false detection and missing detection. The method can be used for vehicle monitoring, parking space guiding and other systems of a smart parking lot, and the parking management efficiency and the user experience are improved.

This application discloses a code generation method, apparatus, device, medium, and product, relating to the field of application development. The method includes converting front-end application design data into a structured dataset containing page element information, initial interaction topology, and visual design specifications, addressing the problem of insufficient interaction logic description capabilities. It then converts this data into an attributed state transition diagram, describing the complete interaction attributes of the front-end application's page-to-page interaction from pre-interaction preparation to the completion of the interaction's effect, replacing vague natural language descriptions and achieving machine-analyzable interaction logic, bridging the information gap between design and implementation. Finally, it combines a pre-trained language model to directly generate front-end development code, achieving automated and standardized output from design to code, addressing the lack of machine-analyzable formal representation of front-end interaction logic, thereby improving front-end development efficiency and code quality, and reducing communication and maintenance costs.

To provide a technique to reduce information gap between visual information and haptics information.SOLUTION: An image processing apparatus comprises: acquisition means that acquires information obtained on the basis of photographing information when image data of an object to be processed is acquired through photographing, the information on a focusing level indicating the degree of focusing on an object to be photographed included in the image data of the object to be processed; haptics changing means that makes a first change to haptics data acquired in association with the image data of the object to be processed, on the basis of the information on the focusing level; and generation means that generates an image file by associating the haptics data after the first change is made with the image data of the object to be processed. The first change includes changing the value of the haptics data of at least part of the object to be photographed.SELECTED DRAWING: Figure 1A