35results about How to "Reduce blindness" patented technology

This application relates to the field of IoT detection technology, specifically to an online accuracy detection method for filling machines using multi-sensor fusion. The method includes: collecting multi-source heterogeneous sensor signals from the filling machine head and adding consistent timestamps based on business events; reconstructing a two-dimensional event matrix using the cumulative mass flow corresponding to the flow signal as the progress coordinate, locating progress anchor points, and defining a transient window; within the transient window, performing adaptive cancellation on the weighing signal using the pressure signal as a reference to obtain a steady-state weighing value, performing dynamic density correction on the flow signal using temperature and pressure signals to obtain a flow integral value, and performing dynamic weight fusion based on the real-time signal-to-noise ratio to obtain a fused output value; using the fused output value at the end of the transient window for qualification judgment and source tracing to generate a traceability tag, and combining the final filling quality detection value to generate an accuracy data package for online detection. This application effectively improves the metrological robustness of the final filling value under valve-closing transients and enhances the traceability of the detection.

The invention relates to the field of intelligent operation and maintenance of power equipment, in particular to a transformer maintenance-free respirator control method integrating temperature, humidity and pressure monitoring and electric heating regeneration and a storage medium. The method comprises the following steps: firstly, deploying a sensor in the respirator, collecting humidity and internal temperature and pressure data of a drying agent, and obtaining accurate data after moving average filtering and temperature compensation; and the control module is combined with the data, a humidity threshold value dynamically adjusted along with the load rate of the transformer and a regeneration period to trigger the regeneration system to start. During regeneration, the electric heating piece heats the drying agent, the fan adjusts the rotating speed according to the real-time temperature and humidity to discharge steam, meanwhile, the moisture absorption capacity recovery rate is corrected by combining aging of the drying agent, and starting and stopping or temperature adjusting delay are conducted according to the standard condition. The process data is uploaded to the operation and maintenance cloud platform through the LoRa module encrypted by AES-128, and the platform analyzes the trend through weighted linear regression and gives an alarm; and operation and maintenance personnel optimize parameters according to the parameters and regurgitate a judgment link. Related programs are stored in the storage medium and can be executed by the processor to achieve the method, and support is provided for maintenance-free of the respirator.

This invention discloses a well placement method, equipment, and storage medium for bioherm-type carbonate reservoirs. The well placement method includes the following steps: S1. Obtaining the amplitude spectrum data of the reservoir to be well placed; S2. Classifying the bioherm type and reservoir category, and determining the connectivity of the reservoir; S3. Determining the optimal well placement area and optimal well placement pattern based on the determined bioherm type, reservoir category, and reservoir connectivity; S4. Performing economic calculations on the wells to be placed within the optimal well placement area, establishing an economic model, and determining the optimal well spacing d. i And the optimal number of oil and gas wells N i This method, tailored to the characteristics of bioherm-type carbonate reservoirs, classifies them into different types, distribution ranges, and connectivity, providing a reliable reference for well placement. It designs optimal well placement areas and patterns, effectively improving well development efficiency. An economic model is established through economic accounting to optimize well spacing and the number of oil and gas wells, thereby increasing reservoir development utilization and economic benefits.

The application is named reservoir scale intelligent optimization demonstration system and method based on multi-target risk coupling, and belongs to the technical field of intelligent decision-making of water conservancy and hydropower engineering. The technical problem to be solved is that the traditional reservoir scale demonstration relies on static scenarios, cannot quantize the multi-target conflict coupling relationship, does not systematically consider multiple uncertainties and risks, has low optimization efficiency and insufficient scheme robustness. The technical solution points are that the application sets six modules of hydrological risk modeling, multi-target coupling analysis, scale optimization decision, uncertainty propagation simulation, comprehensive resilience evaluation and intelligent demonstration integration, generates dynamic hydrological risk indexes by fusing climate scenarios and historical data, quantizes the multi-target coupling relationship, optimizes the reservoir scale parameters by combining reinforcement learning and risk constraint, and automatically generates the optimal reservoir scale demonstration scheme with high robustness through uncertainty simulation and resilience evaluation.

The invention relates to the technical field of knowledge maps, and particularly discloses a knowledge map-based intelligent travel visualization method, which comprises the following steps of: presetting an initial period, calculating a crowding coefficient, dynamically rolling and updating the period, and setting an interval threshold value at the same time; accessing a scenic area API to obtain data, and periodically calculating the popularity of each scenic spot through a weighting formula; based on the new period and the scenic spot density threshold, dividing congestion levels, and drawing a red-yellow-green three-color thermodynamic diagram; screening surrounding scenic spots based on user coordinates, and recommending according to popularity ranking; and constructing a city 3D tourist map to associate the scenic spot popularity. According to the method, the real-time performance of data is guaranteed through dynamic periodic updating, a thermodynamic diagram is generated through multi-dimensional data to realize passenger flow visualization, low-congestion and high-heat scenic spots are recommended in combination with user coordinates, and optimization mechanisms such as 3D map linkage are supplemented, so that the management efficiency and the tourist experience are improved, and text travel management is promoted to be transformed into data driving.

This application provides a core-shell structure microwave absorbing material and its thickness optimization design method and application, relating to the field of electromagnetic wave absorbing materials technology. The core-shell structure microwave absorbing material comprises a sheet-like magnetic metal core and a silica shell covering the core, the silica shell being prepared via a sol-gel method. The optimization design method includes: obtaining the intrinsic electromagnetic parameters of the constituent materials; constructing a single-particle simulation model with shell thickness as the variable; calibrating the simulation parameters through a decoupling-testing-verification iterative process; optimizing the solution for the optimal thickness based on the calibration model with the goal of maximizing the effective absorption bandwidth of reflection loss; and finally determining the optimal thickness range through experimental verification. This application achieves synergistic optimization of microwave absorption performance and corrosion resistance, solving the problems of long development cycles and high costs associated with traditional trial-and-error methods. The designed core-shell structure microwave absorbing material can be widely used in fields such as electronic equipment shielding, stealth technology, and microwave anechoic chambers.

The application relates to a detection and communication integrated identification method for instantaneous permanent fault of a power collection line by means of IIDG active energy injection, and belongs to the technical field of power system relay protection and automation. The method comprises the following steps: after a fault occurs in a power collection line, starting an IIDG with network construction capability, realizing zero starting voltage rise through VF control, establishing a characteristic voltage, judging whether a composite voltage criterion is met, if yes, the fault is permanent, and the injection source exits after maintaining a constant frequency transmission; if not, the fault is instantaneous, and the injection source sends a frequency shift information after a time delay. Voltage is continuously monitored during the injection, and whether a complete frequency shift signal is received is determined through a frequency variance criterion and data segment correlation. If the voltage does not meet the composite voltage criterion during the detection process and the complete frequency shift signal is received, reclosing is allowed after power loss again, otherwise, reclosing is locked. The method aims to solve the technical problem that the fault nature of the power collection line under a voltage loss condition is difficult to identify in the prior art.

This invention relates to a method for optimizing the tubing size of injection and production wells in a water-driven sandstone oil and gas reservoir, comprising the following steps: 1. Determine the coefficients A and B of the binomial production capacity equation for the gas well and establish the production capacity equation. 2. Analyze and determine the critical sand production pressure difference during gas production in the target gas reservoir's injection and production wells. 3. Establish a binomial function relationship between formation pressure and cumulative gas production. 4. Calculate the formation pressure during the peak winter gas production period of the target gas reservoir based on the established binomial function relationship. 5. Use nodal analysis to perform dynamic modeling and calculate the production capacity of different tubing sizes under different formation pressures and production pressure differences. 6. Based on the production capacity under peak formation pressure, use cross-plots to quantitatively optimize the tubing size with a production capacity increase of 10% and a critical sand production pressure difference of less than 3 MPa. This significantly reduces the blind selection of tubing and ensures the gas supply capacity and reliability of the gas reservoir during the critical peak-shaving period.

The invention discloses an endangered plant phoebe hainanensis identification and systematic monitoring method based on multi-source data fusion, and belongs to the technical field of endangered plant protection. According to the method, a potential distribution area is delineated through a species distribution model, individual accurate identification and filing are achieved through a multi-branch feature fusion model, multi-scale growth and microenvironment data are collected through Internet of Things nodes, and finally a'discovery-identification-monitoring-protection 'whole-process closed loop is formed through a unified data management platform. According to the method, phenological feature extraction, transfer learning modeling, man-machine collaborative verification and low-power-consumption Internet of Things monitoring technologies are adopted, and the problems that a traditional method is low in efficiency, insufficient in recognition precision and fragmented in monitoring are solved. According to the method, efficient discovery, accurate identification and long-term dynamic monitoring of the wild population of the phoebe hainanensis are achieved, scientific support is provided for protection decision making, and the method is convenient to operate and high in practicability and has protection value and application prospects.

This invention provides a collaborative control system and method for urban lake stormwater and flood control, relating to the field of flood management. The system and method utilize a multi-source heterogeneous information fusion system, collecting and standardizing multi-dimensional data such as quantitative precipitation forecasts, hydrology, urban flooding, and water quality to construct a unified data lake. This achieves high-precision, multi-dimensional information perception, providing comprehensive and high-quality data support for control decisions. It addresses the problems of incomplete information perception and inconsistent data standards in existing technologies. Furthermore, it establishes a dynamic risk assessment model integrating flood control, ecological water quality, social, and water resource utilization risks. Risk indicators serve as both hard constraints and soft costs in scheme comparison, enabling quantitative assessment and control of multiple risks. This allows decision-makers to clearly understand the potential risks of different schemes, significantly reducing the blindness of decision-making and improving the safety of control schemes.

The invention relates to the technical field of electric power computing power scheduling, and discloses an electric power cross-domain computing power elastic scaling scheduling system supporting a creative GPU (Graphics Processing Unit). The system receives a power cross-domain computing power scheduling request, and searches a matched historical computing power use record set from a historical computing power database according to the request. And carrying out load category division on the historical record set to generate historical computing power record subsets of a plurality of load categories. Computing power feature core calculation is performed on the subsets to obtain a plurality of computing power feature core points and associated time intervals; and using the associated time intervals as the time range of a plurality of scheduling analysis layers, performing multi-scale scheduling feature analysis on the computing power monitoring data sequence of the current power cross-domain within the specified time range through the plurality of set scheduling analysis layers, and outputting a plurality of computing power scheduling feature sets. And carrying out cross-scale fusion calculation on the feature sets to obtain a fusion computing power scheduling feature set.

The invention discloses a cerebral apoplexy lower limb intelligent rehabilitation training system, which relates to the technical field of rehabilitation instruments and comprises a walking module, a body fixing bracket, a foot fixer, a leg adjusting module, a waist and shoulder auxiliary fixing module and a training posture recognition and correction module. According to the training posture recognition and correction module, a binocular 3D camera is innovatively adopted to collect data, a Voxel CNN network and multi-constraint energy function optimization are combined, high-precision joint coordinate recognition, joint angle calculation and motion trajectory similarity evaluation are achieved, and a self-adaptive admittance control algorithm based on performance is matched, so that the precision of the robot is improved. The training load and the auxiliary force can be dynamically adjusted in real time according to the rehabilitation ability of a patient, customized rehabilitation training of one person and one strategy is achieved, the one-step training mode of a traditional instrument is thoroughly changed, rehabilitation training better meets the individual requirements of the patient, and the rehabilitation effect and the training efficiency are remarkably improved.

The application discloses a hydraulic fracturing parameter optimization method based on nano-indentation spatial heterogeneity atlas, and relates to the field of coalbed methane exploitation.The method comprises the following steps: sampling and nano-indentation testing of a target coal seam, and obtaining load-displacement curves of each measuring point; analyzing and calculating the load-displacement curves of each measuring point, and drawing a heterogeneity atlas of the sampling points and a micro-mechanical spatial heterogeneity atlas of the entire coal seam; identifying the micro-mechanical spatial heterogeneity atlas of the entire coal seam, and constructing a hydraulic fracturing design scheme according to the distribution information of the advantageous path and the inferior path of the fracturing fissure in the coal seam; and combining resistivity tomography technology to monitor the fissure expansion range, and dynamically adjusting the fracturing parameters of the hydraulic fracturing design scheme.The application generates a micro-mechanical spatial heterogeneity atlas through a nano-indenter, depicts the mechanical heterogeneity inside the coal rock, saves the trial-and-error cost of fracturing design, and reduces the blindness of fracturing.

The invention belongs to the technical field of biomedical informatics and drug safety assessment, and provides a drug side effect frequency prediction method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the weighted fusion of one-dimensional sequence features and two-dimensional structure features through employing learnable weight parameters; constructing a side effect similar graph through known drug-side effects, and initializing side effect nodes into semantic feature vectors by adopting preset medical term embedding; calculating an attention coefficient between the side-effect node and a neighbor node thereof by adopting a graph attention network, and updating a semantic feature vector; and training the drug weighted fusion result and the semantic feature vector to obtain a model for predicting the side effect frequency of the target drug, and the technical scheme of the invention realizes the accuracy and efficiency of drug-side effect frequency prediction.

The application relates to the field of semiconductor material calculation, and discloses a tin oxide electric property prediction and regulation method based on a first principle, which comprises the following steps: constructing a tin oxide benchmark supercell to generate an intrinsic defect primary configuration pool and an interstitial impurity candidate site, and performing a primary ion step relaxation to determine a transient charge transition energy level; solving a thermal response tracking coefficient by using a band gap renormalization model, dividing a defect preliminary state into a shallow donor or a deep donor preliminary state; generating a composite defect candidate cluster by analyzing a space charge polarization vector of the deep donor preliminary state, and outputting an effective macroscopic preliminary state through thermodynamic ensemble fusion; after structure relaxation is performed on the above preliminary state, a global charge neutrality equation is established and numerically solved to generate an effective carrier concentration atlas; according to the atlas, a target parameter subspace is located, a doping strategy is determined, and a critical annealing temperature upper limit and a boundary oxygen partial pressure upper limit are inverted. The application improves high-temperature carrier concentration prediction accuracy and gives quantitative process boundaries.

This invention relates to the field of management technology and discloses a method and system for generating management suggestions for long-term, low-maintenance mixed flower borders. The method includes: acquiring plant growth data and community succession data based on the spatial distribution characteristics of the sample plot, plant growth morphology characteristics, and environmental characteristics during the flower border's growth cycle; extracting characteristic data on plant morphology, growth rhythm, and tolerance performance; classifying all plant feature vectors based on a decision tree model; determining distance parameters between different plant combinations based on the K-nearest neighbor algorithm and judging the stability trend and substitution relationship of each plant combination; analyzing the vertical hierarchy, coverage relationship, and color coordination relationship of plants based on the plant combination structure; determining the association results between the community discrimination results and the flower border structure layout based on an association rule algorithm; and determining management suggestions based on the association results and a planning suggestion model. This invention ensures the reliability of mixed flower border management.

The invention relates to the technical field of traditional Chinese medicine informatics and artificial intelligence, in particular to an automatic screening method and system for traditional Chinese medicine efficacy substances based on a large model. According to the method, target efficacy attributes are determined, related targets are obtained, semantic comprehension and knowledge reasoning ability of a large model are combined, target related active compounds and compound data of target traditional Chinese medicinal materials or prescriptions are automatically collected and integrated, and after structure and attribute standardization processing, a training set and a prediction set are constructed. And performing model training and optimization by using a large model driven deep neural network, constructing a drug effect substance screening model, and accurately predicting specific drug effect substances in the traditional Chinese medicine. The system comprises a data automatic acquisition module, an intelligent standardization module, a large model knowledge enhancement training module, a prediction reasoning module, a visual output module and the like, the automation level, efficiency and accuracy of drug effect substance screening can be remarkably improved, blindness of traditional experiments is reduced, and intelligent technical support is provided for discovery of active ingredients of traditional Chinese medicine and research and development of new drugs.

The invention discloses a decision suggestion generation method and device for adding site services, and the method comprises the steps: obtaining quantitative data corresponding to a to-be-added service item for each to-be-added service item, including demand data, competitive data, target site capability data and cost income data, carrying out the fuzzy processing of the quantitative data, and obtaining a decision suggestion of the to-be-added service item; obtaining a fuzzy set group G1 corresponding to demand data, obtaining a fuzzy set group G2 corresponding to competitive data, obtaining a fuzzy set group G3 corresponding to target site capability data, obtaining a fuzzy set group G4 corresponding to cost income data, performing fuzzy logic reasoning on the fuzzy set groups G1, G2, G3 and G4 corresponding to the to-be-added service item, and obtaining a fuzzy set group G4 corresponding to the to-be-added service item; the decision suggestion corresponding to the to-be-added service item is generated according to the to-be-added service item, fuzzy logic reasoning can be carried out according to market dynamic requirements, competitive environments, operation capability and income, the complexity and uncertainty of the market environment are reduced, and accurate and scientific decision suggestions for adding site services can be provided.

A pollution source data quality problem intelligent diagnosis method based on a knowledge graph comprises the steps that the knowledge graph is constructed, and abnormal type diagnosis and abnormal root marking are carried out on the knowledge graph; converting the multi-source data stored in the database at the current moment into quadruple data, accessing the quadruple data into the knowledge graph to execute an intelligent diagnosis process, if an exception type is generated, performing confidence detection on the exception type, and screening a core exception type; abnormal nodes of core abnormal types and potential source nodes are constructed, abnormal source tracing is carried out, and a standardized tracing report is generated based on a tracing result and is fed back to a pollution discharge unit; and if the exception type is not generated, constructing a critical feature database, performing retrospective detection on the tetrad data, and judging whether to generate an estimated exception root or not according to a retrospective detection result and feeding back the estimated exception root to a pollution discharge unit. According to the method, the key data quality problem is effectively focused, irrelevant anomaly interference is reduced, the anomaly recognition accuracy is improved, and resource waste in low-value anomaly processing is avoided.

This application relates to a multi-level adaptive control method, apparatus, device, and storage medium for power quality, belonging to the field of power grid service technology. The method includes: determining the disturbance condition type of the power grid based on target indicator data; selecting a first control strategy from a control strategy template based on the disturbance condition type; updating the strategy parameters of the first control strategy based on the target indicator data and the disturbance condition type to obtain a second control strategy; and managing power quality of the power grid according to the second control strategy. This application effectively improves the efficiency and effectiveness of power grid power quality management, while relying on data-driven strategy selection and parameter optimization to reduce the blindness of management and ensure the scientific nature and effectiveness of power grid power quality management.

This invention relates to the field of distribution network fault technology, and discloses an automatic identification method and device for distribution network grounding faults. The method includes: normalizing the format of multi-source heterogeneous data to obtain a standardized fault feature sequence; performing cluster analysis on historical fault features to obtain a feature pattern library; comparing and correlating the standardized fault feature sequence with the feature pattern library, and cross-validating the comparison results to obtain a preliminary fault type inference; performing deep alignment on the standardized fault feature sequence and the feature pattern library, and comprehensively judging the results of the deep alignment based on the line connection relationship to obtain the final fault type; performing spatiotemporal fusion deduction on the standardized fault feature sequence to obtain the fault propagation path and fault impact range; and tracing the fault propagation path backward to obtain the fault occurrence point. This invention can improve the accuracy of automatic identification of distribution network grounding faults.

This invention discloses a method, equipment, and medium for airline allocation in collaboration between base airlines and alliances, relating to the field of airport operation planning technology. By predicting the alliance's capacity demand within a preset future timeframe, and integrating base airline capacity growth forecasts, alliance collaboration needs, and terminal capacity constraints, a multi-objective optimization model is constructed. This model achieves precise matching and dynamic adjustment between airlines and terminals, strengthens the adaptability constraint between the alliance's future total capacity and the terminal's design capacity, ensures that the alliance's future total capacity in the current allocation does not exceed the terminal's design capacity, and provides quantitative capacity recommendations for future terminal planning. It solves the problems of traditional methods neglecting alliance collaboration, capacity adaptability, and planning foresight, reduces cross-terminal transfer costs, improves airport operational efficiency and passenger experience, and provides a scientific basis for future terminal planning. It is applicable to the long-term planning and daily scheduling of large multi-terminal hub airports.

This invention relates to the field of power generation forecasting technology, specifically to a power generation forecasting method and system based on multimodal data fusion. The method includes: constructing a power generation forecasting model based on multimodal data; using the power generation forecasting model to predict power generation at a specific future time scale to output power generation forecast data; and calculating prediction deviation data by combining actual power generation data; decomposing and quantifying the prediction deviation data based on the degree of influence on the power generation deviation to obtain dispatch strategy deviation, equipment availability deviation, meteorological forecast deviation, and model inherent deviation; optimizing the parameters of the power generation forecasting model based on at least one of the dispatch strategy deviation, equipment availability deviation, meteorological forecast deviation, and model inherent deviation to obtain an optimized power generation forecasting model; and predicting power generation at a specific future time scale in the next stage based on the optimized power generation forecasting model, thereby continuously improving the accuracy and stability of power generation forecasting.

The invention belongs to the technical field of vibration reduction of vibrating screens, and particularly relates to an elastic suspension damping system of a vibrating screen and a dynamic parameter analysis method of the elastic suspension damping system. The elastic suspension damping mechanism is connected between the whole screen vibration part and the whole screen base in a suspension manner; the elastic suspension damping mechanism comprises a supporting spring and a damper. According to the system, the damping element is introduced into the elastic suspension damping system, due to the addition of the damper, an original single linear element or a single nonlinear element is added into a composite element formed by combining the elastic element and the damping element, and the vibration reduction effect of the system is greatly improved.

The invention relates to the technical field of route distribution, and discloses a block chain node route distribution method, device and equipment and a medium, and the method comprises the steps: obtaining the historical load data of block chain nodes, and calculating the expected processing delay, the expected concurrent request amount and the network topology distance of each block chain node based on the historical load data; performing performance quantitative analysis on the expected processing delay, the expected concurrent request quantity and the network topology distance to obtain a processing delay metric value, a concurrent request metric value and a network topology distance metric value; determining a corresponding scene weight coefficient according to the business application scene of the block chain node; calculating a routing distribution cost characteristic value according to the processing delay metric value, the concurrent request metric value, the network topology distance metric value and the scene weight coefficient; and performing a routing distribution decision on the block chain node according to the routing distribution cost feature value. According to the invention, the accuracy of node routing distribution can be improved.

This invention discloses an intelligent management system and its operating method based on integrated heating control. The intelligent management system includes a data warehouse, an operation management system, a production management system, a monitoring management system, an equipment and facility management system, a billing management system, and a customer service management system. The operation management system provides functions for heat network balancing, energy consumption analysis, and operation scheduling; the production management system provides online inspection, auditing, and maintenance functions; the monitoring management system provides data monitoring and video monitoring functions; the equipment and facility management system provides equipment ledger and spare parts management functions; the billing management system provides user files and billing receipt functions; and the customer service management system provides customer service and auxiliary customer service decision-making functions. This invention achieves data sharing among various functional modules through a data warehouse, reducing heating operation energy efficiency, improving operation and management efficiency, and enhancing customer service quality, thus having significant promotional value in the heating field.

The application discloses a kind of radioactive contaminated clothing intelligent management method and related equipment.The method comprises the following steps: collecting the initial radiation dose of the contaminated clothing and generation time;Based on the nuclide decay formula, a decay tracking calculation process is constructed, the current dose is calculated in real time according to the nuclide half-life parameter, and the total dose is obtained by superimposing the contribution of each nuclide when there is multi-nuclide contamination;The current dose calculated in real time is compared with the preset control threshold, and the washable instruction is pushed to the medical terminal when the control threshold is met, and the remaining decay time prompt is output when the control threshold is not met.It can solve the problem that the management of radioactive contaminated clothing is highly dependent on manual, which can easily lead to waste of manpower, missed or wrong recording, and occupational health hazards caused by frequent close contact of medical staff with high-activity contaminated clothing during manual monitoring.

This application discloses a photovoltaic-driven soil moisture feedback irrigation device, comprising: a main body, a water storage tank, an electrical box, a photovoltaic module, and a sprinkler assembly. The photovoltaic module is installed on the top of the main body. The electrical box and the water storage tank are sequentially arranged on the main body and located below the photovoltaic module. The sprinkler assembly is disposed on the outer peripheral wall of the water storage tank and connected to the interior of the water storage tank. The electrical box contains a control component for the photovoltaic module. The bottom of the main body is conical and is equipped with a humidity sensor for detecting soil moisture. The humidity sensor is electrically connected to the control component, and the control component is electrically connected to the sprinkler assembly to control the sprinkler assembly to start spraying water. This device can adaptively adjust the spray volume according to the soil moisture conditions to achieve a reasonable irrigation effect.

The present application relates to the technical field of BIM modeling, and more particularly to a track construction period asset data management method driven by BIM model dynamic updating. The method comprises the following steps: acquiring track construction data and track terrain data stored in a GIS platform; performing component and terrain alignment processing of track construction based on the track construction data and the track terrain data to generate track component terrain alignment data; establishing a track construction dynamic BIM model through the track component terrain alignment data; performing construction-driven minimum maintenance unit node and attribute feature analysis based on the track construction dynamic BIM model to generate construction-driven minimum maintenance unit node-attribute feature data; and performing track construction period asset dynamic management analysis based on the construction-driven minimum maintenance unit node-attribute feature data to generate track construction period asset dynamic management data. The present application realizes BIM model establishment and intelligent dynamic management of assets during the track construction period.

The application relates to the technical field of building design and artificial intelligence, and discloses a method for generating an aging-adapted function topological relationship of a pension building based on a large language model, which comprises the following steps: S1, constructing a function topological relationship database of a pension building; S2, converting the function topological relationship of the pension building case in S1; S3, building a large language model training environment, and calling an API-key to start the large language model; S4, defining reasoning key rules based on the function requirements of a target pension building project, fine-tuning prompt parameters, and enabling the large language model to generate a function topological relationship prediction graph; S5, performing visual processing on the prediction result of S4 by using a Matplotlib library, and distinguishing the display styles of function nodes and connection relationships; S6, selecting the function topological relationship prediction graph meeting the requirements in S5, dividing function partitions, arranging rooms, and adjusting details to complete the plan scheme design of the pension building. The application improves the intelligent level of the pension building design by introducing the large language model and topological relationship reasoning.