98 results about "Matrix model" patented technology

The invention provides a power distribution box insulation monitoring method based on dynamic threshold analysis, and relates to the technical field of power distribution box insulation monitoring, and the method comprises the steps: obtaining multi-class parameter data capable of representing a power distribution box in a healthy insulation state, obtaining a multi-dimensional feature vector set of each time window, and constructing a reference matrix model; inputting a current time window multi-dimensional feature vector set of the distribution box needing to be monitored to obtain an estimated multi-dimensional feature vector set, and calculating a deviation index of the current time window multi-dimensional feature vector set; generating a dynamic early warning threshold value; judging whether a preliminary abnormal signal is triggered or not according to a comparison result of the deviation degree index and a dynamic early warning threshold value; if so, continuously acquiring deviation index slopes of a plurality of later time windows, and performing graded early warning on the insulation state of the distribution box to be monitored according to the deviation index slopes. According to the invention, the insulation state of the distribution box is analyzed based on a working condition self-adaptive dynamic threshold value, and the early and accurate hidden danger identification effect is realized.

The invention discloses a roadbed compactness rapid detection method and system based on a three-dimensional point cloud technology, and relates to the technical field of three-dimensional scanning. The method comprises the following steps: acquiring normalized point cloud of the inner wall of a roadbed compactness test hole, fitting parameters of a matrix cylinder model by combining macroscopic priori knowledge of a test hole drilling tool and adopting a process fusing two algorithms, and calculating an interior point rate; calculating a normal distance from the point cloud to the surface of the model as a geometric residual error, expanding a cylindrical surface to a two-dimensional plane, mapping the residual error, and performing interpolation to generate an initial residual error grid field; obtaining a filler physical and mechanical parameter derivation constraint condition, and optimizing the initial residual error grid field to obtain a physical compliance residual error grid field; and mapping the data back to three dimensions and superposing the data to a matrix model, generating a triangular mesh model, calculating the volume through numerical integration, outputting a result after interior point rate correction, and calculating the compaction degree in combination with filler performance parameters. According to the invention, the accuracy of roadbed compactness detection is effectively improved.

The invention relates to a digital-intelligent automatic point alignment and full information verification method based on a power distribution terminal tester, which comprises the following steps of: acquiring electrical quantity signals and operating parameters of a terminal through the tester, and establishing communication connection through a digital-intelligent point alignment module; starting a three-remote check matrix model to perform matrix check on telemetering, remote signaling and remote control functions, calling an FFT harmonic synthesis telemetering calibration algorithm to dynamically calibrate a deviation value, introducing an abnormal attribution model based on a Bayesian network to perform probability reasoning on abnormal data, generating a report containing abnormal information and calibration suggestions, and uploading the report. The method improves the verification efficiency and overcomes the problem that the existing mode is tedious; checking accuracy is improved, and the problem that measurement deviation is difficult to correct is solved; abnormality processing capability is enhanced, defects of insufficient attribution capability are made up, stable operation of the power distribution terminal is guaranteed, and support is provided for power grid safety.

The invention discloses an assembly precision analysis method for a rotary shaft system of a mechanical structure based on a laser tracking measurement system, and in the laser tracking measurement system, the high precision guarantee of an assembled mechanical system is the premise of realizing accurate measurement. In order to obtain the assembly precision of a laser tracking measurement system, the invention provides an assembly precision analysis method based on Jacobi-spinor for a rotary shaft mechanical structure of the laser tracking measurement system. A Jacobian matrix model in the deviation transfer process and a spinor model comprising plane features, cylinder features and plane and cylinder parallel features are combined, a laser tracking measurement system rotating shaft assembly precision analysis model is established, and Monte Carlo simulation is adopted for calculation results to simulate actual assembly errors. A result shows that a difference value between a theoretical assembling condition and an analogue simulation actual assembling condition is 6.79 microns. The result shows that the provided method can qualitatively analyze the assembly precision of the rotating shaft of the laser tracking measurement system.

A weather prediction method includes generating radiance differences as a difference between measured radiances from satellites and forecast satellite radiances generated by a radiative transfer model and forecasted state profiles output by a numerical weather prediction (NWP) model. When the radiance differences exceed a noise threshold, the method includes generating updated state profiles by generating radiance-sensitivities using a Jacobian model and the forecasted state profiles; constructing a Kalman-gain matrix from background error covariance (BEC) matrices and the radiance-sensitivities; generating filtered state-profile changes from the Kalman-gain matrix and the radiance differences; updating the state profiles by adding the filtered state-profile changes to the forecasted state profiles to yield updated state profiles.

The invention discloses a resolution-oriented 4D millimeter wave radar antenna array and physical layout collaborative optimization method, a program, equipment and a storage medium, which are suitable for a radar system with a limited space and a multi-chip structure. The method comprises the steps of firstly collecting system input parameters; then, an antenna design constraint model is constructed, spatial discretization is carried out, and an optimizable matrix model is formed; transmitting and receiving array structures in the azimuth angle direction and the pitch angle direction are jointly designed through a virtual array mapping strategy, so that the requirements of MIMO mapping efficiency maximization and target angle resolution are met. After an antenna structure is determined, an optimization objective function is further constructed based on strong constraint and soft constraint, and an antenna layout scheme which meets the manufacturing requirements and has optimal performance is obtained through a traversal and search method. According to the method, the virtual aperture can be effectively improved, the antenna number redundancy is reduced, the wiring accessibility is optimized, and the resolution and engineering realizability of a 4D radar system are enhanced.

The invention provides a preset bit automatic configuration method and system for a remote intelligent patrol system, and relates to the technical field of intelligent patrol preset bit configuration.The method comprises the steps that a patrol video stream or a video file obtained from the remote intelligent patrol system is decoded, and a target point location detection model and a multi-target tracking algorithm are used for detecting a target point location; identifying each inspection target point location in the video, matching a unique track for the inspection target point location, and generating a point location list containing track information; based on the point location list, constructing a matrix model for describing a coverage relationship between video frames and inspection point locations, solving an optimal frame set covering all inspection point locations through an optimization algorithm, screening out a final optimal preset bit image and corresponding equipment control parameters from the optimal frame set according to a preset rule, and generating a preset bit list. According to the method, automatic identification, trajectory tracking and intelligent optimization of the preset position of the patrol point can be realized, and the configuration efficiency and accuracy of the preset position are remarkably improved.

The application provides a kind of multi-unmanned aerial vehicle target allocation attack-defense strategy game method and system. Multi-unmanned aerial vehicle formation information of first unmanned aerial vehicle formation and second unmanned aerial vehicle formation is acquired to generate strategy pair of multiple unmanned aerial vehicles according to unmanned aerial vehicle information, and strategy group set of multi-unmanned aerial vehicle formation is generated according to strategy pair, strategy pair can include current unmanned aerial vehicle, attack-defense strategy and strategy target;Attack-defense strategy includes attack strategy, avoidance strategy and interference strategy. By calculating the probability distribution of each unmanned aerial vehicle under different attack-defense strategies, a payoff matrix is constructed, and a zero-sum game matrix model is further generated. Based on the zero-sum game matrix model, the attack-defense strategy game solution of multi-unmanned aerial vehicle target allocation is solved. The application fully considers the three attack-defense strategies of unmanned aerial vehicles, and solves the attack-defense strategy game solution, thereby improving the solution quality of unmanned aerial vehicle target allocation problem.

The application discloses a sequence construction method and system. The method constructs a switching matrix based on the number of various types of elements in the sequence, establishes a unified constraint system, and obtains a numerical solution of the switching matrix through optimization. Based on the numerical solution, a graph structure is constructed and connectivity is determined to determine whether a complete sequence can be formed; when the connectivity is satisfied, a target sequence that meets the switching relationship and quantity requirements is generated based on the graph structure. The method supports segment-level structure expression, modeling of the head-tail relationship of the augmented matrix, and sub-sequence combination expression, and is suitable for multiple sequence construction tasks. Accordingly, the application also provides a sequence construction system, which includes a matrix modeling module, a constraint construction module, a solving module, a connectivity determination module, and a sequence generation module.

The application provides a scientific research business management and control system based on large model technology, comprising a data acquisition module for acquiring multi-source heterogeneous data in the whole process of power scientific research business; a knowledge extraction module for extracting knowledge from the multi-source heterogeneous data according to a power knowledge graph and a data extraction model to obtain a semantic matrix; a model reasoning module for reasoning knowledge from the semantic matrix according to an intelligent reasoning large model to obtain decision information; a bidirectional association interface for determining a reasoning direction according to a structured field constraint of the data extraction model and determining prior knowledge of the intelligent reasoning large model according to the power knowledge graph; and a business management and control module for managing and controlling the scientific research business according to the decision information. Through multi-module cooperation and deep integration of large models and domain knowledge, the application realizes full mining and accurate analysis of multi-source heterogeneous data in the whole process of power scientific research, makes the management and control basis more comprehensive, and guarantees the accuracy and scene adaptability of the reasoning direction.

The application discloses an online network measurement flow recovery method, a terminal device and a storage medium. Network flow data at each moment is modeled according to a two-dimensional matrix model; a basic subspace column is trained according to flow data at historical moments, and indexes of the columns are marked, and a leverage score is obtained by calculation; according to the indexes of the subspace columns, a subspace column that needs full sampling at the current moment is selected, and only part of elements in the remaining columns are sampled; whether sampling needs to be continued is judged according to a sampling matrix at the current moment; when a maximum residual value is less than a certain threshold, unsampled data is recovered by using subspace matrix filling; when the maximum residual value is greater than a certain threshold, columns that need to be continuously measured are selected according to residual sizes, a column space is updated, and then the unsampled data is recovered. The application solves the problems of low recovery precision and inability to recover online in the prior art, and realizes online network measurement with low overhead.

The invention discloses a network communication anomaly detection method and device, equipment and a storage medium, and the method comprises the steps: constructing a real-time communication matrix and a historical communication matrix, carrying out the initialization setting of the real-time communication matrix and the historical communication matrix, continuously capturing a network message at a protocol stack bottom layer of the equipment, and carrying out the analysis of the network message, thereby constructing a quintuple, and carrying out the detection of the network communication anomaly. Performing Hash operation on the quintuple by using a preset Hash function, performing matrix updating on the real-time communication matrix according to a Hash operation result, performing matrix comparison on the real-time communication matrix and the historical communication matrix according to a preset period to obtain a difference communication matrix, performing matrix evaluation on the difference communication matrix, and performing matrix calculation on the difference communication matrix according to a matrix evaluation result. And judging whether the current network communication is abnormal or not. According to the method, all communication links of the equipment can be monitored in real time by constructing the network communication matrix model of the global port, and the defect of one-sidedness of a traditional detection method is overcome.

The application discloses a kind of direct current motor iterative learning control optimization methods for executing change task, it is related to direct current motor control field.The method is based on the closed loop feedback control system of direct current motor and parallelly joins iterative learning controller, based on promotion technique will direct current motor control system be converted into time series input-output matrix model.Under the norm optimization framework, optimal iterative learning control algorithm is designed, through the combination of batch-to-batch repeated learning and batch real-time feedback, so that the system basically realizes zero error tracking to expected output.Based on the optimal input sequence and error sequence obtained by repeatedly executing a task, the feedback and feedforward controller are integrated into a new learning-based feedback controller using least squares fitting method, and finally it is applied to the system executing the change trajectory task.This method transfers the historical learning experience to a new task without limiting its time length, and realizes the trajectory tracking of direct current motor change task without relearning.

The application discloses a dynamic time-sensitive application network routing method and device, a storage medium and an electronic device, and the method comprises the following steps: in the case that a node application initiates a data request to a center node, the center node determines a candidate path based on a network state matrix model, wherein the node application is a user node mapped on a data plane of a logical network topology of a dynamic time-sensitive application network, and the center node is located on a control plane of the logical network topology; a communication time delay of each candidate path calculated based on a routing metric is used to determine a target path from the candidate path, and a path planning parameter is formed; on the basis of the same time reference, the center node performs quadratic programming on the target path, and forms a shaping configuration parameter; and the center node issues the path planning parameter and the shaping configuration parameter to the node application, so that the node application performs data forwarding based on the target path. The application solves the technical problem of deterministic time delay transmission of time-sensitive applications in a dynamic complex network.

This application provides a method, apparatus, device, and medium for detecting polarization aberration in a projection lens. The method includes: sequentially arranging a polarization state generator, a projection lens, a polarization state analyzer, and a detector along the optical path propagation direction to establish a Mueller matrix model corresponding to the projection lens; determining the projection lens Mueller matrix under the characteristic parameters of each component based on the Mueller matrix model; and for each characteristic parameter, changing its value within a preset parameter range based on the Mueller matrix model, while keeping other characteristic parameters at preset values, and calculating the detection deviation of each element in the projection lens Mueller matrix under the current conditions. This method and apparatus significantly improve the accuracy and reliability of polarization aberration detection.

The invention discloses a silicon smelting enterprise carbon emission accounting method based on multiple purposes, and belongs to the technical field of carbon emission accounting. According to the method, a two-dimensional accounting matrix including a production system dimension and an emission link dimension is constructed, and accounting units in the two-dimensional accounting matrix are dynamically activated by designing a unit activation function and a parameter mapping function for different application scenes; constructing a general carbon emission accounting model which is suitable for different scenes and is easy to explain based on the activated two-dimensional accounting matrix; based on the general carbon emission accounting model, designing a carbon emission calculation function in the general accounting model; and constructing an industrial silicon product carbon strength calculation formula in a specific scene. According to the method, the condition that the carbon emission accounting requirements of the silicon smelting enterprise are different under different application scenes such as enterprise carbon transaction, industry carbon management and control and product carbon footprint is fully considered, and a multi-demand response and flexible and adaptive carbon emission accounting technical system is formed by constructing the modular accounting unit and the configurable matrix model.

The invention relates to the technical field of shale gas geology, in particular to a method for depicting a breaking joint body in a breaking joint body development area, and the method comprises the steps: firstly, generating an initial breaking joint body probability body based on interpretable machine learning fusion seismic attributes, and building a three-dimensional space distribution model containing large and medium faults after manual interactive interpretation and well seismic calibration; on the basis, large and medium-sized faults serve as a deterministic skeleton, a fracture development rule is predicted in combination with paleotectonic stress field simulation and a rock fracture criterion, a three-dimensional discrete fracture network model constrained by geomechanics is constructed and then coupled with a matrix model, and a model set is generated by defining an uncertainty parameter space. And screening out an equivalent model group through historical matching, performing prediction verification and iterative optimization by using recent production data, and finally obtaining a three-dimensional space distribution model of the high-precision breaking joint body. According to the method, closed loop of static identification and dynamic verification is realized, and the depicting precision and the geological reliability are remarkably improved.

The application discloses a kind of processing method, device and electronic equipment of customer information, which is applied to big data field, and the method comprises: the customer information in multiple incoming call work orders of multiple customers is encoded and processed, to obtain multiple documents corresponding to multiple incoming call work orders;Obtain the weighting matrix model of each document in multiple documents;Obtain the theme word set of each document in multiple documents;According to the theme word set of each document and the weighting matrix model of each document, the target similarity between each document in multiple documents and each other document is calculated;According to target similarity, multiple documents are clustered based on PAM clustering algorithm, to obtain the clustered document set;From the clustered document set, obtain the target information of multiple customers.By the present application, the problem that the value information of incoming call work order is extracted by artificial labeling or natural language processing technology in related technology, leading to the inaccuracy of information extracted from incoming call work order is solved.

The embodiment of the application discloses a CAD-based three-dimensional terrain geological model modeling method, device and medium, relates to the CAD modeling technical field, and is used for solving the problem of low reliability of the existing three-dimensional modeling mode. The method comprises the following steps: acquiring multi-source heterogeneous data corresponding to a current modeling type for preprocessing to obtain a discrete point set; if it is determined that the current modeling type is a terrain modeling type, performing dimension reduction and profile division on the discrete point set to obtain a triangular facet, and performing dimension increase on a two-dimensional discrete point set corresponding to the triangular facet to obtain a three-dimensional terrain grid model; if it is determined that the current modeling type is a geological modeling type, performing dimension reduction and analysis on the discrete point set to generate a stratigraphic interface; processing the discrete point set through a preset strategy to obtain a geological matrix model, and performing stratigraphic segmentation on the geological matrix model according to the stratigraphic interface to obtain a three-dimensional geological model; and transmitting modeling data corresponding to the obtained model to a browser for rendering and display based on an application server.

The application discloses a star-inertial integrated outfield dynamic calibration method based on a refracting surface constraint mechanism, and relates to the technical field of calibration methods, and specifically discloses the following technical scheme: a relationship model of an observed star position and a zenith direction is established based on a refracting surface constraint mechanism and observation imaging of a star, a first zenith direction measurement model under a star sensor system corresponding to an observation time and an observation position is established based on the relationship model; a second zenith direction measurement model under an inertial navigation system of the zenith direction of a current observation position is established through a filter combination model based on real-time measurement values of angular velocity and angular acceleration of the inertial navigation system; a zenith direction integrated conversion matrix model between the inertial navigation system and the star sensor system is established by simultaneously solving the first zenith direction measurement model under the star sensor coordinate system and the second zenith direction measurement model under the inertial navigation system; and a star-inertial integrated outfield optimization calibration model is established by changing the longitude and latitude of the observation position and the observation direction for multiple times, so that star-inertial integrated outfield calibration is carried out.

The invention relates to the technical field of metallogenic prediction, in particular to a metallogenic prospective area prediction system and method based on embedded knowledge reasoning, and the system comprises a collection module which is used for collecting exploration data and geological map data; the data preparation module is used for cutting the exploration data into fishing net units; the knowledge graph construction and embedding module is used for constructing a knowledge graph database by utilizing the geological map data and embedding entities and relationships into a low-dimensional space; the knowledge-data fusion module is used for generating a knowledge-data fusion matrix of the corresponding fishing net unit for each fishing net unit; the model training and optimizing module is used for inputting the knowledge-data fusion matrix of the labeled fishing net unit into a deep learning network to construct a metallogenic prediction model; and the metallogenic prediction and result interpretation module is used for calculating the metallogenic probabilities of all the fishing net units in the research area by using the metallogenic prediction model. According to the method, knowledge graph embedding and exploration data are subjected to structured fusion in an input layer, so that the model not only learns a data mode, but also can understand a geological background.

The application discloses a kind of based on gradient descent method's uniform array ultra-wideband radar positioning imaging method, it is related to radar positioning technical field, the signal matrix model after matching filtering is constructed in the application, matrix decomposition is carried out by gradient descent method, joint direction matrix and joint electromagnetic guide vector matrix are obtained, then, two groups of two-dimensional angle estimation values with high resolution and no ambiguity are respectively obtained from the two matrices, accurate angle parameters are obtained by weighted fusion, and target three-dimensional coordinates are calculated accordingly, finally, radar image is generated by back projection algorithm, so that the number of array elements and hardware complexity are significantly reduced, the inherent angle ambiguity problem of array is overcome, the multi-target angle resolution and parameter estimation stability are improved, and the calculation efficiency and engineering realizability are also considered.

The application discloses a self-synchronization current differential protection method suitable for a cable-overhead line hybrid transmission line and related devices. The method comprises the following steps: constructing a complete distributed parameter matrix model of the hybrid line; before a fault occurs, performing non-synchronous phase angle compensation on sampling values at two ends, determining an optimal compensation angle by traversing search of minimum differential current variance, and realizing self-synchronization; calculating three-phase differential currents and braking currents based on the synchronized electrical quantities; and adopting a proportional braking criterion to identify an in-zone fault. The device comprises a data acquisition module, a model construction module, a self-synchronization module, a fault detection module and a protection action module which are connected in sequence. Through accurate modeling and self-synchronization technology based on pre-fault data, the application effectively solves the problem of poor protection reliability caused by different parameters of the hybrid line and different sampling at two ends, can quickly and accurately identify an in-zone fault, and is suitable for hybrid line scenes of offshore wind power transmission and urban power grids.

The invention discloses a scheduling method and device for a new energy power system containing small hydropower stations, equipment and a medium, and the method comprises the steps: constructing a hydropower space-time matrix model of the system based on a topological structure and water flow motion parameters between nodes of a watershed; substituting the load prediction value and the operation parameter prediction value of each unit into a deterministic model to obtain a reference value of a system optimization target; and according to the uncertainty model, the reference value and the certainty model of the system, constructing an IGDT scheduling model of the system and solving the IGDT scheduling model to obtain an output plan and an optimization target of each unit in the system. By constructing a hydropower space-time matrix model of the system, a topological structure and a water flow motion state between each small hydropower station and a conventional hydropower station are considered when a decision is made, and the accuracy and the reliability of a scheduling result are improved; the influence of water load uncertainty on a scheduling result is quantified through an information gap decision theory, a decision maker provides scheduling strategies under different risks and different effects, and the reliability and economical efficiency of a final scheduling scheme are guaranteed.

The present disclosure provides a method and device for generating an automatic test script and a storage medium, including: obtaining an initial automatic test script and parsing the initial automatic test script to extract an initial XPath path; obtaining content of a webpage to be tested, parsing the content of the webpage to generate a DOM tree of the webpage to be tested; determining a corresponding test script data table based on the initial XPath path; establishing a webpage element matrix model based on the DOM tree; optimizing the initial XPath path based on the test script data table and the webpage element matrix model to obtain a target XPath path, and generating a target UI automatic test script based on the target XPath path. Thus, the present disclosure can automatically adjust the initial XPath path to obtain the target XPath path through the test script data table and the webpage element matrix model, without manual adjustment, thereby improving the generation efficiency and accuracy of the test script, and further improving the efficiency and accuracy of UI testing.

The invention discloses a tube bundle structure thermal coupling multi-objective topological optimization method considering gap heat conduction. According to the method, firstly, two matrix models are subjected to topological optimization with mechanical flexibility and heat dissipation weakness as optimization targets, and then the two matrix models are combined into a coupling model for topological optimization; an objective function during topological optimization of the coupling model is formed by carrying out linear weighted aggregation on mechanical compliance and heat dissipation weakness after normalization processing, then adjusting weight factors of the mechanical compliance and the heat dissipation weakness in the objective function, and generating Pareto leading edges of a multi-objective optimal solution set under different weight factors; and screening an optimal solution from the Pareto frontier, carrying out thermal coupling simulation on the tube bundle model reconstructed by using the screened optimal solution, then adjusting the constraint volume fraction, and repeating the steps until the optimal tube bundle model is obtained. According to the invention, collaborative optimization of rigidity, heat dissipation and weight reduction of the tube bundle structure can be realized.

The invention relates to the technical field of semiconductors, discloses a beam forming chip array coupling suppression method and system, and aims to solve the technical problems that electromagnetic coupling between array units under high-density integration causes radiation performance degradation, and a traditional decoupling method depends on additional hardware and lacks dynamic adaptive capacity. The method comprises the following steps: acquiring near-field response data of each antenna unit through a near-field sensing unit, and constructing and dynamically updating an array coupling matrix model; and calculating a decoupling predistortion matrix based on the model in combination with target beam pointing, generating an excitation correction value sequence, and injecting the excitation correction value sequence into a transmitting channel to realize signal precorrection. Through the above scheme, real-time sensing and adaptive suppression of the internal coupling effect of the chip array are realized, dependence on external test equipment is not needed, the beam pointing precision and the system stability are improved, the method is compatible with a mainstream process platform, and the method has good engineering portability and industrialization prospects.

The application provides a method for calibrating the inner parameters of a defocus camera based on a circular hole target, comprising the following steps: step one: according to a light ray tracing model, an inner parameter matrix model containing unknown image distance, focal length and camera center position coordinates is established; step two: the circular hole target is moved for multiple times, and the size of each element in the matrix is obtained by using Zhang Zhengyou's calibration method; step three: the value of a polynomial containing the image distance and the focal length is calculated by moving the position of a point light source; step four: the CCD camera is moved, and a nonlinear equation set is established according to the difference value information of different image distances and focal lengths and the parameters obtained in step two, and the image distance, the camera focal length, the camera center position coordinates and the position of the point light source are solved. The application can solve the focal length and the coordinates of the camera center point under the condition of unknown image distance, and solves the problem that most calibration methods assume that the image distance is equal to the focal length, and the calibration is not accurate enough in the case that the image plane deviates from the focal plane.

The invention relates to the technical field of petroleum and natural gas exploration and development, in particular to a carbonate rock platform favorable reservoir body prediction method and device. The method comprises the following steps: interpreting a target stratum structure based on geological data, seismic data and logging data of a carbonate reservoir body to obtain a geological framework of the target stratum; based on a target stratum geological framework, a data element matrix model is constructed; filtering and smoothing the constructed data element matrix model to obtain a normal landform surplus map corresponding to the target stratum structure; and predicting the favorable reservoir body development area of the carbonate rock bench by combining the normal landform surplus map with the carbonate rock bench sedimentary mode and well data. According to the method, the specific three-dimensional geometrical characteristics of the sedimentary geologic body are considered, the geometrical characteristics of the geologic body are fully utilized, the distribution of the reservoir body can be automatically identified, interference of human factors is avoided, and scientific technical support can be provided for decision-making aspects such as exploration and evaluation well optimization deployment and carbonate rock new project selection in the oil-gas exploration period.

This invention relates to a multi-energy flow carbon footprint tracking method based on a carbon memory matrix and conservation constraints, belonging to the technical fields of energy internet, industrial carbon management, and intelligent manufacturing. It constructs a multi-source energy-carbon coupled data foundation to achieve unified data across multiple time scales; establishes an energy storage carbon memory matrix model with time and temperature hierarchies to characterize the dynamic evolution of carbon intensity in the energy storage system; based on this, it constructs a multi-energy flow directed carbon flow graph to achieve unified carbon tracking and allocation for electrical, thermal, and cooling energy flows; introduces carbon flow conservation constraints and a weighted least squares state estimation method to achieve physical consistency verification and self-repair of carbon data; finally, it constructs a mixed-integer linear programming model with explicit embedded carbon memory constraints to achieve optimal multi-energy coordinated scheduling of carbon emissions throughout the entire life cycle. This invention realizes the transformation of carbon footprint from static accounting to dynamic tracking, and from post-event statistics to proactive optimization, significantly improving the reliability of carbon data and the effectiveness of low-carbon scheduling.