2873 results about "Information technology" patented technology

The invention discloses a power grid equipment state sensing driving dynamic response method based on the Internet of Things technology, and relates to the technical field of power system automation and informatization, and the method comprises the following steps: S001, collecting original multi-dimensional state signals of a plurality of sensors deployed in a power grid equipment state sensing channel, constructing an electromagnetic disturbance recognition model, and carrying out the recognition of the original multi-dimensional state signals; frequency domain and time domain feature extraction is carried out on the signals, and a feature comparison parameter set used for distinguishing electromagnetic interference and real faults is generated. Frequency domain and time domain features are extracted through an electromagnetic disturbance recognition model, dynamic threshold judgment and response strategy adjustment are achieved in combination with multi-source sensing data, interference and faults can be accurately distinguished, early warning and protection logic can be corrected in real time, protection actions can be accurately triggered, closed-loop control is achieved, the delayed fault tolerance and multi-source verification capacity is achieved, and the method is suitable for large-scale popularization and application. The false operation rate and the false stop risk are effectively reduced, and the intelligence, the safety and the stability of power grid operation are improved.

The invention discloses an illness state tracking management system and method based on a lingual face diagnosis instrument, and belongs to the technical field of traditional Chinese medicine tongue diagnosis and modern information technology fusion. The system comprises a multi-modal data acquisition module, a data processing and analysis module and an augmented reality visualization module; according to the method, illness state tracking is achieved through the steps of multi-modal data acquisition, data preprocessing and feature fusion, personalized digital twinborn model establishment, augmented reality visualization presentation and the like, multi-dimensional data such as tongue picture macroscopic features and tongue surface microorganism distribution can be integrated, dynamic association between the data is revealed, the health state and the intervention effect are visually displayed, and the method is suitable for being popularized and applied. The method is suitable for the fields of traditional Chinese medicine health management and chronic disease monitoring.

The invention relates to an enhanced LLM-RAG multi-hop question and answer method based on logic tree reasoning, and belongs to the technical field of new-generation information, and the method comprises the following steps: inputting a multi-hop question and answer question into a computer system; the computer system calls a pre-training large language model LLM, the multi-hop question-answer question is decomposed into a hierarchical logic tree in a recursive mode, and each node of the logic tree comprises a sub-question and a corresponding hypothesis answer; performing image retrieval from a structured knowledge source Wikidata and performing text retrieval from an unstructured knowledge source Wikipedia on the basis of each node sub-question and the hypothesis answer to obtain corresponding evidence; traversing the logic tree, verifying the consistency between the hypothetical answer of each node and the evidence through LLM, if the contradiction exists, reconstructing the corresponding sub-tree, and dynamically correcting the reasoning path; and integrating the verified logic tree node information, and outputting an accurate answer to the multi-hop question and answer question.

The invention belongs to the technical field of tunnel and underground engineering intelligent construction and geotechnical engineering informatization, and discloses a high-energy geological environment surrounding rock classification and decision-making method based on digital twinning and multi-source feedback. The problems caused by difficulty in realizing surrounding rock state dynamic sensing, multi-source data fusion classification and construction decision closed-loop linkage in the prior art in a high-energy geological environment are solved. The method comprises the following steps: firstly, constructing a tunnel three-dimensional geology-structure digital twinborn body based on initial survey data; in the construction process, multi-source data such as geology, construction disturbance and surrounding rock response are collected in real time through the Internet of Things technology and mapped to the digital twinborn body, and virtual-real synchronous updating is achieved. And then, constructing a deep learning-parameter inversion hybrid model on the basis of the multi-source fusion data, outputting a dynamic surrounding rock classification index DRCI and key mechanical parameters, inputting the DRCI and the key mechanical parameters into a multi-objective optimization module, and giving a self-adaptive drilling and blasting scheme. And finally, reversely correcting the model through a construction feedback result to realize closed-loop self-learning.

The invention discloses an information retrieval system and method based on semantic normalization, and relates to the technical field of artificial intelligence information, and the method comprises the steps: collecting a semantic query record input by a user, carrying out the preliminary semantic analysis, and generating structured data; on the basis of the structured data, entity disambiguation is carried out by utilizing a knowledge graph, abstract classes are generated through a neural network, calibration and dynamic weight adjustment are carried out, and high-confidence entity abstract classes and confidence scores are generated; entity abstract classes and confidence scores are combined with user contexts, an action-value function is calculated through a value network, and an optimal action is selected by utilizing a-greedy algorithm; executing semantic normalization mapping according to the optimal action, and obtaining an intermediate expression by using a meta-symbol dynamic generator; and performing index retrieval and multi-dimensional sorting based on the intermediate expression to generate a sorted retrieval result list. According to the method, the semantic fragmentation problem of multi-modal query is solved, and deep semantic alignment and dynamic weight calibration of heterogeneous data are realized.

The invention relates to the field of geographic information technology and natural resource management, and discloses an automatic analysis system for land utilization flow change in land change investigation. The system comprises an object-level spatiotemporal spectrum tree reconstruction and data initialization module, a topological potential energy field construction module based on evolution entropy, a multi-scale geometric difference extraction and morphological analysis module, a variable stiffness topological adsorption and decoupling module based on a stiffness ratio, and a flow damping filtering and event serialization module driven by semantic rules. The system constructs a topological potential energy field by using a historical state vector and semantic stiffness, performs one-way adsorption, adjustment or retention on a difference polygon according to relative stiffness, and cleans invalid traffic based on a damping matrix. According to the method, through physical field simulation and semantic logic verification, high-frequency disturbance misjudgment is effectively eliminated, pattern spot boundary correction is ensured to conform to the legal weight, and the authenticity and logic self-consistency of change survey data are improved.

The invention discloses a shield tunneling intelligent control method and system based on a ground-tunnel-machine-information-human adaptation level, and relates to the crossing field of underground engineering intelligent construction and information technology. Setting a first-level index and a second-level index; dividing the shield construction state into three levels of intelligent adaptation levels by combining the total score of the construction state with a dynamic threshold value; setting four targets of attitude intelligent control, settlement intelligent control, tunneling efficiency optimization and construction abnormity diagnosis; a machine learning prediction model is constructed, and the construction state parameters corresponding to the targets are predicted in real time; according to the shield intelligent adaptation level, the man-machine cooperation modes are divided into three classes of A level, B level and C level; and comparing actual data with a prediction result of the machine learning model, and dynamically correcting the control target parameters. Through real-time sensing of geological, mechanical and environmental multi-dimensional construction states and in combination with a dynamic weight distribution strategy, precise evaluation of the shield construction state is achieved, and meanwhile self-adaptive switching of the man-machine control right is achieved.

The invention relates to the technical field of artificial intelligence application, and discloses an information technology auxiliary consultation system based on artificial intelligence. The system comprises a data acquisition module, a knowledge graph construction module, an intention analysis module, a decision engine module, a strategy optimization module and a feedback correction module. The data acquisition module acquires multi-dimensional data such as a semantic type, an intention label and a historical interaction record of a user consultation request in real time; the knowledge graph construction module dynamically generates a hierarchically associated domain knowledge graph according to the domain database; and the intention analysis module completes user intention classification and analysis through a multi-level attention mechanism. The decision engine module combines the analysis result and the knowledge graph to generate candidate strategies, and the strategy optimization module screens out target strategies meeting real-time response requirements through an adaptive weighting algorithm. The feedback correction module utilizes user interaction data to update system parameters, improves service precision, and is suitable for various information technology consultation scenes.

The invention belongs to the technical field of logistics information, and discloses a multimodal transport trusted data space construction method based on privacy calculation and a block chain. The method comprises the following steps: deploying a modular intelligent data gateway at a core node of a multimodal transport line, unifying the format of multi-source heterogeneous original data, and chaining a hash value; after the multi-source heterogeneous data is subjected to customization processing, key metadata attributes of all the data are registered and linked in real time; constructing a core ontology model, and establishing a cross-domain semantic interoperation capability; establishing a privacy calculation and block chain collaborative dual-channel architecture, and cooperatively training an ETA prediction model in a local data isolation environment by adopting transverse federal learning to ensure that original trajectory data is not out of a domain; constructing a dispute arbitration and credible verification system, and realizing an arbitration process of judicial verification when a transportation dispute occurs; data minimization disclosure and compliance sharing are achieved through dynamic access control. According to the method, multimodal transport data can be available and invisible, and the whole operation process can be audited.

The invention discloses a cerebral apoplexy multi-mode early screening intelligent evaluation system based on a large model, and relates to the technical field of medical health information, the cerebral apoplexy multi-mode early screening intelligent evaluation system comprises an intelligent management platform, and the intelligent management platform is in communication connection with the following modules: a multi-source heterogeneous data fusion engine, the data integration module is used for integrating multi-modal data including clinical data and terminal health data and constructing a health portrait of a patient; and the cerebral apoplexy knowledge graph construction platform is used for constructing a cerebral apoplexy domain knowledge graph in combination with evidence-based medical knowledge. By combining the digital twinning technology and the intelligent risk assessment engine, the influence of different intervention schemes on the cerebral apoplexy risk can be simulated, personalized intervention suggestions are generated, a patient is helped to reduce the cerebral apoplexy risk and change from passive prediction to active intervention, the patient is helped to take effective measures earlier, the health condition is improved, and the patient experience is improved. The occurrence of cerebral apoplexy is prevented, so that the disability rate and the death rate caused by cerebral apoplexy are reduced.

The invention relates to the technical field of data management and information, and discloses a data asset identification system and method based on multi-dimensional rule engine blood relationship analysis, and the method comprises the steps: obtaining static code information and dynamic operation tracking information of to-be-analyzed data; constructing a theoretical data blood relationship map based on the static code information; constructing a real-time data blood relationship map based on the dynamic operation tracking information; generating a fusion data consanguinity map by adopting a time window alignment strategy; constructing a five-dimensional data asset identification rule model; starting a blood relationship driven multi-dimensional rule engine; executing the multi-dimensional rule engine, and evaluating and determining the nature of the to-be-analyzed data; in the evaluation process, a conflict resolution mechanism is started. According to the method, the multi-dimensional rule engine is driven through dynamic and static combined blood relationship analysis, and conflict judgment is performed by using blood relationship information.

The invention relates to the technical field of artificial intelligence and information, provides an AI-based campus security risk dynamic monitoring system, and aims to solve the limitations of data fragmentation, risk identification lagging, insufficient early warning, manual dependence and the like of an existing campus security monitoring system. The system comprises a multi-source data acquisition subsystem, an integrated preprocessing subsystem, an AI analysis subsystem, a dynamic evaluation prediction subsystem, an intelligent early warning response subsystem and a system self-learning optimization subsystem, and realizes real-time acquisition, deep fusion and intelligent analysis of campus heterogeneous data so as to realize dynamic evaluation, accurate prediction and active early warning. According to the technical scheme, the intelligent and automatic level of campus safety management can be remarkably improved, the manual load is relieved, active prediction and accurate early warning are achieved, false alarm and missing alarm are reduced, and the management efficiency is improved.

The invention discloses an intelligent wheat yield prediction method and system, and relates to the technical field of agricultural information. According to the method, basic geography, climate, soil, crop physiology and agricultural management multi-source data are collected, and an input feature set is obtained through preprocessing and feature engineering; constructing an Attention-LSTM-CNN model fused with an improved attention mechanism, extracting local features through CNN, capturing time sequence association through LSTM, highlighting key contribution through an attention layer, and finishing model training in combination with an RMSE loss function and an Adam optimizer; and dynamically updating data and a prediction result in a wheat growth cycle, and outputting and triggering early warning in multiple forms. The system correspondingly comprises a data acquisition module, a data storage module, a data preprocessing module, a model calculation module, a prediction output and early warning module and a communication module. The method solves the problems that a traditional method is single in data, poor in model adaptability and lack of dynamic prediction, high-precision full-period prediction is achieved, and scientific support is provided for agricultural decision making.

The invention discloses a radiator micro-channel structure integrity detection method based on acoustic measurement, and relates to the technical field of information, the method couples acoustic propagation measurement with density inversion and particle transport observation, firstly screens a key observation object according to density gradient change, and then constructs a hydrodynamic equilibrium graph by using auxiliary particle flow, and finally obtains the structural integrity of the radiator micro-channel. And channel-by-channel difference is carried out with reflection measurement of standard acquired data, so that defects are indicated by three domains of energy, time and space together. According to the closed-loop link, the sensitivity to tiny blockage, slight deformation and early crosstalk is remarkably improved, the false alarm rate that single measurement is easily influenced by noise and working condition fluctuation is reduced, fine positioning of channel-level abnormal positions and ranges is achieved, and the closed-loop link is suitable for high-resolution detection of dense micro-channel arrays without disassembly or destructive operation.

The invention provides a multi-tenant data pushing method, and relates to the technical field of computer software and information, and the method comprises the steps: achieving unified identity authentication through single sign-on, and dynamically distributing a pushing authority based on an authority strategy; defining conversion rules and tasks by utilizing a visual interface of the low-code configuration center, and generating a standardized data packet; and centralized scheduling is carried out in a multi-tenant management and control center, and the stability of the system is guaranteed by combining a current limiting and dynamic retry mechanism. Source system data are collected in real time, and format conversion is completed through a rule engine after grammar, permission and event state verification. And pushing in an asynchronous mode, and recording full-link information including a tracking ID, a timestamp, a data fingerprint and a response state. And when pushing fails, a compensation mechanism is triggered, degradation or retry is carried out according to a preset rule, final consistency of data is ensured, and the reliability and maintainability of the system are improved.

The invention relates to a low-code visualization optimization method and system for power credential development, and the method comprises the following steps: S1, obtaining data in a credential environment, recognizing the interface difference and performance bottleneck points between components through a compatibility test matrix, and building a standardized adaptive interface specification; s2, obtaining a standardized business object model based on the standardized adaptive interface specification; based on the business object model, defining attributes, relationships and constraint rules of each business entity, and forming a data dictionary and an interface specification special for the electric power field; s3, on the basis of the data dictionary and the interface specification special for the power field, constructing a DSL (field specific language) of power visualization; s4, a dragging type interactive design is adopted, and the visual operation is converted into a DSL configuration file; and S5, automatically converting the DSL configuration into a React or Vue component code through a code generation engine, and carrying out compatibility optimization on the kernel of the creative browser. According to the invention, the power credential development efficiency is effectively improved.

The invention provides a BIM component automatic identification and storage method and system based on multi-modal artificial intelligence fusion, and relates to the technical field of building information, and the method comprises the steps: receiving a BIM component model file, and preprocessing an obtained attribute parameter table; inputting the information into a multi-modal recognition engine, and outputting a classification result and confidence through Rapidfuzz fuzzy matching file names, OPEN-CV + YOLOv8 image recognition and knowledge graph analysis parameters; the dynamic fusion decision-making module calculates the final confidence coefficient according to the dynamic weight, and solves classification conflicts in combination with a dynamic rule base of industry specification rule priority; according to a confidence coefficient threshold value, judging automatic warehousing or triggering grading manual auditing; manual audit data are collected and fed back to the multi-mode recognition engine, and incremental knowledge self-learning is achieved. Through multi-modal fusion and dynamic decision making, the BIM component recognition accuracy and warehousing efficiency are remarkably improved, personal errors are reduced, and dynamic updating of a component resource library and system self-evolution are achieved.

The invention relates to a method and system for encrypting and isolating storage data of a credential mobile terminal, and belongs to the technical field of information. The method comprises the following steps: encrypting and partitioning the whole storage area, and setting an access strategy according to user permission; when a user requests to access, executing multi-factor authentication containing a password and an external hardware certificate, and adding biological characteristic authentication; after the authentication is passed, an encryption key is taken from the domestic security chip; and encrypting and decrypting data by using the secret key, and opening corresponding partition access according to authority. The system comprises a storage partition module, an identity authentication module, a key management module, an encryption and decryption module and an authority control module and is used for executing the method. The method also comprises the steps of equipment startup trusted boot and firmware upgrade verification, is based on a custom curing system, and is compatible with Android 10 +. The problems of poor hardware controllability and positioning security risk of the creative mobile terminal are solved, and full-link data security protection is realized.

The invention discloses a mobile phone energy consumption optimization method, and relates to the technical field of information, and the method comprises the steps: obtaining a current game frame of a mobile phone game application, and extracting a key rendering parameter of the current game frame; according to the current game frame and the historical game frame, calculating a static scene element space consistency score and a dynamic rendering object state change rate; according to the static scene element space consistency score and the dynamic rendering object state change rate, generating a computing resource allocation scheme; according to the computing resource allocation scheme, GPU rendering pipelines and CPU computing resources are configured, corresponding game computing execution paths are selected, and the computing execution paths comprise a complete rendering pipeline path, an incremental rendering path or an inter-frame interpolation path; aiming at high energy consumption of 3D scene rendering in a mobile game, a three-level rendering strategy selection mechanism based on scene change degree and the like are established, and the energy consumption of a mobile phone is reduced while the game quality is kept.

The invention discloses an intelligent traceability system for veterinary drug safety information, which relates to the technical field of veterinary drug safety and information and comprises a data fusion module, a risk traceability module, an event reconstruction module, a chain integration module, a critical path module and a report generation module. The system dynamically constructs a risk association map by fusing multi-source heterogeneous data in production circulation, actively recognizes a potential risk veterinary drug batch cluster and realizes full-chain reverse tracing. Fine-grained event reconstruction is carried out on each link, a risk event chain is formed after integration, a core event sequence causing risks is extracted by calculating the contribution degree weight of each event, and finally a traceability report and a disposal suggestion are generated in combination with a safety knowledge base. According to the system, intelligent tracing from passive query to active early warning and from link enumeration to root cause accurate positioning is realized.

The invention relates to the technical field of information, and provides a bulk commodity transaction system based on a block chain, and the system comprises a parameter and publishing module which uniformly receives and stores parameters; the unified examination and approval engine performs isomorphic arrangement and gray level updating through a configurable template and a state machine; consistency snapshots and recovery are paused / abnormally collected snapshots and monotonically replayed, and it is guaranteed that the sequence is consistent with a window; the security fund risk control uses DSL + fund DAG to drive freezing / unfreezing / deduction and account checking; and block chain evidence storage and auditing execute field-level hash and pedigree anchoring to realize verifiable traceability. According to the system, an end-to-end consistency and verifiability framework is constructed around the aspects of field-level fingerprinting, unified examination and approval, windowed stable sorting, consistency snapshot and monotone replay, fund event patterning, contract assembling and signature anchoring, settlement / final recalculation and pedigree uplink and offline verification; and under the conditions of abnormity, recovery and version evolution, each link keeps uniform caliber, stable sorting and approvable state.

The invention provides a photovoltaic knowledge question-answering method, system and device based on a ReAct architecture, and relates to the technical field of photovoltaic information. The method comprises the steps that a photovoltaic industry knowledge base is obtained, original photovoltaic industry knowledge documents are processed through analysis, abstract generation and abstract vectorization, and a three-layer storage structure containing an abstract vector index table, a document metadata table and a complete document storage library is formed; obtaining a user question, initializing a ReAct cycle and creating a memory storage structure according to the user question and a retrieval tool set constructed based on the three-layer storage structure; the ReAct circulation is executed until the end, and each round of circulation comprises the steps that questions, system cue words and memory data are integrated to generate a context, a round tool and parameters are obtained through reasoning of a large language model, and accordingly the tool is called to retrieve a knowledge base, update memory and remove duplication; after the loop is terminated, an answer is generated based on the memory data. According to the method, when the photovoltaic problem is solved, the key diagnosis link and the solution can be deeply given out without omitting the key diagnosis link and the solution.

The invention provides a PDF document intelligent word segmentation method based on content structure perception, and belongs to the technical field of computer information.The PDF document intelligent word segmentation method comprises the steps that firstly, by fusing layout analysis and multi-tool analysis, multiple types of content such as title levels, ordinary tables, characters in pictures and tables in the pictures in a PDF are accurately recognized and extracted; secondly, providing a structure-perceived word segmentation strategy, and carrying out differentiation processing according to content types, namely, dividing semantic blocks by taking a title as a guide, taking a complete table as an independent semantic unit, and carrying out context association on a picture OCR (Optical Character Recognition) result; and finally outputting high-quality knowledge fragments rich in metadata such as levels and types. According to the method, the information integrity and semantic accuracy of the PDF document during construction of the large model knowledge base can be remarkably improved.

The invention relates to the technical field of information, and discloses a radar dynamic anti-interference method and system based on interference source positioning. The method comprises the following steps: acquiring current signal data and a historical signal sequence, and determining an initial deviation value; extracting a historical deviation sequence according to the initial deviation value to obtain a deviation change trend vector; calculating a trend slope and a fluctuation amplitude, and determining an adjustment trigger signal; extracting feature interaction influence according to the adjustment trigger signal, and determining a weight coefficient update increment; iterative optimization is carried out in combination with the convergence rate parameter, and an optimized convergence rate value is obtained; adjusting deviation compensation model parameters according to the convergence speed value, and outputting a deviation compensation result when the compensation residual error is lower than a preset threshold value; and carrying out positioning calculation according to a deviation compensation result, and determining a corrected positioning coordinate. The model is dynamically optimized through technologies such as a sliding window and gradient descent, the problem of positioning deviation caused by complex environment signal interference is solved, and the positioning precision and the response speed are improved.

An information technology system for a distributed manufacturing network includes an additive manufacturing platform configured to manage workflows for a set of distributed manufacturing network entities associated with the distributed manufacturing network. The information technology system includes a set of digital twins generated by the additive manufacturing platform. The information technology system includes an artificial intelligence system configured to be executed by a data processing system in communication with the additive manufacturing platform. The artificial intelligence system is trained to generate process parameters for the workflows managed by the additive manufacturing platform using data collected from the set of distributed manufacturing network entities. The information technology system includes a control system configured to adjust the process parameters during an additive manufacturing process performed by at least one of the set of distributed manufacturing network entities.

The invention discloses a three-dimensional geological model dynamic updating system and method based on multi-modal data fusion, and belongs to the technical field of geological engineering and information. According to the method, multi-source data of geological radar, earthquake, drilling, remote sensing and the like are integrated, and after unified formatting and quality optimization preprocessing, geological features of a stratum interface, a fault zone and the like are automatically extracted by using a deep learning network; multi-source feature data fusion is realized through space-time registration and attention; constructing a three-dimensional geologic model by adopting a TIN and Octree mixed structure based on a fusion result; dynamic updating of the model is realized through incremental detection and a local reconstruction mechanism, and the boundary of the model is optimized by adopting a radial basis function interpolation. According to the method, the problems of single data, updating lag and the like of a traditional method are solved, the modeling precision and efficiency are remarkably improved, and reliable support is provided for geological engineering decision making.

The invention relates to the technical field of power system operation and control, and particularly discloses a time-sharing electric quantity prediction method based on a logarithmic load density growth curve, which comprises the following steps of: firstly, performing causal detection and dynamic time-delay optimization on historical load and multivariate external data through convergence cross mapping and mutual information technologies, and constructing a causal time-delay feature set; and the problems of multi-element coupling and time-delay effect quantization are solved. Secondly, fitting a load trend by using time-frequency decomposition in cooperation with a segmented logistic model, extracting dynamic parameters representing a growth rate and a saturation capacity, and endowing the model with a sensing ability for a load evolution stage; then, causal features, growth parameters and load components are deeply fused through cross-domain modulation and a gating mechanism, the nonlinear modulation effect of an external environment on a load mode is explicitly modeled, and finally, a probability interval is generated in combination with quantile regression and residual error correction. According to the scheme, accurate and probabilistic prediction of the time-sharing electric quantity in a complex scene is realized, and the scientificity of an agent electricity purchase decision is improved.

The embodiment of the invention relates to the technical field of information, and discloses an intelligent multi-source data quality evaluation and verification method and device, a medium and a product, and the method comprises the steps: converting intelligent multi-source data into standardized format data; performing quality evaluation on the standardized format data, wherein the quality evaluation comprises at least one of integrity check, availability check and consistency check; loading a robot URDF model corresponding to the standardized format data, driving the URDF model to move according to joint data, and synchronously playing corresponding visual data for realizing linkage playback of model actions and visual pictures; analyzing linkage playback through the first large model and / or the second large model; wherein the first large model is used for judging the physical safety of the robot action, and the second large model is used for judging the high-level semantic correctness of the robot action and task annotation, so that a high-quality and reliable self-service intelligent data set is constructed.

The invention discloses a retrieval method based on a semantic enhanced knowledge graph, which relates to the technical field of information, and comprises the following steps: receiving a natural language query of a user, and carrying out deep analysis on the query, including named entity recognition and linking, relationship extraction and query intention classification; and based on an analysis result, extracting a related local sub-graph from the knowledge graph, generating a query context vector, and generating dynamic semantic embedding for the sub-graph through a query-perceived graph attention network to obtain a dynamic enhanced semantic graph. According to the retrieval method based on the semantic enhancement knowledge graph, the retrieval precision and the recall rate are remarkably improved, the limitation of static knowledge representation is solved through a dynamic semantic enhancement mechanism of query intention perception, so that the local semantic representation of the knowledge graph is highly aligned with the query intention of a specific user; and the ability of understanding and answering complex, fuzzy, ambiguous and multi-hop queries is improved.

The invention discloses an intelligent earth surface solar radiation forecasting method based on satellite remote sensing, and belongs to the field of information technology and meteorological technology. The method comprises the following steps: S1, acquiring geostationary satellite observation data, satellite inversion earth surface solar radiation data and terrain factor data, and executing Z-score standardization processing; s2, performing dimensionality reduction on the standardized input sequence and the target data by using a pre-training auto-encoder to obtain latent variables of a historical sequence and a future cloud picture observation sequence; s3, inputting the dimension-reduced historical sequence into a conditional potential space diffusion model, modeling the historical satellite cloud picture sequence, and predicting a probabilistic potential variable of a cloud picture at a future moment; converting the solar radiation prediction result into a corresponding earth surface solar radiation prediction result through an inversion model; and S4, the self-encoder is adopted to perform dimension raising to obtain a final prediction result. According to the method, based on a frequency domain and space domain multi-modal feature adaptive fusion mechanism, while a complex cloud-radiation relation is modeled, predicted structural consistency and physical rationality of radiation intensity are kept.