203 results about "Bidirectional map" patented technology

The invention relates to the technical field of intelligent power grids, in particular to a power distribution network battery digital dynamic management system based on digital twinning. Comprising a data acquisition unit; the digital twinborn modeling unit is used for constructing a battery-power grid-environment multi-dimensional dynamic twinborn body and realizing virtual-real bidirectional mapping and adaptive updating by combining a multi-physics field coupling model and a long-short-term memory network time sequence prediction algorithm; a dynamic optimization unit; and executing the feedback unit. Through a distributed heterogeneous sensing network of a data acquisition unit, multi-dimensional operation data of a battery pack and a key node of a power distribution network are acquired, and a high-fidelity data set containing four-dimensional labels of a battery state, a power grid parameter, time and a position is generated in combination with a spatial-temporal feature extraction technology; the deep fusion of the full life cycle state of the battery and the global operation data of the power distribution network is realized, and the comprehensive data support covering the global is provided for the optimization decision.

The invention provides a method for generating an SQL (Structured Query Language) by a natural language based on bidirectional mapping and semantic parsing, which relates to the technical field of database query and comprises the following steps of: extracting natural language query elements and packaging the natural language query elements into structured data, and establishing a mapping relationship from a query field to a service attribute and a physical data table by adopting a bidirectional Hash index technology; and automatically identifying multi-table association keys, performing semantic extension and compliance verification, generating an abstract syntax tree, performing processing according to user permission, and finally converting the abstract syntax tree into an SQL statement conforming to a target database syntax specification. According to the method, the accuracy and the efficiency of converting the natural language into the SQL are improved, and the flexibility and the safety of the system are enhanced.

The invention discloses a multi-welding-robot collaborative operation system based on digital twinning, and belongs to the technical field of intelligent manufacturing and robot control, the system comprises a physical space module, a virtual space module, a twinning data layer and a control module, and communication connection is established among the physical space module, the virtual space module, the twinning data layer and the control module; the physical space module comprises a plurality of welding robots, a sensor group and a data transmission network; the virtual space module comprises a multi-welding robot twinning body and a workpiece twinning model; the twin data layer is used for connecting the physical space module and the virtual space module; and the control module generates a welding path optimization scheme, a multi-welding-robot collaborative collision avoidance strategy and a welding quality feedback control instruction based on the twin data layer. According to the method, a closed-loop control framework of'physical-virtual 'bidirectional mapping is constructed, so that dynamic collaborative optimization of multi-robot motion trails, welding seam forming and thermal deformation is realized.

The invention discloses a digital production plan scheduling method and system, and belongs to the technical field of optimal scheduling, and the method comprises the steps: constructing a distributed storage architecture based on edge computing nodes; a central coordinator is adopted to realize cross-node data synchronization through an improved Raft consensus algorithm, multi-version concurrency control is realized based on a vector clock, and a global consistent data view is established; a visual scheduling platform is built based on a Vue3 framework, and man-machine interaction is realized by adopting a Canvas and WebGL collaborative rendering framework; establishing a dynamic coordinate conversion model based on bilinear interpolation, designing a space mapping function containing distortion compensation, establishing a multi-thread coordinate service based on WebWorker, and realizing submillimeter-level bidirectional mapping of pixel coordinates and physical coordinates; constructing a three-dimensional space-time analysis model fused with the multi-dimensional features; and all the units are subjected to feature fusion through residual connection, and finally a scheduling scheme with a confidence coefficient weight is output. The method and the device have the effect of meeting various scheduling requirements.

The invention discloses an electric power analysis method and system based on artificial intelligence, and relates to the technical field of electric power system intelligent analysis. Establishing a hierarchical depth map neural network model, and setting a cross-layer information interaction channel to connect each sub-network; executing a bidirectional knowledge distillation algorithm, extracting a rule set from neural network output, and forming a parameter-rule bidirectional mapping matrix; deploying a federal reinforcement learning architecture, performing parameter aggregation on the local models on the distributed power nodes, and generating a power system state evaluation result and a risk coefficient matrix; and starting the self-repairing intelligent agent network, calculating a regulation and control parameter set of the multilevel power system, and outputting a regulation and control instruction. According to the invention, through the hierarchical depth map neural network and a cross-layer information interaction mechanism, collaborative optimization among all levels of the power system is realized, and the operation efficiency and stability of the system are improved.

The invention discloses a special disease queue data capturing method and system based on an intelligent medical knowledge graph, and relates to the technical field of medical information, and the method comprises the following steps: S1, constructing a special disease intelligent medical knowledge graph which comprises a bidirectional mapping relation between standard terms of a single disease category and clinical actual corpora, clinical text data is accumulated in a mode of combining manual annotation and machine learning, and a domain exclusive knowledge base containing symptoms, diagnosis and examination indexes is formed. According to the special disease queue data capturing method and system provided by the invention, by constructing the special disease intelligent medical knowledge graph, bidirectional mapping of single disease specification terms and clinical actual corpora is realized, and the problem of insufficient semantic understanding when non-standardized clinical corpora are processed by a traditional method is effectively solved; the entity information in the unstructured medical data can be accurately extracted by utilizing a natural language processing model and an inference engine.

The invention discloses a remote sensing image open vocabulary segmentation method and system based on vision-language interaction. According to the method, the advantages of a multi-modal large language model and a semantic segmentation network based on a visual basic model are cooperatively utilized, language-pixel two-way mapping is taken as a core, five types of marks of images, texts, categories, objects and segmentation are introduced as carriers of cross-modal information, and three types of cross-modal fine-grained information interaction modules are taken as bridges, so that the cross-modal information interaction is realized. Bidirectional mapping and alignment of fine-grained information of the multi-modal large language model and the semantic segmentation network are realized, the open vocabulary segmentation capability of the semantic segmentation model is improved, and the method can adapt to different remote sensing scenes and category definitions. The method has the following advantages: the method has high performance, strong generalization ability and good expansibility, can provide any category of semantic segmentation maps for unlabeled target domain images based on instructions, and has high application value in the aspects of urban planning, map making, disaster response and the like.

The invention relates to the technical field of database management, in particular to a two-way linkage database table and supervision submission form field synchronous construction method which is applied to a supervision data submission scene. According to the scheme, the method comprises the steps that physical structure metadata of a database table and definition metadata of a supervision submission form are obtained, a semantic vector set is formed by combining metadata semantic analysis and semantic coding, and a bidirectional mapping relation graph is constructed through relation weaving; constructing a linkage propagation path according to a field change event, realizing adaptive bidirectional structure adjustment, generating a field synchronous construction scheme, and driving bidirectional mapping relation graph evolution optimization through feedback learning; according to the method, the bidirectional mapping relation graph and self-adaptive bidirectional structure adjustment are creatively combined, and efficient and self-adaptive bidirectional field synchronous construction is realized.

The invention discloses a method and a system for supporting visual and AI bidirectional intercommunication editing views. The method comprises the following steps: establishing a bidirectional mapping rule between a rendering tree protocol and an intercommunication protocol; in response to an operation of a user on the visual editor, generating a first atomic operation instruction, applying the first atomic operation instruction to the current rendering tree and triggering local redrawing of a view; serializing the updated rendering tree into context segments in an intercommunication protocol format according to the mapping rule, and pushing the context segments to an AI model; responding to a natural language editing request initiated by a user to the AI model, receiving streaming data in an intercommunication protocol format returned by the user based on the request, analyzing the streaming data according to the mapping rule to obtain a second atomic operation instruction, applying the second atomic operation instruction to the rendering tree and triggering local redrawing of a view, and obtaining a second atomic operation instruction. The view is edited by the AI, so that real-time two-way intercommunication between visual editing and AI editing is realized, and the user experience is remarkably improved.

The invention provides a 3D modeling method based on a digital twin city, and belongs to the technical field of 3D city modeling. Through a multi-source semantic data fusion acquisition means, space-time semantic tags are added to various types of data, the problem of multi-source data isomerism is solved, and semantic unification and efficient fusion of different types of data are realized; by means of hierarchical dynamic modeling means, a building component network is constructed based on triple association of geometry, functions and semantics, so that a model structure better conforms to the logic of the building industry, and the reasonability and efficiency of modeling are improved; a virtual-real two-way mapping means is applied, incremental updating of the model is triggered through a cross-modal semantic comparison algorithm, limitation of traditional static modeling is broken through, and dynamic synchronization of the virtual model and the physical world is achieved; an intelligent optimization means is adopted, a multi-constraint-condition generative adversarial network is combined with a visual attention mechanism, it is ensured that generated textures conform to building geometric features and material specifications, and meanwhile intelligent distribution of rendering resources is achieved.

The invention discloses a computer data storage method and system, and relates to the technical field of computer data storage.The computer data storage method comprises the steps that variant samples are generated through multi-modal feature extraction, font topology analysis and adversarial training, and fine modeling of Chinese character connection and pixel-level interference in an electric power drawing is achieved; an isolated storage pool path is dynamically generated through a tree-shaped namespace, and a physical storage address and version information can efficiently and uniquely correspond and retrieve in combination with bidirectional mapping of version identifier construction and block chain indexes; according to a confidence score obtained through weighted calculation of the topological similarity and the term library matching degree, once the confidence score is lower than a preset threshold value, the system pushes a manual recheck mark to a specified terminal through an asynchronous message queue, and meanwhile, read-only data locking is implemented to ensure that the writing process is not interrupted; the consensus management mechanism is based on an improved practical Byzantine fault-tolerant algorithm, and block chain index consistency and data traceability security are guaranteed.

The invention relates to the technical field of hydrological survey skill training, in particular to a construction method and system of a hydrological survey knowledge model based on a large model. The method comprises the following steps: acquiring multi-source hydrological data, and constructing a hydrological knowledge graph; generating a confusion sample corresponding to the hydrological knowledge graph, and performing adversarial training on the confusion sample; according to the confrontation training result and historical test questions in the multi-source hydrological data, obtaining bidirectional mapping test questions; inputting the bidirectional mapping test questions into a question setting interface of a hydrological survey learning platform; collecting answer data and student physiological data corresponding to the bidirectional mapping test questions in real time, and updating a student knowledge state according to the answer data and the student physiological data; constructing a hydrological survey knowledge model based on the updated student knowledge state; and generating a student recommendation learning scheme by using the hydrological survey knowledge model. According to the invention, the intellectualization and practicability of hydrological survey education can be improved.

The invention discloses a physical field reconstruction method fusing a reduced-order model and a multi-fidelity model, and belongs to the technical field of data-driven physical field reconstruction. The method comprises the following steps of: firstly, carrying out nonlinear dimension reduction on high-dimensional simulation data by utilizing a deep auto-encoder, extracting a low-dimensional feature vector, training an encoder-decoder network, and establishing bidirectional mapping between high-dimensional data and low-dimensional data; then, a mapping model from the working condition parameters to the low-dimensional features is constructed and used for predicting feature vectors under the new working condition; the prediction features are then reconstructed by a decoder into preliminary physical field data as a low fidelity trend. And finally, on the basis of the trend, in combination with sparse high-fidelity measured data, correction is carried out through a multi-fidelity fusion model, and a high-precision reconstructed physical field is obtained. According to the method, the precision and credibility of physical field prediction are effectively improved by fusing multi-source data, and the method is suitable for the fields of structural health monitoring, digital twinning and the like.

The invention discloses a low-illumination image enhancement method suitable for a complex night operation scene. The method comprises the following steps: preprocessing a collected low-illumination RGB image to obtain a preprocessed image; multi-scale features are extracted from the shallow convolution projection and the multilayer axial converter unit, and cross-layer attention is used for weighted aggregation to form enhanced features; forward noise addition is executed according to noise scheduling to obtain potential representation representing low-illumination noise distribution, and deep semantic representation is extracted in combination with a U-Net encoder embedded in CBAM; in the decoding stage, details are reconstructed through jump connection and a multi-layer converter, meanwhile, reverse denoising of a diffusion model is introduced to gradually remove noise, and an enhanced image with high brightness and low noise is output; in the training process, bidirectional mapping from low illumination to normal illumination is constructed, a weighted target of self-encoding loss and enhanced loss is introduced to carry out joint optimization on a converter and diffusion parameters, and a low-illumination scene is monitored on a general GPU / edge device.

The invention relates to a fabricated building management method and system based on BIM and digital twinning. The method comprises the steps that a BIM project model is constructed; generating project plan information; building a project digital twinborn model based on the BIM project model and the project plan information; driving a project flow process to be executed; receiving feedback information of the Internet of Things to perform space-time constraint rule verification, and driving state evolution update of the digital twin model; when the risk information is recognized, the risk type is judged, and an adaptive regulation and control strategy is executed; according to the method, a bidirectional mapping mechanism of the BIM project model and the digital twinborn model is constructed, time-space constraint verification and state evolution updating are carried out on the construction process in combination with real-time data of the Internet of Things, an adaptive regulation and control strategy is triggered when the risk is identified, real-time monitoring and dynamic optimization of the whole process of the fabricated building are realized, and the construction efficiency is improved. The method has the advantages of improving the collaboration of the construction process, reducing the rework rate and guaranteeing the project progress and quality.

The invention provides a vision-based cross-network interaction method and system, and relates to the technical field of intelligent interaction, and the method comprises the steps: obtaining a visual interaction sequence, constructing multi-modal feature representation, achieving cross-domain semantic alignment, deconstructing visual information into a hierarchical control instruction set, and transmitting the hierarchical control instruction set to a target network environment for execution after security classification. And a bidirectional mapping relation graph is constructed to realize incremental optimization. According to the method, semantic bridging between heterogeneous networks can be established, the cross-domain control precision is improved, and meanwhile safe interaction in a network isolation environment is guaranteed.

The invention relates to the technical field of water level data processing, in particular to a water level data acquisition and processing system based on the Internet of Things, which comprises a trend identification module, a sampling frequency modulation module, a data encapsulation module, an exception elimination module and an instruction linkage module. According to the method, trend recognition is achieved by analyzing the continuous water level change trend, the sampling frequency is dynamically adjusted, so that the sampling interval is matched with the actual water level fluctuation state, the response sensitivity of water level data and the timeliness of data acquisition are improved, and a uniform packaging format is constructed by adopting a timestamp index mechanism and a bidirectional mapping structure; the integrity of a water level data structure and the convenience of index management are enhanced, sudden change breakpoints are recognized through the water level amplitude difference, data are stored in a segmented mode, the data stability and the emergency situation recognition capacity are improved, and the self-adaptive capacity of water level information processing, the maintaining level of data continuity and the coping efficiency of sudden abnormity are overall improved.

The invention discloses a context-aware-based gap containerization TLS compatible method, which comprises the following steps of: distinguishing a simple TLS variable and a complex TLS variable in a source gap system, and establishing a TLS variable source feature; the method comprises the following steps: constructing a dynamic telescopic TLS memory pool matched with a variable access permission in a target system, expanding a kernel state TLS segment descriptor, constructing a bidirectional mapping table of musl TLS offset and a memory pool address, and optimizing and constructing a clustering structure aligned with a CPU cache line for a hotspot variable to improve the access efficiency; tLS variable access tracks are recorded through a dynamic binary translation engine, TLS segment descriptors are updated, the descriptors are read during thread switching to recover TLS context and refresh cache to guarantee consistency, address and offset conversion is completed according to target system alignment requirements by combining source features and a bidirectional mapping table for TLS variables of nested structures, pointers and array types, and the TLS variables of the nesting structures, the pointers and the array types are aligned. And completing dynamic conversion execution of the source system application program in the target system.

The invention provides an authentication document form generation method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining an authentication document; converting the authentication document into an XML (Extensible Markup Language) file so as to map authentication document data to an XML tree node of the XML file; standardizing the XML file through the global unique identifier and the tag system to obtain a standardized XML file; in combination with the standardized XML file, template candidate items conforming to different manageable data templates in the authentication document are extracted respectively; in combination with the template candidate item, mapping the authentication document to a target form; and establishing a bidirectional mapping relationship between the target form and the authentication document to realize bidirectional conversion between the target form and the authentication document and complete the form processing of the authentication document. Through establishment of the bidirectional mapping relation, synchronous updating of the form and the document content can be achieved, errors caused by manual operation are avoided, and automation, accuracy and practicability of document conversion are remarkably improved.

The invention discloses a drainage basin water engineering joint intelligent scheduling system and scheduling method for intelligent water conservancy. The system comprises a drainage basin water engineering joint scheduling knowledge graph distiller, a drainage basin water conservancy model set and a water engineering joint scheduling plan inference device. The drainage basin water engineering joint scheduling knowledge graph distiller starts from a drainage basin data base plate and an expert instruction, and bidirectionally distills to obtain a water engineering joint scheduling operation mode; the drainage basin water conservancy model set comprises engineering scheduling, drainage basin simulation, an artificial intelligence module, service drainage basin water engineering joint scheduling knowledge graph distillation and water engineering joint scheduling plan reasoning; and the water engineering joint dispatching plan inference device constructs a driving feedback mechanism two-way mapping relation between water engineering dispatching measures and disposal effects, and carries out water engineering optimization and dispatching measure matching inference according to the dispatching boundary condition of the current disposal event. According to the invention, drainage basin water engineering joint scheduling suggestions are provided based on big data, knowledge reasoning and a water conservancy professional model.

The invention discloses an educational data distributed storage method based on a block chain, and the method comprises the following steps: S1, collecting and preprocessing educational data, and generating a standardized data unit; s2, performing hierarchical label labeling and encryption on the data unit to generate an encrypted data block; s3, performing hash operation on the encrypted data block, extracting an abstract, a tag and a timestamp, constructing an index and writing the index into a block chain; s4, generating a unique path based on the index entry, and mapping the encrypted data block to a plurality of distributed nodes for storage; s5, constructing a bidirectional mapping relation in combination with the index entry and the binding path, and adding access control parameters; s6, the access identity is recognized, the authority is verified, an authorization identifier and a decryption token are generated, and control parameters are updated; and S7, the access party obtains the encrypted data block according to the authorization identifier, decrypts and uses the encrypted data block, and writes an access behavior into the block chain. According to the invention, encrypted storage, intelligent authorization and traceable sharing of education data are realized, and security, reliability and management efficiency are improved.

The invention relates to the technical field of engineering construction informatization, in particular to a process-level multi-dimensional coding construction file detection system and method, and the system comprises a four-dimensional dynamic coding engine, an intelligent file verification module, a block chain evidence storage and restoration module and a dynamic tracing platform. The four-dimensional dynamic coding engine generates a unique code and verifies process logic; the intelligent file verification module identifies missing files based on an engineering file template library and a weighting algorithm; the block chain evidence storage and repair module carries out cochain evidence storage on missing records and sets a time-limited completion mechanism; the dynamic tracing platform realizes bidirectional mapping and visual monitoring of the construction file and the BIM model; according to the method, through cooperation of all the modules, code generation verification, file integrity detection, missing evidence storage repair and construction whole process tracing are completed. The method solves the problems that traditional construction file management is low in efficiency, difficult in process supervision, difficult in data tracing and collaboration and the like, promotes digital transformation of project management, and improves project quality and management efficiency.

The invention discloses an operating system containerization kernel compatibility method based on shadow structure mapping, which comprises the following steps of: constructing a multi-dimensional mapping rule base by analyzing the difference of data structures between a container system and a standard system, and creating a shadow structure comprising a data area, a metadata area and an expansion area when the container system runs on a host system; the host system allocates a shadow memory space and a memory pool, establishes mapping between a shadow structure and a physical memory page and bidirectional mapping between the shadow structure and a host structure, intercepts system call of a container application, obtains a target structure and allocates a shadow structure and a host structure memory, and sends the shadow structure and the host structure memory to the host system; according to the method, conversion from the target structure to the host structure is completed according to the multi-dimensional mapping rule base, the host machine completes calling through the host structure, then the calling result is reversely converted into the target structure and returned to the container application, and seamless compatibility of the container system and the host system is achieved under the condition that a user mode program of the container system is not modified.

The invention provides a graphical programming education system, which comprises a database used for storing coding information and drawing data; the scheduler is connected with the database and used for managing data flow between the database and the interpreter; the interpreter is connected with the scheduler and is used for analyzing the coding information and generating a task in an intermediate representation form which can be understood by the system; the judgment module is connected with the interpreter and is used for carrying out logic judgment on the task and providing a control signal for the operation module; the operation module is connected with the judgment module and is used for executing the task according to the control signal and transmitting the output to the output module; and the output module is used for displaying the result transmitted by the operation module. The system is used for realizing bidirectional mapping and real-time synchronization between the coded information and the graphical representation, and realizing dynamic visualization of the coded information logic based on the data flow.

The invention discloses a cooperative control text generation method and system based on potential semantic space transformation, and relates to the technical field of artificial intelligence. Original data are input into a text generation model to obtain reconstructed data; the training process of the text generation model comprises the following steps: mapping original data to an original potential representation space through a first encoder, and generating an original potential representation; fitting the original potential representation space through an EM algorithm to optimize distribution parameters, and carrying out balanced sampling on the fitted potential space to obtain a potential semantic space; a confrontation training mechanism and an activation vector are utilized to realize bidirectional mapping between a potential semantic space and equal variance normal distribution, linear interpolation is performed on different attributes in the potential semantic space, an interpolation result is mapped back to the original potential semantic space through an encoder EN after confrontation training, and a multi-attribute text is obtained through decoding of a decoder. According to the multi-attribute cooperative control text generation method, through equalization and reversible transformation of a potential semantic space, smooth transition between multi-attribute cooperative control and attributes is achieved, and meanwhile the stability and interpretability of the generation process are enhanced.

The invention discloses a digital twinborn emergency rescue deduction optimization method for a complex disaster scene, and the method comprises the steps: constructing a composite random model for emergency resources, rescue task demands and the high dynamics and randomness of environmental elements in the disaster scene through employing a random process theory and a discretization method, and carrying out the deduction optimization of the digital twinborn emergency rescue. A deduction algorithm of a continuous state space and discrete time step length is constructed based on a digital twin deduction technology, bidirectional mapping of a physical space and a virtual space is realized, an emergency rescue optimization module based on a matching game mechanism is embedded in a digital twin deduction framework, a task demand gap and resource cost are taken as objective functions, and the task demand gap and the resource cost are taken as objective functions. And a global optimal solution is gradually approached by utilizing multi-round iteration and local strategy exchange, so that efficient optimization of resource allocation in a disaster scene is realized. According to the method, the future disaster trend can be predicted in real time, and dual optimization of task demand satisfaction and resource cost control can be realized.

The embodiment of the invention discloses a visual fine adjustment method and device of an interface, a storage medium and a terminal. Firstly, a source code and a running state preview interface are synchronously obtained, and it is ensured that operation is based on a real rendering state. Then, when the user edits the interface elements, the system accurately positions the visual elements to the corresponding positions in the source codes during operation through a pre-established bidirectional mapping mechanism. Based on the accurate positioning, the system generates a code modification instruction and updates the target code. And finally, generating a new preview by running the updated code in real time, completing an operation feedback closed loop, and realizing a real-time editing preview effect. According to the method, manual modification of complex codes is avoided through the complete process, the modification precision is ensured while the low operation threshold is kept through intuitive visual operation, and the operation simplicity and control precision are effectively balanced.

The invention discloses a regulation-work package bidirectional association and dynamic mapping method and system, and relates to the technical field of enterprise compliance management and task management informatization. The method comprises the following steps: constructing a standardized law and regulation library and a work package attribute library, disassembling a law and regulation file into compliance requirement points, and determining multi-dimensional attributes of a work package; forward mapping and reverse tracing binding of the compliance requirement point and the work package are realized through a mapping matching model; performing integrity, consistency and rationality verification on the mapping relation; monitoring the regulation change and automatically updating the mapping relation; and visually displaying the mapping relationship and monitoring compliance execution. The system correspondingly comprises a regulation management module, a work package management module, a bidirectional mapping module and the like. According to the method, closed-loop management and control of law and regulation requirements, task execution and compliance evidence are realized, the problems of unidirectional and static mapping and rough granularity in the prior art are solved, the compliance management and control accuracy and the dynamic adaptation capability are improved, and the compliance risk of an enterprise is reduced.

The invention belongs to the technical field of semantic retrieval, and particularly relates to an intelligent customer service information retrieval method and system based on a large model. Performing retrieval judgment on a differential hierarchical index tree-shaped standard semantic question and answer information base of each main body node in the distributed isolation mapping security chain, returning retrieved standard question and answer information according to key entity frequency sorting, and generating an answer by utilizing a pre-training reasoning generation model and combining with the information base when the retrieved standard question and answer information is not retrieved; when the retrieval semantics comprise a reservation demand, generating a cross-system reservation parameter set by means of a distributed reservation decision tree and standard question and answer information, outputting recommended reservation information through a bidirectional mapping dictionary and a matching recommendation algorithm, and dynamically updating the bidirectional mapping dictionary and retrieval index information by collecting the consistency frequency ratio of recommendation to real reservation in real time. And the semantic retrieval precision and the cross-system reservation accuracy are effectively improved.

The invention discloses a photovoltaic construction professional knowledge base construction and updating method based on an NLP technology. The method comprises the following steps: firstly, acquiring a multi-source text from multiple channels; photovoltaic domain entity recognition is completed by adopting a named entity recognition technology after preprocessing, an entity relationship is extracted through dependency syntax and semantic role labeling, and a knowledge triple is generated; and then performing unified modeling on entity category levels and relationship types based on the ontology, storing a triple into a graph database, storing detailed attributes and business process data of entities and relationships into a relational database, and realizing interconnection of the two databases by a bidirectional URI mapping mechanism. In the updating stage, minute-level knowledge updating is achieved through increment monitoring, entity alignment, conflict resolution and version control. And finally, performing quantitative evaluation on knowledge quality, and performing feedback by a visual instrument panel to form closed-loop optimization. Real-time and reliable knowledge support can be provided for planning, design, construction and operation and maintenance of a photovoltaic project through knowledge base entity recognition query constructed by the method.