649 results about "Schematic maps" patented technology

The invention provides an electronic clinical medical assessment method and system for an ophthalmology diagnosis and treatment scheme, and relates to the technical field of medical information, and the method comprises the steps: 1, carrying out the multi-scale edge detection calculation of an input ophthalmology image-text mixed medical record image, and obtaining a medical record image; the method comprises the following steps: extracting a boundary contour of a text labeling area and a hand-drawn lesion schematic diagram through adaptive threshold segmentation and morphological closed operation, and establishing a coordinate mapping table containing text block circumscribed rectangular coordinates, geometric positions of key anatomical mark points of the schematic diagram and symbol spacing characteristics; 2, constructing a two-channel attention gating network based on the coordinate mapping table, fusing the semantic features of the text region and the morphological features of the schematic diagram through a dynamic weight distribution strategy, and generating a multi-modal fusion feature matrix with a spatial alignment relationship; according to the method, through multi-modal feature fusion, triangular verification region confidence regulation and control and three-dimensional topology modeling, analysis and structured output of ophthalmology image-text medical records are realized, and the spatial alignment of diagnosis and treatment information is improved.

The invention provides an equipment fatigue crack intelligent detection method and system based on deep learning, and the method comprises the steps: firstly obtaining an equipment surface detection image set, generating a first crack detection thermodynamic diagram through a pre-trained deep learning model, and constructing a crack physical expansion constraint model according to equipment design material parameters and real-time operation condition parameters, then performing crack area iterative optimization based on the first crack detection thermodynamic diagram and the crack physical expansion constraint model to obtain a second crack detection thermodynamic diagram, and analyzing the second crack detection thermodynamic diagram to determine equipment surface crack state parameters such as crack area boundary coordinates, crack expansion direction vectors and crack depth gradient values; and finally, generating an equipment fatigue crack intelligent detection report containing a crack space distribution schematic diagram and a crack propagation risk grade identifier, thereby integrating image data and physical constraints, and improving the accuracy and reliability of crack detection.

The invention belongs to an aircraft wire harness design technology, and relates to a digital and automatic collaborative design simulation method for aircraft wire harnesses based on Capal and CATIA. According to the method, an existing boundary data model is utilized, electrical parts are installed on CATIA software, and wiring harness arrangement environment conditions are created; creating a three-dimensional wire harness model in the CATIA software; establishing a Capal graphic symbol library and a wire harness part library; creating an aircraft electrical wiring diagram on the Capital software by using the graphic symbol library and the wiring harness part library file; in combination with a CATIA three-dimensional wiring harness model, interactive design is carried out with flight Capital software, and an aircraft two-dimensional topological graph is formed; the sectional area of the wire harness is automatically calculated through CATIA software, and an aircraft simulation three-dimensional wire harness is formed; and combining the aircraft simulation three-dimensional wiring harness with the aircraft topological graph and the aircraft wiring harness two-dimensional graph design to form an aircraft two-dimensional wiring harness chart diagram. According to the invention, database management informatization, three-dimensional wiring harness design digitalization, two-dimensional electrical system principle design and three-dimensional electrical wiring harness model interaction design automation are realized.

The invention discloses a new energy equipment troubleshooting method based on a knowledge graph and a large model. The method is used for solving the problems of fault positioning and troubleshooting of photovoltaic and wind power new energy equipment and the like. The method mainly comprises the following steps: performing data cleaning and preprocessing on a new energy equipment troubleshooting professional field document, and constructing a structured knowledge graph of equipment types, fault types, fault information and solution nodes in a graph database through Cypher; the big language model analyzes the user fault description, extracts and maps node attributes in the knowledge graph, and generates a graph query statement; the question-tracing type multi-round interaction is realized, the missing information is dynamically complemented, and the basic fault is accurately positioned in a step-by-step reasoning mode; according to the method, multi-modal resources such as texts, schematic diagrams and videos stored in the knowledge graph are combined, a step-by-step reasoning path and a solution with illustrative features are generated through a preset template, the whole reasoning process is visualized in a branch thinking graph form, and the accuracy, interpretability and user experience of troubleshooting are remarkably improved.

The invention discloses an integral equation general solution method for horizontal bearing characteristics of a pile body composite foundation, which comprises the following steps of: S1, establishing a pile body composite foundation schematic diagram consisting of N (N = n1 * n2) foundation piles and a coordinate system {0, x, y, z} thereof, and dividing the pile body composite foundation schematic diagram into m subunits by taking a pile diameter d as a side length; determining the load resultant force V (y, 0) of the top of each subunit according to the horizontal load H0 of the upper structure borne by the foundation; s2, the pile-soil system is decomposed into semi-infinite space expansion soil and virtual pile units, and stress analysis schematic diagrams of the corresponding units are obtained; obtaining analytic expressions of pile body deflection # imgabs0 # and bending moment # imgabs1 # according to static equilibrium conditions and geometric conditions of the ith (i = 1,..., N) virtual pile unit; and S5, the lateral displacement # imgabs2 # of the extended soil unit at the corresponding position of the ith virtual pile is obtained based on the Mindlin solution, according to the lateral displacement coordination condition of the semi-infinite space extended soil and the virtual pile unit at the corresponding position, an integral control equation of the horizontal bearing characteristic of the pile body composite foundation is established, and then the pile body deflection and the internal force of the pile body composite foundation are obtained.

The invention discloses a material supply and resource recovery collaborative scheduling method and system, and belongs to the technical field of logistics scheduling, and the method comprises the steps: obtaining a material supply instruction and a garbage recovery instruction, carrying out the image recognition of a building garbage picture, obtaining the garbage attribute, and generating a demand instruction library; the method comprises the following steps: establishing a feature knowledge base, setting a spatial clustering method, carrying out spatial clustering and time window screening, carrying out geographic coordinate analysis and time sequence sorting on material demand points and recovery points, generating an initial task pool, setting a loading matching method, and generating a material supply and recovery loading schematic diagram according to building material and garbage attributes; a circulation path is planned, a path planning method is set, an ant colony algorithm is used for initial path planning, a monitoring feedback method is set, data are returned in real time, the running state of the vehicle is monitored, and an alarm is given out immediately once abnormity is found; and the sorted and regenerated aggregate data is synchronized to a building material database, a resource feedback method is set, a reverse transportation task is identified, and a material supply and resource recovery closed loop is formed.

The invention discloses a large model enhanced equipment operation and maintenance multi-modal knowledge graph construction method, which comprises the following steps of: firstly, introducing QWEN-VL into a double-flow Transform architecture, realizing dynamic alignment of an image and a text, supplementing few-sample semantics, and improving the identification precision of a part and problem entity relationship in the field of operation and maintenance; secondly, an MT-Transform module is provided, cross-modal time sequence embedding fusion is realized through fusion causal, expansion convolution and memory slot mechanisms, and the association continuity of new and old parts and causal chain embedding precision are improved; then, designing a multi-modal dynamic weight attention guiding module, introducing a weight key value to guide attention focus points, fusing schematic diagrams and text features, and improving entity relationship modeling precision of parts and faults; and finally, the marked image embedding and position embedding are fused into RoBERTa feature embedding, MNER and MRE tasks are completed in combination with CRF and SOFTMAX, and multi-modal operation and maintenance atlas construction is realized. The invention further provides a large-model-enhanced equipment operation and maintenance multi-modal knowledge graph construction system and a storage medium.

The embodiment of the invention relates to the field of large language models and multi-agents, and provides a multi-agent collaborative query response method based on a state dependency graph and a related device, and the method comprises the following steps: receiving a to-be-queried text input by a user; performing query semantic analysis on the to-be-queried text to obtain the analyzed to-be-queried text and query complexity; instructing the intention recognition agent to generate a domain index; calling a preference matching agent to generate preference information; calling a resource retrieval agent to query to obtain query use resource information corresponding to the to-be-queried text according to the query complexity; the query response information is generated at least according to the historical context of the to-be-queried text, the to-be-queried text, the analyzed to-be-queried text, the field structure information, the field index, the preference information and the query use resource information, and the personalized service corresponding to the to-be-queried text currently input by the user can be automatically adapted according to the actual interaction scene; and response type and high-efficiency intelligent assistance is realized.

The invention relates to the technical field of breach image processing, in particular to a breach rapid situation awareness method and system based on multi-source data. The method comprises the following steps: acquiring dam monitoring station data; performing hydrological sensor network setting on the dam monitoring station data to obtain dam hydrological sensor network data; performing ultrasonic water level change trend analysis on the dam hydrological sensor network data to generate an ultrasonic water level change trend chart; performing breach node sensing on the dam hydrological sensor network data according to the ultrasonic water level change trend chart to generate breach node data and breach prediction node data; and according to the breach node data, macroscopic disaster risk analysis is carried out on the breach area, and a breach area macroscopic disaster risk schematic diagram is generated. According to the invention, through real-time data integration, comprehensive risk assessment, unmanned aerial vehicle monitoring, dynamic prediction model and multi-party cooperative response, the accuracy and response speed of breach rapid situation awareness are improved.

The invention discloses a wafer positioning MAP positioning marking method, which comprises the following steps of: firstly, establishing a system coordinate system based on a pixel point drawing frame, generating a schematic diagram of a to-be-detected wafer in the system coordinate system according to information of the to-be-detected wafer, and acquiring system coordinates of each crystal grain in the system coordinate system; then any crystal grain is selected from the system coordinate system to serve as a benchmarking crystal grain, and benchmarking of the position of the benchmarking crystal grain in the system coordinate system and the actual position is completed; the appearances of all crystal grains are checked through an observation lens, when abnormal crystal grains are found, the displacement distances of the observation lens in the X-axis direction and the Y-axis direction are obtained, and the coordinates of the abnormal crystal grains in the system coordinate system are calculated; and finally, abnormal marking is performed on the abnormal crystal grains in the system coordinate system, and a corresponding marked wafer MAP is generated. According to the invention, the crystal grains are inspected through the artificial lens, and abnormal marking is carried out through the system after the defective products are found, so that the marking accuracy and marking efficiency of the defective products are greatly improved.

The invention discloses an intelligent chart generation method and system suitable for multi-modal data and a storage medium, and the method comprises the steps: receiving and preprocessing the multi-modal data, and completing user intention type recognition and task routing; selecting an adaptive model according to a routing result, and constructing and generating a cue word; standardizing an initial graph code output by the model into an intermediate representation format containing a metadata field, converting the intermediate representation format into a graph code compatible with a target platform, and reserving node definition, a connection relation, layout constraint and metadata information; the method comprises the following steps: respectively completing chart type identification and layout strategy determination, node format size adjustment, overall layout alignment correction and partition adjustment, and connection line identifier optimization through four optimization components, and rendering and outputting a chart. The problem that due to the fact that an existing model lacks a special optimizing and processing mechanism for the structured chart, the effect is remarkably poor when a professional schematic chart needing an accurate logic structure and geometric constraints is generated is solved.

The invention discloses an analog IC synchronization test optimization method and system based on crosstalk simulation. The method comprises the following steps: firstly, acquiring position layout data and test signal data of each analog IC in a synchronous test process of the analog ICs, determining electromagnetic crosstalk information by combining test signals, and constructing a crosstalk schematic diagram according to the electromagnetic crosstalk information and the position layout data; clustering the schematic diagrams by using a spectral clustering algorithm, and identifying a crosstalk path in the synchronization test; designing an electromagnetic crosstalk signal isolation barrier based on the schematic diagram and the crosstalk path, deploying the electromagnetic crosstalk signal isolation barrier in a test environment, performing simulation evaluation on an independently tested analog IC by constructing and injecting a crosstalk simulation signal, and judging an isolation effect; and optimizing the isolation barrier according to an evaluation result to obtain an optimization scheme. According to the method, the electromagnetic crosstalk path in the synchronous test process can be effectively identified and isolated, and the accuracy and reliability of the simulation IC test are improved.

The invention discloses a ChatGPT-python programming method, particularly relates to the field of artificial intelligence, and comprises three steps of problem definition, algorithm design and code implementation. According to the method, project situations are described in detail through question definition, and ChatGPT is guided to generate project schematic diagrams; through a design algorithm, a calculation problem is elaborated, and ChatGPT is required to provide an effective solution; by implementing codes, generating a feasible programming solution according to a calculation theory, providing intelligent suggestions in each process, ensuring theoretical accuracy and engineering feasibility of a result through manual examination, and comparing by taking three-dimensional slope stability analysis as a case and combining with a calculation result of commercial software, a calculation result of the three-dimensional slope stability analysis is obtained. It is verified that the Python algorithm obtained through ChatGPT programming has good calculation precision, an innovative auxiliary means is provided for engineering calculation, and the huge application prospect of artificial intelligence in the field of civil engineering is shown.

The invention discloses a blasting vibration monitoring method and system based on vision and vibration sensors, and relates to the technical field of blasting vibration monitoring. An aerial vision monitoring device is arranged at a set height right above a blasting point, and a vibration sensor array is radially arranged around the blasting point; and the visual monitoring device and the vibration sensor array are in wireless communication connection with the blasting vibration analysis module based on the computer. Omnibearing monitoring of the blasting process is achieved by combining the aerial vision monitoring device and the ground vibration sensor array, ground vibration data can be captured, and the scattering condition of fragments generated by explosion can be observed. An image feature recognition algorithm is used for analyzing an image captured by a high-speed camera, and visual evidence is provided for understanding the explosion effect. Complex vibration data and visual feature changes can be converted into charts and schematic diagrams which are easy to understand through image processing software and a data visualization tool, and non-professionals can conveniently and rapidly grasp key information.

The invention relates to the technical field of geological disaster hidden danger recognition, in particular to a geological disaster hidden danger recognition method based on InSAR and semi-supervised learning, which comprises the steps of dividing hydrological sensitivity of a monitoring area according to a regional underground water unit supply schematic diagram, and setting an InSAR data sampling frequency; acquiring earth surface time sequence displacement data, including accumulated displacement, displacement rate and displacement acceleration, by using a set sampling frequency for preliminarily identifying a potential hidden danger area; geological radar detection is carried out in the potential hidden danger area, underground structure features are evaluated through a geological radar profile map, and a multi-source feature vector is constructed; according to the method, the hydrological sensitivity of the monitoring area is divided according to the regional groundwater unit supply schematic diagram, and the InSAR data sampling frequency is set, so that the problem that the high-risk area is not monitored in time due to the fact that the hydrological sensitivity change is not considered because the conventional monitoring frequency mostly adopts a fixed sampling interval is solved.

Tracked mobile X-ray imaging equipment is used to produce single or stereo long calibrated views of the anatomy of a patient on the operating table. The system estimates the position and orientation of the anatomical planes, virtually places measurement grids over these reference planes, and transforms any radiographic views taking by the X-ray imaging system onto these calibrated planes. The system may apply information about the depth of the anatomy to remove parallax artifacts. This system enables displaying and evaluation of the entire radiographic length of the anatomical planes using a mobile X-ray equipment. It also provides a platform for overlaying the real time X-ray images taken during operation with radiographic images of the patient or schematic of the surgical plan developed before the surgery for quick evaluation of a surgical plan.

The invention discloses a controllable schematic diagram generation method and system based on a large language model and a storage medium. The method comprises the steps of constructing a schematic diagram generation task data set based on the large language model; pre-establishing a layout planning rule of the schematic diagram according to the image characteristics of the schematic diagram, and converting a schematic diagram generation task data set based on the large language model into a schematic diagram of a set layout through the layout planning rule of the schematic diagram; serializing the layout planning rule of the schematic diagram, converting the layout planning rule into a text expression form, and positioning an application area of the layout planning rule of the text expression form in the image; and optimizing a serialization processing process and an image generation process according to an application area of the layout planning rule in the image in combination with a multi-mode embedded representation and fine-tuning diffusion model, and generating a schematic diagram meeting the requirement. According to the method, challenges of high-level semantic complexity and bottom-layer visual diversity in the schematic diagram generation process can be effectively coped, and the overall quality of a schematic diagram understanding technology is improved.

The invention discloses a cable crane management and control method and system based on digital twinning, and relates to the technical field of bridge construction intelligent monitoring, and the method comprises the following steps: preprocessing different types of monitoring data to obtain different types of preprocessed monitoring data; constructing a twinborn model based on the on-site live-action data, and performing real-time rendering based on the preprocessed monitoring data to construct a real-time twinborn model; based on the real-time twinborn model, constructing an AR auxiliary hoisting schematic diagram; and planning an optimal path of the crown block based on the AR auxiliary hoisting schematic diagram. Through multi-source data acquisition, real-time analysis, safety early warning and visual display, comprehensive monitoring and risk pre-control of the operation state of the cable crane are realized.

[Problem] In assessing whether a statement is true or false, it is desirable to make an assessment for the entirety of a document rather than a portion thereof. It is also said that the truth or falsehood of a statement depends on context. There is a method referred to as "surrounding context". However, this method is not for entire documents. [Solution] Accordingly, a "global context" is proposed. Any given bundle of conjunctively joined statements is defined as a unit context. A global context is defined when a conjunction of unit contexts continues from the beginning to the end of a document. In the hypothetical case where a statement "p" and its negation "￢p" are latent within this global context, it can be said that the global context "p∧,, ∧￢p∧" is a contradiction. FIG. 6 is a schematic diagram of sentence context. In the diagram, (α)-(γ) are individual global contexts. Also, (a)-(e) are unit contexts. U1, U2, and so on are unit statements. A conjunction of unit statements is a unit context, and a conjunction of unit contexts is an individual global context. A connotation such as (b) also constitutes a conjunction. If "p" and "￢p" are in different unit contexts, there is no contradiction.

1. Name of the design product: Eyelash brush (A07). 2. Use of the design product: For applying makeup to the eyelashes of the eyes. 3. Design key points of the design product: Lies in the shape. 4. Picture or photo that best shows the design key points: Perspective view 1. 5. Other situations that need to be explained: The enlarged top view is an enlarged schematic diagram of the top view, and the enlarged bottom view is an enlarged schematic diagram of the bottom view.

Systems, methods and / or interfaces are provided for generating interior design options. In some implementations, the method includes obtaining an inspiration image of a portion of a room, a furniture, fixture and equipment, or a combination. The method also includes parsing the image, including segmenting the inspiration image into sub-images corresponding to each furniture, fixture or equipment. The method also include identifying alternatives based on the sub-images and a layout of the room, including coordinating the alternatives with respect to each other and coordinating the alternatives with respect to the room. The method also includes generating and / or displaying variations of the room with images corresponding to the alternatives. In some implementations, the method includes parsing an image to generate an empty room sketch or schematic, generating alternatives to be placed in the empty room according to the room, and generating and / or displaying a visualization by placing the alternatives in the room.

The method involves obtaining input data that includes: (i) railway mapping data, (ii) clearance data for the railways, (iii) schematic (preferably image) data related to the load being transported, and (iv) the transport's origin and destination. Using this data, one or more artificial intelligence (AI) models determine dimensional parameters of the load by processing the schematic image. A transport envelope for the load is defined based on these parameters. The railways connecting the origin and destination are identified, the probability of the transport envelope clearing clearance data on those railways is determined. Based on these probabilities, at least one viable route is determined across the railways connecting the origin to the destination.

The invention relates to the technical field of six-degree-of-freedom mechanical arm control, in particular to a six-degree-of-freedom mechanical arm control method and system. The method comprises the following steps: obtaining an assembly schematic diagram, carrying out multi-machine cooperation process analysis, and collecting the vibration frequency of a vehicle body structure by using an acoustic emission sensor; thirdly, vibration impact force disorder of the connection interface is simulated through the vibration frequency, pre-tightening force misalignment regression analysis is carried out, and therefore fatigue fracture failure of the connection structure is predicted; then, based on regression data and a prediction result, torque-angle compound control of the six-degree-of-freedom mechanical arm is implemented, and iteration is carried out; and finally, control firmware is designed and embedded into the mechanical arm, and precise control is executed. Through optimization processing of the six-degree-of-freedom mechanical arm control technology, the six-degree-of-freedom mechanical arm control technology is more perfect.

The invention relates to the technical field of electro-pneumatic valve state monitoring, in particular to a state monitoring and alarming method for an electro-pneumatic valve. The method comprises the steps of formulating a knowledge graph updating simulation schematic diagram, and updating association states of various state characteristics and fault types under different time nodes in real time; and predicting the fault type of the current electro-pneumatic valve according to the state characteristics acquired in real time and the updated mapping knowledge domain. According to the method, the knowledge graph updating simulation schematic diagram is formulated, the association state of each state feature and the fault type under different time nodes is updated in real time, the fault matching quantity and the change rate are used as association degree evaluation items of each state feature and the fault type, the relationship between each state feature and the fault type is accurately described, and the fault diagnosis accuracy is improved. A stable knowledge graph is established, the alarm degree is divided according to the predicted fault type and the dynamic association and grade of the current fault type and the state characteristics, early warning is performed according to the alarm degree, and the early warning effect is improved.

1. Name of the Design Product: Electric Push Rod (Six). 2. Use of the Design Product: Used to push and pull various industrial machines or various industrial equipment in a linear reciprocating motion manner. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: Perspective View 1. 5. Other Situations Requiring Explanation: Other Explanation: The reference drawing is a schematic diagram of the electric push rod of this design with a transmission line provided at the neck.

The invention discloses an AUV (Autonomous Underwater Vehicle) multi-target global path planning method based on a sparrow search algorithm in the field of artificial intelligence and ocean engineering, and the method comprises the following steps: S1, constructing a multi-target optimization model with path length and path safety as the core, and reducing the total length of a path as much as possible while ensuring that the path avoids an obstacle, therefore, a short and safe path is found; s2, determining constraint conditions of path search of the AUV in a complex static environment formed by a plurality of obstacles; s3, solving the multi-objective optimization model established in the step S1 by using a sparrow search strategy; s4, after the algorithm converges, outputting an optimal solution, and drawing an obstacle avoidance 3D schematic diagram and a Pareto frontier map in AUV path planning according to the optimal solution; according to the invention, by improving the sparrow search algorithm and introducing an obstacle avoidance mechanism, the problem of path optimization in a complex underwater environment can be effectively solved, and the navigation efficiency of the AUV and the reliability of task completion are improved.

The invention relates to an AI-driven system for data analytics, processing, mining, and user interaction, utilizing large language models (LLMs) and machine learning (ML) techniques. The system enables personalized, real-time access to company data, guided by AI Agents. These Agents handle tasks such as data extraction, transformation, and loading, with a multi-stage processing pipeline that includes raw data ingestion, curation, and modeling. Specialized Agents like Fixing and Modeling Agents ensure data quality, analysis, and visualization. The system also integrates with BI dashboards for generating insights and predictive analytics. Users interact via natural language queries (NLQs) to receive context-aware, AI-generated answers, including various types of plots, graphs and charts, thus improving decision-making and data management efficiency.

Techniques are disclosed for the design and modeling of a low-voltage system or network. The low-voltage system is currently or prospectively deployed in a building / site. For this purpose, a schematic diagram and a corresponding 3D model are created for the low-voltage network. The schematic diagram is integrated with the 3D model. As a result, the latter is fully aware of the choices of low-voltage devices, port configurations, connections between the exact ports of the devices and the cable-types for the connections for the low-voltage system being designed. This leads to a number of advantages for the designers / modelers of low-voltage systems. The system can also calculate voltage-drops in connections as well as potential overload conditions. Such error detection capabilities allow the user to take proactive actions at the design stage of the low-voltage system in order to circumvent problems during its operation and after deployment.

The invention discloses a port shipping traffic volume analysis and prediction method. The method comprises the following steps: S1, constructing a port zoning map; s2, acquiring ship comprehensive information data, performing classification statistics on port entering and leaving ships of each port according to a preset ship classification rule, generating information lists of various types of port entering and leaving ships of each port, and marking latest positions, historical driving tracks and historical attachment positions of the ships based on the port zoning map; s3, screening different ship types through the ship information list, and analyzing ship operation behaviors and efficiency indexes; and S4, on the basis of the port zoning map marked in the step S2 and the ship operation behaviors and efficiency indexes in the step S3, predicting the next to-be-arrived position and the future navigation trajectory of the ship, and constructing a to-be-arrived ship schematic diagram of each port.

The invention discloses a water conservancy safety monitoring system and method based on dynamic vision, and relates to the field of water conservancy monitoring, and the system comprises a multi-view dynamic vision collection module, an image preprocessing and feature extraction unit, a data fusion and analysis module, and an early warning decision module. According to the invention, a three-dimensional monitoring network is constructed through the multi-view dynamic visual acquisition module, and equipment parameters are dynamically adjusted in combination with real-time meteorological data, so that all-directional dead-corner-free monitoring is realized; the image preprocessing precision and the feature extraction accuracy are improved by using wavelet transform and a deep learning algorithm, and the hidden danger is accurately positioned by combining space-time correlation analysis and an image neural network; an early warning threshold is dynamically optimized through a gradient descent algorithm, a risk trend is predicted based on an LSTM model, early warning information containing three-dimensional coordinates and a dynamic schematic diagram is generated, and decision suggestions are optimized by means of case reasoning and a genetic algorithm.