589 results about "Information support" patented technology

The invention discloses an enterprise global data analysis method based on a knowledge graph and a large language model, and the method comprises the following steps: collecting internal and external multi-source data of an enterprise, cleaning, standardizing and mapping, and constructing a unified data graph; after a user inputs a natural language query, a reasoning target and task description are generated in combination with semantic understanding, two reasoning paths are formed through structural reasoning and semantic reasoning respectively, and the two reasoning paths are fused for interactive verification and optimization. Logic conflicts and data missing are detected in real time in the reasoning process, and supplementary knowledge is automatically called for local reasoning correction. Through the corrected reasoning result, the system carries out semantic alignment and correlation analysis on multi-source data, a unified enterprise data analysis view is dynamically generated, a reasoning path and evolution information are recorded in the reasoning and analysis process, and subsequent traceable query is supported. According to the method, the data integration, intelligent reasoning and decision support capabilities of an enterprise in a complex data environment are improved.

The invention discloses a vertical field document question-answering method and system based on a knowledge graph enhanced large model, and the method comprises the following steps: S1, construction of a knowledge graph: collecting related data of a vertical field, and cleaning and sorting the related data; performing knowledge extraction on the processed data, and designing a domain ontology according to a knowledge extraction result to construct and store a knowledge graph; s2, questioning and answering based on the knowledge graph: extracting key entities and relationships in the input text, and querying related information from the knowledge graph according to the key entities and the relationships; and dynamically constructing a prompt based on the knowledge graph query result and the question, inputting the prompt into the large model, and generating an answer. The method has the advantages that data of professional fields are structured by constructing the vertical domain knowledge graph, authoritative and reliable background information support is provided during question answering, and it is ensured that model answering is more scientific and accurate.

The invention discloses a motor vehicle maintenance management service system, and relates to the technical field of motor vehicle maintenance management, and the system comprises a client information management module which builds data for storing client multi-information, supports multi-format import and export, intelligently recognizes and updates, and guarantees the information to be timely and accurate; the vehicle fault diagnosis module is provided with various interfaces and expert systems, analyzes and diagnoses faults based on big data, and gives reasons, suggestions and cost estimation; the maintenance work order management module supports work order full-process operation, automatically distributes personnel and updates the progress in real time for clients to inquire; the maintenance accessory management module is provided with an inventory database and can intelligently match accessories and provide position query navigation; and the maintenance personnel management module is used for storing personnel information and evaluating performance. According to the invention, management efficiency and accuracy can be improved, accessory management and cost are optimized, personnel quality and service quality are improved, customer experience and satisfaction are enhanced, powerful support can be provided for enterprise decision making, and intelligentization of the motor vehicle maintenance industry is promoted.

The invention discloses a multi-modal enhanced retrieval method and system, and the method comprises the steps: obtaining heterogeneous data, and executing data processing to obtain a meta-information set; encoding the meta-information set into a high-dimensional meta-information vector, and constructing a vector index; receiving a query statement of a user, calculating the similarity between the query statement and the meta-information vector, and obtaining a meta-information query result; and calling a large language model based on the obtained meta-information to generate a summary result, and merging and outputting the summary result and heterogeneous data corresponding to the meta-information. According to the method, multi-modal data is processed into unified semantic vector representation, efficient vectorization indexing and semantic generation and expansion capacity of a large-scale language model are combined, high-value information can be rapidly extracted from multi-source heterogeneous data, and real-time, cross-modal and high-precision retrieval requirements are supported. A reordering and traceability mechanism introduced in the scheme further enhances the correlation and reliability of the information, and provides comprehensive and accurate knowledge support for the generation of query results.

The invention discloses an emergency rescue strategy and system for emergencies in a tunnel, and belongs to the field of intelligent expressways and traffic control intelligence. The method comprises the following steps: acquiring historical emergency data and a historical management and control strategy; preprocessing the historical emergency data and the historical management and control strategy to obtain preprocessed data; acquiring entities, relationships and attributes from the preprocessed data; constructing a knowledge graph according to the entities, the relationships and the attributes; acquiring current emergency information; and obtaining a final emergency rescue scheme from the knowledge graph according to the current emergency information. According to the invention, by constructing the (special) long tunnel emergency rescue knowledge graph, systematic integration and efficient utilization of historical data and experience knowledge are realized, and rapid, accurate and intelligent information support and application services are provided for tunnel management departments in emergency rescue work.

The invention discloses an expressway air-ground integrated intelligent tour inspection system, and relates to the technical field of expressway tour inspection. The inspection management platform is in communication connection with a data acquisition module, an environment perception analysis module, a target detection module, a disease target classification module, a pavement disease dynamic identification module and an inspection early warning management module, and the data acquisition module is used for collecting and preprocessing various inspection data required by highway inspection. Through cooperative work of air patrol of the unmanned aerial vehicle and the ground sensor, large-area patrol data can be rapidly obtained, all-directional and real-time monitoring of the expressway is achieved, the patrol efficiency is remarkably improved, a large-area patrol task can be completed in a short time, potential road diseases can be found in time, and the safety of the expressway is improved. Timely and accurate information support is provided for road maintenance and management departments, and safe and smooth operation of the expressway is guaranteed.

The invention discloses a map navigation method and system based on integrated navigation, and particularly relates to the field of integrated navigation, comprising compass data acquisition, magnetic declination correction, map integration, navigation system data acquisition, navigation system data analysis and integrated navigation. According to the method, the precision and robustness of the navigation system are remarkably improved, different environments can be dynamically adapted, and the error influence is reduced; rich geographic information support is provided by presetting an electronic map and POI marks; the real-time navigation service provides visual road condition information and path planning, the user experience is enhanced, and on the whole, more accurate, reliable and convenient navigation service is provided for the user.

The invention discloses a multi-source fusion detection and formation recognition system for an unmanned aerial vehicle cluster. The multi-source fusion detection and formation recognition system comprises a radar detection system, a photoelectric detection system and an information processing module. The invention further discloses a multi-source fusion detection and formation recognition method for the unmanned aerial vehicle cluster. The method comprises the steps that the radar detection system obtains the initial azimuth information of the unmanned aerial vehicle; the information processing module generates guidance information according to the initial azimuth information; the photoelectric detection system tracks the unmanned aerial vehicle according to the guidance information to obtain an image of the unmanned aerial vehicle; and the information processing module obtains the three-dimensional position information of the unmanned aerial vehicle according to the initial azimuth information and the unmanned aerial vehicle image, carries out the recognition of the unmanned aerial vehicle cluster formation pattern, and obtains a formation pattern structure. According to the method, accurate identification and three-dimensional coordinate acquisition of individual targets in a long-distance high-resolution unmanned aerial vehicle cluster and feature identification of the formation of the unmanned aerial vehicle can be realized, and high-reliability information support is provided for command, control and strike decisions.

The invention relates to the technical field of road pavement disease recognition, in particular to an intelligent road pavement disease recognition method and system based on a multispectral image, and the method comprises the steps: obtaining road pavement image data collected by a multispectral camera carried by an unmanned aerial vehicle; generating a registered multispectral fusion image; performing enhancement processing on the multispectral fusion image based on a dark channel algorithm to generate an enhanced image; performing shallow feature extraction and deep feature extraction on the enhanced image according to a convolutional neural network to generate an initial disease extraction image; performing segmentation processing on the initial disease extraction image through adaptive threshold segmentation to generate a binary image; performing morphological processing on the binary image to generate a candidate disease image; extracting edge information of a disease area from the candidate disease image based on an instance segmentation technology, and generating a segmented image; the segmented image is subjected to crack refining processing, a crack refined image is generated, and more comprehensive disease information support is provided for collection and fusion of multispectral data.

The invention belongs to the technical field of three-dimensional geological modeling, and discloses a real-time three-dimensional geological modeling system and method based on groundwater dynamics. The system comprises a geological data acquisition module, a complex geological structure modeling module, a geological body internal attribute simulation module, an underground water monitoring module, an underground water simulation module, a geological evolution simulation module, an underground water-geological body simulation module and a visual interaction module. By integrating multi-source data and applying advanced data cleaning and quality control technologies, the accuracy and consistency of the data are ensured, then by utilizing advanced geologic structure modeling and geologic body internal attribute simulation technologies, a high-precision three-dimensional geologic body model is constructed, and the accuracy and consistency of the geologic body model are improved. A reliable space frame is provided for dynamic simulation and analysis of underground water, and timely and accurate information support can be provided for water resource management and environmental protection. The method has a wide application prospect and an important practical value in the fields of dynamic monitoring, analysis and simulation of underground water.

The invention relates to the technical field of knowledge maps and large models, and discloses a fully-mechanized coal mining equipment large model decision support method and system. The method comprises the following steps: defining entities in data information of fully-mechanized coal mining equipment and a relationship between the entities to form triple data; converting the triple data into question and answer pairs based on the question and answer template, and optimizing the question and answer pairs; establishing a large language model, training the large language model based on question and answer pairs, performing fine tuning on the large language model based on a LoRA technology, and performing quantification processing on the equipment state in combination with fuzzy comprehensive evaluation to obtain a quantification result; the system uses the fine-tuned large language model to carry out entity and intention recognition on a natural language input by a user, a Cypher query statement is constructed to carry out query in a graph database, sub-graph information is obtained, the sub-graph information and the quantization result serve as cue words and are transmitted to the large language model, and retrieval information supporting large model decision making is obtained. The operation and maintenance efficiency of the fully-mechanized coal mining equipment is improved.

The invention discloses a bidding document writing management system and a bidding document writing management method, the system comprises a bidding document generation module, a bidding document splitting module and a bidding document duplicate checking module, the system takes an enterprise knowledge base as reference information, and after a user uploads a bidding document, bidding document content meeting bidding requirements is automatically generated; a required picture is automatically matched according to the text content and intelligently inserted into a proper position; and template adjustment of different formats is supported, and diversified bidding document requirements are met. Through semantic analysis of terms of the bid invitation book, waste bid items are automatically identified; performing tagging classification on the split content of the bid inviting book to generate a tagged document; and according to the bid inviting book splitting result, a common letter template is automatically generated for subsequent filling. The method supports the multi-dimensional duplicate checking of the bidding book, identifies whether the bidding book has a surrounding bid and a cross bid through big data analysis, and provides a detailed report. And the bidding document writing and management efficiency and accuracy are effectively improved.

The invention discloses a network security situation awareness and analysis platform based on AI, and relates to the technical field of network security situation awareness and analysis, and the platform comprises a multi-source data collection module which integrates flow, logs, assets and threat intelligence data, and carries out encryption transmission and standardization; the data preprocessing module purifies and optimizes data, and guarantees data quality and sensitive information security; the AI situation awareness analysis module extracts features through a deep learning model, dynamically evaluates the situation and identifies threats; the threat early warning and decision-making module triggers graded early warning and generates a targeted emergency response scheme; the visual display and interaction module displays information in multiple dimensions and supports query and report generation; and the data storage and tracing module adopts a mixed storage architecture, so that the data security and traceability are ensured. The platform integrates multi-source data and realizes situation accurate perception and intelligent decision by means of an AI technology; the early warning is accurate, the visual interaction is convenient, and the intelligent and efficient level of network security protection is comprehensively improved.

The invention discloses a multi-resource collaborative power system short-time dynamic supply and demand balance evaluation method and device, and the method comprises the steps: constructing a target function based on the power generation cost of an adjustable generator set, the starting and stopping cost of the adjustable generator set, the wind and light abandoning penalty cost, the load shedding cost and the load transfer cost, and determining a corresponding initial constraint condition; determining a prediction error constraint based on meteorological elements, a frequency support constraint of an adjustable generator set and a set fault constraint, carrying out optimization replacement on an initial constraint condition, and giving an optimization constraint condition; based on the objective function and the initial constraint condition, determining a unit commitment start-stop decision; and performing short-time dynamic supply and demand balance evaluation on the power system based on a unit combination start-stop decision in combination with an objective function and optimization constraint adjustment. According to the invention, more accurate and timely information support can be provided for scheduling and operation of a power system, and the short-time supply and demand balance demand and capability in a high-proportion new energy access scene can be effectively evaluated.

The invention discloses an LEO on-orbit real-time precision orbit and clock error determination method and system based on PPP-B2b enhancement, and belongs to the technical field of low-orbit satellite high-precision autonomous orbit determination and clock error estimation. According to the method, enhanced information broadcasted by Beidou No.3 B2b signals is used for correcting a BDS-3 / GPS satellite orbit and clock correction, under the support of the regional BDS-3 / GPS enhanced information, when a new BDS-3 / GPS tracking satellite exists, before measurement updating, the inter-epoch clock correction variable quantity obtained through calculation by using a carrier phase time difference method is used as two orbit determination filtering clock correction parameters for constraint, so that the measurement accuracy is improved. In-orbit real-time separation of receiver clock error and non-difference floating point ambiguity parameters is carried out; and finally, substituting an LEO precision orbit output by orbit determination filtering and a non-difference floating point ambiguity parameter into a phase observation equation to calculate the precision clock error of the BDS-3 / GPS receiver. The method is suitable for the situation that only regional GNSS enhancement information support exists, and the influence of orbital maneuver is small.

The invention relates to a data packet transmission method and device, computer equipment, a computer readable storage medium and a computer program product. The method is applied to a receiver and comprises the steps that under the condition that configuration information of the receiver supports a custom extension header, a first data packet in a sending window is acquired through a transmission channel, and the first data packet carries a serial number and the custom extension header; the user-defined extension head comprises a step length; and under the condition that an out-of-order data packet is received, writing the out-of-order data packet into the corresponding first storage position according to the serial number of the out-of-order data packet, the serial number of the first data packet, the step length and the length of the custom extension head, and returning a confirmation signal of the out-of-order data packet through the transmission channel. By adopting the method, the transmission efficiency of the out-of-order data packet can be improved.

The invention discloses a tunnel surrounding rock multi-source data dynamic fine rapid sensing method, which comprises the following steps: based on a mobile terminal multi-view image sequence, arranging shooting positions according to a preset space interval and an orthogonal angle, generating a sparse point cloud through a motion recovery structure algorithm, and generating a dense point cloud model in combination with multi-view stereo matching optimization; and for the dense point cloud model, delimiting a local neighborhood based on k-nearest neighbor search, resolving a neighborhood point covariance matrix through principal component analysis, extracting a feature vector corresponding to a minimum feature value as a normal vector, and constructing a rock mass surface microscopic geometric feature field. The invention provides a dynamic fine rapid sensing method based on multi-source data, and aims to improve the efficiency, precision and timeliness of tunnel surrounding rock information acquisition and provide accurate surrounding rock information support for tunnel construction and support design.

The invention discloses an intelligent fire-fighting AI collaborative early warning system and method fusing GIS and multi-source data, and relates to the technical field of fire-fighting safety, and the system comprises a GIS space modeling module which is used for constructing a digital twinborn model through integrating a building BIM model, fire-fighting facility distribution, a population density thermodynamic diagram, sensing equipment layout and real-time environment data; the multi-source data fusion module is used for integrating sensing equipment data, real-time environment data, meteorological information, manually reported hidden dangers and a historical fire case library, and outputting the data after standardization processing; the AI collaborative early warning engine module is used for accessing standardized data, realizing building fire dynamic risk assessment and outputting graded warning information; the 3D simulation drilling platform is used for calling the digital twinborn model, receiving graded alarm information and supporting fire spreading simulation, emergency drilling and plan optimization; and the block chain evidence storage module is used for storing alarm information and drill records. According to the invention, risk assessment and accurate prediction of the fire hazard can be realized.

The invention relates to the technical field of electrical fire information analysis and statistics scheme design, in particular to an electrical fire information analysis and statistics method and system based on a knowledge graph. According to the method, through the knowledge credibility evaluation model and the optimization algorithm, the accuracy of knowledge fusion is effectively improved, so that the constructed knowledge graph is more accurate and complete, and electrical fire information analysis and statistics work can be better supported. The introduction of the intelligent inference engine can deeply excavate the potential causal relationship and influence factors of the electrical fire, generates detailed and accurate analysis and statistics results, and provides more comprehensive information support for users. The establishment of a dynamic updating mechanism ensures that the knowledge graph can reflect new electrical fire information and knowledge in real time, the timeliness and effectiveness of the information are always kept, and the practicability and reliability of electrical fire information analysis and statistics are greatly improved.

The invention discloses a heaven and earth integrated multi-domain fused automobile high-level automatic driving system, which realizes more comprehensive and non-blind area sensing and positioning of an automatic driving automobile through multi-domain information fusion of a satellite platform, a cloud platform, an automobile end platform and the like, and promotes comprehensive upgrading of comprehensive efficiency of an intelligent traffic system. Based on cloud error broadcasting and a high and low orbit satellite fusion enhancement technology, the problem of automobile communication loss caused by the fact that single ground communication is limited by base station coverage is solved; based on a cloud reinforcement learning architecture, the communication network stability of the space-ground integrated system is improved through adaptive switching of a communication network; a road semantic map and a decision control experience pool are established based on vehicle high-precision trajectory data collected by a platform, and the limitation of the perception ability of a bicycle is made up through cloud federal learning scene experience sharing; the vehicle end dynamically updates a cloud road semantic map through local map matching; and information support is provided for realizing a chassis multi-domain fusion technology based on high-precision positioning.

The invention discloses a railway engineering unfavorable geology knowledge base construction method and system, and the method comprises the steps: collecting and preprocessing multi-source railway engineering text data, and obtaining a multi-source text data set; performing knowledge extraction, knowledge fusion and knowledge processing based on the multi-source file data set; constructing a railway engineering unfavorable geology knowledge base; and carrying out user interaction design based on a railway unfavorable geology knowledge base. According to the method, unfavorable geological knowledge of railway engineering can be automatically extracted from a large amount of text data, a structured knowledge base is constructed, the knowledge base not only improves the knowledge extraction efficiency and accuracy, but also provides scientific and accurate information support for safety management and decision-making of railway engineering in the form of the knowledge graph, and the method is suitable for popularization and application. Therefore, key fault information can be better mastered for railway operation enterprises, and accurate and effective information data and technical support are provided for decision making.

The invention discloses a behavior recognition method and device based on dynamic context, equipment and a medium, and the method comprises the steps: obtaining a dynamic context graph through cross-modal modeling among multi-modal data, fusing long / short-term events in a monitoring video through dynamic upper and lower graphs, carrying out the cross-modal semantic connection, carrying out the multi-modal feature fusion, and carrying out the multi-modal feature fusion. Determining a gating strategy vector and a gating weight matrix according to a splicing result; and performing multi-modal fusion according to the gating strategy vector, the gating weight matrix and the multi-modal sequence feature to obtain a multi-modal fusion feature, and performing abnormal behavior identification on the monitoring video based on the multi-modal fusion feature. Richer information support is provided for decision making through feature fusion, so that the decision making accuracy in a complex scene is improved. The method can be applied to security and protection monitoring scenes in the financial field or the medical field, so that the abnormal behavior recognition accuracy in the security and protection monitoring scenes is improved.

The invention discloses a knowledge graph construction and application method based on the insurance industry, and belongs to the technical field of industry knowledge graphs. Comprising the following steps: S1, data collection and arrangement; collecting multi-source data of the insurance industry, and sorting the data; s2, knowledge modeling: defining an entity, determining a relationship, and performing attribute setting; s3, constructing a map: performing entity recognition and disambiguation, performing relation extraction, and storing a map database; s4, map optimization: adding semantic information, optimizing a relationship and creating an index; and S5, applying the atlas. According to the invention, multi-source data of the insurance industry is collected, and more comprehensive and accurate information support is provided for insurance business; according to the technical scheme, multiple application methods of the knowledge graph are provided, insurance business links such as risk assessment and management, customer portrait and precision marketing, intelligent customer service and knowledge questions and answers, product design and optimization, claim settlement management and the like are covered, the practical value of the knowledge graph is realized, and the efficiency and effect of each business link can be effectively improved.

The invention discloses an intelligent agent system and a control method thereof, and relates to the technical field of natural language processing. The system comprises an execution layer, a planning layer and an auditing layer, the planning layer identifies and extracts innovation task meta-information, constructs a task tree to complete operations such as hierarchical clustering, and determines a task execution path; the execution layer calculates the semantic similarity between the content of the knowledge graph and the user innovation question, determines the optimal question and answer, extracts heuristic information, and decomposes the heuristic information into sub-questions to construct a dependency graph; generating an answer set based on the graph solving sub-problems, and integrating answers by using a genetic algorithm to obtain an overall solution; and the auditing layer performs multi-dimensional scoring on the scheme, and determines a structured scheme report and optimization suggestions for users to use according to a scoring result. The method has the capabilities of structured reasoning, problem recursive decomposition and scheme closed-loop optimization, can generate a multi-dimensional evaluation result, and efficiently realizes systematic modeling of a clear path for analogy heuristic information support problem solution.

The invention provides a tunnel three-dimensional geologic body modeling method and system based on in-hole camera shooting and while-drilling lithology perception, and relates to the technical field of tunnel and underground engineering and intelligent geological information processing.The method comprises the steps that firstly, a drill hole wall optical image sequence and while-drilling engineering parameters are synchronously collected and preprocessed respectively; then establishing a depth-time mapping relation to realize accurate alignment of the multi-source data in a depth domain; then fracture intelligent identification and parameter extraction are realized through an improved U-Net network, and lithology classification is completed by using an XGBoost model; feature level and decision level fusion is carried out on the fracture features and the lithologic features, and rock mass quality grades are generated; and finally, constructing an integrated geologic model fusing lithologic distribution and a three-dimensional fracture network by adopting an implicit modeling and discrete fracture network technology. According to the method, the problem of splitting of in-hole visual information and while-drilling physical information is solved, automation and precision of geological recognition are improved, and reliable geological information support is provided for tunnel construction safety and support design.

The invention relates to the technical field of blank visual inspection, in particular to a blank defect visual inspection method and system for a plastic extruder, and the method comprises the steps: carrying out the region segmentation of a real-time image, extracting a first-stage defect region, completing the preprocessing, and selecting a specific analysis path according to the defect type. Extracting multi-level defect features and forming a structured feature vector; the reliability degree of each feature is judged through feature integrity judgment and feature quality evaluation, real defects are recognized by adopting multi-stage judgment logic, defect type classification is carried out, and quality influence level multi-stage judgment logic and a branch processing strategy are given, so that accurate detection, classification and analysis of the defects of the plastic extrusion blank are realized. The detection accuracy and adaptability are remarkably improved, the optimal processing path can be automatically selected according to different production conditions and defect types, meanwhile, potential systematic problems are identified through defect correlation analysis, and comprehensive and in-depth information support is provided for quality control.

The invention belongs to the technical field of intelligent mines, and discloses a method and system for improving the precision of a transparent geologic model based on tunneling navigation data elements. According to the method, multi-source data acquisition of tunneling navigation data and advanced detection geological data is carried out, the acquired multi-source data is preprocessed, data formats of different sources are converted into a unified database format, and data storage is carried out; multi-source data fusion is completed; modeling a three-dimensional dynamic geologic model based on a triangulated irregular network-generalized triangular prism model; and iteratively optimizing the obtained three-dimensional dynamic geologic model to obtain a three-dimensional dynamic transparent geologic model, and outputting and visualizing the three-dimensional dynamic transparent geologic model. Through multi-source data fusion and dynamic modeling, the spatial precision and the real-time response capability of the model are improved, and more reliable geological information support is provided for rapid tunneling of a coal mine.

The invention discloses a distributed photovoltaic optimization coordination control system and method, and relates to the technical field of distributed photovoltaic power generation, and the control system comprises a multi-dimensional data collection module, a self-adaptive cluster division module, a robust dominant node election module, a three-dimensional voltage state evaluation module, and a hierarchical coordination control execution module. According to the distributed photovoltaic optimization coordination control system and method, real-time operation data, meteorological prediction data and power grid load prediction data of each node are continuously monitored, comprehensive information support is provided for a control strategy, and when it is detected that voltage abnormity is caused by sudden change of illumination intensity in a certain area, the real-time operation data of each node, meteorological prediction data and power grid load prediction data are monitored. And immediately finishing cluster structure adjustment in an extremely short time by adopting a fuzzy clustering algorithm with constraint conditions based on the electrical distance and the voltage fluctuation trend characteristic value, and ensuring that the node voltage change characteristics in the same cluster are highly consistent.

The invention provides a cultural field-oriented knowledge graph space-time map display method, which comprises the following steps of: extracting culture entities and relationships thereof from multi-source heterogeneous data through a knowledge graph construction module, and constructing a structured knowledge graph; analyzing and normalizing the time and space information of the culture entity through a space-time processing module; through a map display module, displaying the processed culture entity and the time-space relationship thereof on a user terminal in a map form; through the interaction module, interaction operation between the user and the knowledge graph displayed in the map is achieved, and the user can more conveniently explore culture information; the method supports the display of multi-level cultural relationships, can effectively extract and display target information in a complex cultural network, has good applicability, can be widely applied to the fields of cultural heritage, historical research, archaeological research and the like, and enables cultural entities and relationships thereof to be more visually and dynamically presented in front of users.

The invention relates to the technical field of ship energy consumption prediction, and discloses a ship energy consumption interval prediction method and system based on a Gaussian quantile regression model.The method comprises the steps that firstly, a ship navigation historical data set is preprocessed, a model input feature set is screened, a Gaussian process quantile regression model with a radial basis function as a kernel is constructed, and hyper-parameters are optimized; and after the prediction performance of the subset evaluation point is verified through the model, an upper quantile prediction model and a lower quantile prediction model are respectively established according to a target confidence level, and finally a prediction interval is synchronously output and an evaluation report is generated. According to the method, through combination of Gaussian process processing nonlinear relation and quantile regression estimation condition distribution, high-precision point prediction is provided, meanwhile, prediction uncertainty can be quantized, an energy consumption prediction interval corresponding to a target confidence level is output, and more comprehensive and reliable information support is provided for ship energy efficiency management and operation decision making.