500 results about "Mapping algorithm" patented technology

The invention relates to the technical field of fault detection control, and discloses an automobile fault detection method and system fusing sensor data. The method comprises the following steps: modeling a multi-system sensor network through an automobile system topology mapping algorithm to obtain a sensor topology incidence matrix; performing synchronous processing on the sensor topological incidence matrix according to a vehicle dynamics constraint equation to obtain a synchronous multi-sensor data set; inputting the synchronous multi-sensor data set into a fault propagation path sensing network for fusion to obtain a vehicle system fault feature vector; detecting the fault feature vector based on an automobile physical model constraint optimizer to obtain a fault state recognition result; and tracing and controlling a fault state identification result according to the fault propagation atlas model to obtain a system adjustment control signal. According to the invention, the source identification accuracy of the complex coupling fault and the pertinence of control and adjustment are improved.

A distributed intelligent authentication method based on dynamic multi-modal fusion relates to the field of network security, and adopts an alliance chain + DAG hybrid block chain architecture, combines a threshold signature to realize secret key fragment management, and switches among PBFT, Raft and probabilistic algorithms through a dynamic consensus mechanism to improve authentication efficiency. The multi-mode authentication module is based on a dynamic weight distribution algorithm, integrates biological characteristics, behavior analysis, equipment fingerprints and environmental factors, and combines an LSTM-GAN model and a quantum random number driven challenge-response mechanism to realize zero-trust verification under environmental perception. The session management module generates a session key by using a chaotic mapping algorithm. In the aspect of privacy protection, CKKS homomorphic encryption, zero-knowledge proof and attribute-based encryption are fused. According to the method, the block chain technology, the secure multi-party computing technology, the machine learning technology and the quantum cryptography technology are fused, and a high-performance, high-security and strong-privacy-protection distributed authentication solution is provided.

The invention discloses a defect repair method based on digital twinning and friction stir welding technologies, and relates to the technical field of intelligent manufacturing and digital twinning, and the defect repair method comprises the following steps: synchronously capturing full-dimensional data of a welding area through a multi-mode sensor array integrated by an actuator; secondly, segmenting defect boundaries by adopting a deep learning algorithm, constructing a dynamic twin model in combination with thermal-force field coupling simulation, and accurately mapping defect three-dimensional features; generating a repair track according to the twinborn model, converting the repair track into a robot joint instruction through a curved surface parameterization mapping algorithm, and implanting real-time anti-collision constraint; in the repairing process, based on reinforcement learning control of the material rheological resistance and the temperature gradient, the rotating speed, the advancing speed and the down force of the tool are dynamically adjusted; and after repairing, micro-focus CT scanning is started immediately, actually measured data is compared with twinborn prediction, and when the deviation exceeds a threshold value, a re-repairing process is triggered automatically. The method solves the problems that a traditional method depends on manual intervention and the precision of a sensor is easily interfered by the environment.

The invention discloses a battery cluster level fire-fighting linkage control method and system based on a BMS, and the method comprises the steps: carrying out the thermal runaway prediction through a multi-source feature fusion network according to the real-time voltage, temperature and gas concentration data of a battery cluster, and outputting a thermal runaway prediction level; on the basis of the thermal runaway prediction level, a dynamic priority mapping algorithm is utilized, and a control instruction set containing execution priority and spatial positioning is output according to the battery cluster topological structure; according to the control instruction set, a dual-channel redundant signal verification mechanism is adopted to execute a fire-fighting action, and a real-time action feedback signal is output; and on the basis of the real-time action feedback signal and the residual state data of the battery cluster, updating the parameter weight of the multi-source feature fusion network through a reinforcement learning model so as to be used for fire-fighting linkage control in the next period, and forming a closed-loop control link. According to the embodiment of the invention, battery cluster-level fire-fighting linkage control can be realized, so that the safety protection capability of a battery system is improved.

The invention discloses a precise interference avoidance method and device in a radio system, and relates to the field of signal processing, and the method comprises the steps: constructing a sensing matrix through sensing node data, and capturing a transient interference signal through aperiodic scanning; performing tensor decomposition on the signal data to extract time domain, frequency domain, space domain and modulation domain features, constructing a dual-mode spectrum analysis model, reconstructing an instantaneous spectrogram by using compressed sensing, and predicting an interference mode through LSTM; after the instantaneous spectrogram and the predicted interference graph are fused, threat assessment is carried out through a multi-stage interference classification model; according to the interference category and the threat level, beam forming is optimized, adaptive null is generated, a power density optimization model is constructed, and the transmitting power is dynamically adjusted; an anti-interference frequency hopping sequence is generated based on a chaotic mapping algorithm, and spectrum camouflage and tracking interference resistance are realized. The method has the advantages that accurate identification and dynamic avoidance of interference are realized through multi-dimensional perception, intelligent prediction and adaptive beam forming, and the interference avoidance capability of a wireless system is improved.

The invention provides a hybrid parallel and dynamic scheduling method of a hybrid expert model based on 3D near-memory processing. The method comprises the following steps: establishing a joint performance analysis model; performing off-line linear programming optimization expert distribution; performing Bayesian optimization on physical node mapping; performing online reasoning; carrying out online dynamic priority detection; and an expert pre-broadcast and communication-friendly lexical element distribution strategy with optimal efficiency is provided. According to the method, node balancing optimization is realized through offline linear programming, and the problem of load imbalance of 3D NMP calculation is remarkably improved; in combination with a Bayesian optimization mapping strategy of link balance, the communication speed-up ratio is increased, and NoC link congestion is reduced; a dynamic scheduling strategy adapts to dynamic changes of expert activation in real-time reasoning through calculation load prediction and a pre-broadcast mechanism. Through cooperation of the offline automatic hybrid parallel mapping algorithm and the online dynamic scheduling strategy, the calculation load and the communication overhead are effectively balanced, and the reasoning efficiency of the hybrid expert model MoE on the 3D near-memory processing architecture is remarkably improved.

The invention relates to the field of measurement, in particular to a subway tunnel secondary lining section limit measurement method based on SLAM mobile scanning, which comprises the following steps: step 1, tunnel point cloud acquisition and target clustering point cloud acquisition; step 2, CPIII control point coordinate extraction; step 3, point cloud coordinate conversion; 4, performing point cloud processing, and removing noisy points and non-secondary-lining target point cloud data in the tunnel secondary-lining point cloud; and step 5, performing three-dimensional limit deviation analysis, performing spatial comparative analysis on the point cloud under the construction coordinate system and the subway secondary lining tunnel design three-dimensional model by adopting a voxelization deviation mapping algorithm, extracting a continuous deviation region through voxel clustering, and generating a three-dimensional deviation thermodynamic diagram. According to the method, the two-lining tunnel point cloud obtained by SLAM mobile scanning is accurately converted into a construction coordinate system by combining CPIII high-precision control points in the tunnel, rapid, visual and three-dimensional contrastive analysis with design of a three-dimensional model can be achieved, and visual and reliable data support is provided for line and slope adjustment, track laying and defect improvement.

The invention belongs to the technical field of data processing, and particularly discloses a dynamic path planning method and system for an inspection robot, and the method comprises the steps: collecting field data through a sensor, processing a laser scanning point cloud and a camera image through a positioning mapping algorithm, and fusing multi-source information to generate a real-time map. Obtaining a three-dimensional environment model containing a dynamic obstacle position; according to the three-dimensional environment model, obstacle features are extracted, a deep learning model is adopted to identify moving personnel and randomly placed goods, obstacle types and movement tracks are judged, and a classified obstacle data set is obtained; through the classified obstacle data set, the distance and the relative speed between the obstacle and the current position of the robot are calculated, and if the distance is smaller than a preset threshold value and the speed is larger than zero, high-priority interference is marked; according to the invention, the problem of inaccurate dynamic obstacle identification and obstacle avoidance in a complex scene in the prior art is solved.

The invention discloses an intelligent monitoring method and system for the construction progress of a building decoration curtain wall. The method comprises the steps that multi-source construction data of a construction site are collected through Internet of Things equipment and a high-definition camera; constructing a multi-dimensional tensor model and extracting data association features by applying a local reversible mapping algorithm to generate a standardized feature data set; performing parallel computing through shared memory hierarchical process mapping by utilizing the standardized feature data set, and outputting a project progress state evaluation result; constructing a decision diagram based on the project progress state evaluation result, and generating a construction progress deviation report; predicting a construction progress trend by adopting a sample optimal private regression algorithm and generating an optimization scheme; and visually displaying the construction progress prediction report and carrying out early warning. According to the invention, the problems of low data integration efficiency, delayed decision response and weak multi-dimensional data association analysis capability of traditional curtain wall construction monitoring are solved, and intelligent and efficient monitoring of the construction progress of the building decoration curtain wall is realized.

The present invention discloses a distributed heuristic unmanned cluster brain-like swarm intelligence fusion search and capture method, comprising: step 1: completing single target detection on the basis of a Yolov5 network, and predicting the position of a next frame of target on the basis of a DeepSort algorithm; step 2, on the basis of the distance difference and the area difference, determining, by mapping, navigation end point coordinates formula (1) of an intelligent agent in a physical space; step 3, constructing a diffusion-contraction coordinated chaotic mapping algorithm, and mapping the update of the navigation end point coordinates into a uniformly distributed chaotic space; step 4: on the basis of target detection confidence decision information and regional position information of all intelligent agents, fusing and generating global search information formula (3) of a search space formula (2); step 5: on the basis of the intelligent agent global search information, fusing various sensing data in a multi-agent system, so as to estimate target position information; and step 6: performing measurement on the basis of a real-time position of the intelligent agent and an obstacle position. The present invention has high capture efficiency and can accurately update a capture end point of the intelligent agent to complete a task of encircling a moving target.

The invention belongs to the technical field of artificial intelligence, is applied to the field of financial science and technology and the field of medical health, and discloses a rule engine configuration method, device and equipment based on machine learning and a storage medium. The method comprises the steps that historical calculation data and performance indexes in historical calculation tasks are collected, and a training data set is constructed; a machine learning model is trained, and algorithm parameters of the rule engine are dynamically optimized through the training data set; configuring an expression and a user-defined function of a rule engine, and realizing analysis and execution of scripts through JEXL (JavaScript Exchange Library); establishing a dynamic mapping relationship between the algorithm configuration library and the business variables, mapping algorithm variable names and business variable names, and generating configurable algorithm rules; and analyzing task load and resource requirements based on a pre-trained machine learning model, distributing system resources, and repairing abnormal behaviors in a calculation process. According to the invention, the problems of low processing efficiency, high maintenance cost, unreasonable resource allocation and poor expandability in the prior art are solved.

The invention relates to the technical field of intelligent driving, and discloses a defogging embedded system and method for an intelligent driving vehicle-mounted camera, and the method comprises the steps: obtaining original image data collected by the vehicle-mounted camera, and analyzing the brightness distribution, color shift and texture features in an image; based on the image degradation feature information, performing preliminary enhancement processing on the image by adopting an edge guided filtering and brightness adaptive mapping algorithm to generate an initial enhanced image; carrying out fog distribution estimation on the initial enhanced image, carrying out detail restoration and color compensation in combination with a lightweight image reconstruction strategy, and dynamically improving the image quality through an iterative optimization mode; performing definition evaluation on the optimized image, and measuring the fuzzy degree change trend and the structural similarity; and in combination with the finally output clear image, performing target identification and feature extraction operation, and performing accuracy evaluation on an identification result. The method has the advantage of improving the definition of the intelligent driving image.

A page identification technique is configurable to select regions of a screen for optical character recognition. The size of the regions may be selected to reduce the CPU resources needed to identify a page. Pre-processing and post-processing may be performed to improve the accuracy of the optical character recognition. A word mapping algorithm may include logical condition to determine a page name.

A method for surveying an environment by a movable surveying instrument with a progressional capturing of 2D-images by at least one camera and applying a visual simultaneous location and mapping algorithm (VSLAM) or a visual inertial simultaneous location and mapping algorithm (VISLAM) with a progressional deriving of a sparse evolving point cloud of at least part of the environment, and a progressional deriving of a trajectory of movement. The method comprises a progressional matching of the sparse evolving point cloud with a previously derived 3D-geometry, with a minimizing of a function configured to model a distance between the sparse point cloud and the previously derived 3D-geometry and deriving a spatial localization and orientation of the surveying instrument. At least one surveying measurement value of the environment by a spatial measurement unit is combined with the sparse point cloud or the previously derived 3D-geometry.

The invention relates to the technical field of bridge engineering structure health monitoring, in particular to a service life prediction method and system for a bridge connection part, and the method comprises the steps: collecting the strain of a grouting sleeve, a reinforcement-grouting interface ultrasonic reflection signal and environment temperature and humidity data through a distributed sensor array; a three-dimensional dynamic void rate model is generated through fusion of a spatial topological mapping algorithm, a correlation function of load circulation and void expansion is established, the dynamic void rate is input into a bond strength coupling degradation model, after strength attenuation is quantized in combination with steel bar corrosion data and bond failure early warning is triggered, stress redistribution is calculated through multi-physics coupling simulation, and the dynamic void rate is obtained. Early warning is taken as a starting node, the actual load spectrum and temperature and humidity data are combined, Monte Carlo sampling is adopted to simulate rigidity degradation and output the residual life probability, the system comprises a multi-source collaborative sensing unit, a micro-void evolution analysis unit and a life prediction decision unit, and the safety control precision of bridge connection parts is improved.

The invention provides an automobile seat massage adjusting method and adjusting system, and belongs to the technical field of automobile seat intelligent massage control. The method comprises the steps that seat multi-area pressure sensing data are collected, and a pressure feature matrix and a massage mode classification model set are constructed; setting a user body type parameter adjustment category set, and establishing a parameter fusion association model based on historical use data; current pressure and vibration characteristic parameters are extracted, and an optimized parameter set is generated through characteristic optimization; and updating massage control logic and calibrating a parameter matching position. The system comprises a data acquisition module, a model construction module, a feature optimization module and a calibration module. By dynamically fusing real-time data and historical parameters, self-adaptive adjustment of massage intensity is achieved, the problem that a traditional fixed mode cannot be matched with personalized requirements is solved, meanwhile, the parameter calibration precision is improved through a coordinate mapping algorithm, and user experience is improved.

The invention discloses a brightness adjustment control method and a brightness adjustment device, and relates to the technical field of vehicle-mounted systems. The brightness adjustment control method comprises the following steps: acquiring light parameters, position data and time information; determining a current scene of the vehicle; and generating a corresponding control signal to drive the backlight source to work. According to the method, the light parameters, the position data and the time information are fused to realize multi-dimensional environment perception and dynamic scene discrimination, so that the environment state of the vehicle is accurately identified, the scene classification accuracy is improved, and then, the adaptive brightness mapping algorithm based on scene feature matching is utilized to improve the accuracy of scene classification. Smooth and continuous control signals are generated according to human eye perception characteristics to drive a backlight source, and visual fatigue caused by brightness step in a traditional scheme is avoided; meanwhile, instantaneous environment interference is filtered out through position pre-judgment and illumination trend analysis, and the system stability under the complex working condition is enhanced.

The invention provides a battery car dynamic charging optimization management system based on battery health state evaluation, and belongs to the technical field of battery car charging management. The system comprises a data acquisition module which is connected with an environment sensing device and a battery management system and acquires environment and battery parameters in real time; the data storage module is used for storing an initial training data set, a charging and discharging data set and a battery aging feature library; the model building module is used for building a battery health state evaluation model through a migration strategy and building a response model through a modeling strategy; the health state evaluation module is used for extracting associated features with a critical damage threshold value as a core through a mapping algorithm based on the battery parameters, the environmental parameters and an aging feature library; and the charging strategy generation module comprises a strategy generation unit, a reference parameter generation unit and a dynamic correction unit. The system effectively improves the adaptability of battery car charging, guarantees the efficient and stable operation of the battery, and remarkably improves the safety and prolongs the service life of the battery.

The invention relates to the technical field of image encryption, in particular to an image chaotic encryption method based on a magnetic control memristor and electronic equipment, and the method comprises the steps: obtaining an input image; calculating a hash value or generating a random challenge value according to the input image to determine input excitation; judging whether the magnetic field intensity is in a set legal magnetic field domain; if so, calling a real response path of the magnetic control memristor to generate a real response code stream at least according to the input excitation and the magnetic field intensity; constructing a chaotic parameter and a disturbance source according to the real response code stream, and injecting the chaotic parameter and the disturbance source into the fractional order hyperchaotic system; generating a dynamic key stream through a fractional order hyper-chaotic system according to the chaotic parameters; the dynamic secret key stream is combined with a mapping algorithm to globally scramble pixels of an input image, the dynamic secret key stream and a disturbance source are used to carry out bidirectional diffusion on the scrambled image, and a chaotic encryption image is obtained. According to the invention, the magnetic control memristor PUF and the fractional order hyper-chaotic system are deeply fused, and a hardware and algorithm collaborative image encryption mechanism is realized.

The invention provides an LED spherical screen video image coordinate generation method and system, a medium, a program product and a terminal, and the method comprises the steps: obtaining a configuration file of an LED spherical screen, and carrying out the analysis, so as to obtain the spatial geometric parameters of the LED spherical screen; obtaining a to-be-displayed video image of the LED spherical screen, and analyzing and screening the to-be-displayed video image to obtain an effective pixel data set; and calculating latitude and longitude coordinates corresponding to the pixel coordinates of the to-be-displayed video image by adopting a nonlinear mapping method based on the spatial geometric parameters of the LED spherical screen and the effective pixel data set of the to-be-displayed video image. By preloading spatial geometric parameters of a sphere, image pixels are dynamically analyzed, and efficient and accurate conversion from pixel coordinates to latitude and longitude coordinates is realized by adopting a nonlinear mapping algorithm. Meanwhile, the batch writing optimization and dynamic buffer management technology is adopted, the processing speed and the system operation stability are remarkably improved, and the method can be widely applied to the fields of LED spherical screen content manufacturing, display correction and the like.

The invention discloses a self-adaptive mouse control method and device based on an inertial measurement unit and a computer readable storage medium. The method comprises the steps that basic mouse sensitivity adjusting parameters are calculated according to physical mouse sensitivity setting; obtaining original three-dimensional motion data of the inertial measurement unit to generate a standard motion feature flow; selecting parameters from the standard motion feature flow as basic cursor control input based on current human-computer interaction situation information; using the basic sensitivity parameter as an adjusting parameter, and processing the basic cursor control input by applying a preset mapping algorithm corresponding to the current effective sensitivity mapping mode to generate a mouse cursor moving instruction; and matching the standard motion feature flow with a pre-constructed hierarchical motion primitive library to obtain a mouse key instruction. The method has the advantage that the operation efficiency and the user experience of IMU-based mouse control in multiple scenes are improved.

The invention discloses a biaxial coaxiality in-situ detection system and method based on optical dynamic reference coupling, relates to the field of real-time calibration of photoelectric tracking equipment, and solves the technical defects of reference transmission errors and dynamic response delay caused by mechanical stress deformation in traditional contact measurement. The system comprises a pitching assembly, a laser light source, a two-dimensional moving platform, a stable platform, a base, a standard clamping ring, a left shaft, a right shaft and a photosensitive position sensor. A stable platform is arranged on the base, a two-dimensional moving platform is arranged on the stable platform, a laser light source emitted by the laser device penetrates through a standard clamping ring through hole and forms light spots on the photosensitive position sensors, and the two photosensitive position sensors achieve coordinate correlation mapping through a dynamic coordinate system mapping algorithm and obtain two coordinate systems at the same time; the standard clamping rings are symmetrically installed on the end faces of the two sides of the left shaft and the right shaft, and the back photosensitive position sensors are symmetrically arranged in the gap between the left shaft and the right shaft. And data collaborative acquisition is realized through the synchronous controller.

The invention discloses a mouse cursor control method and device based on an inertial measurement unit and a computer readable storage medium. The method comprises the steps that basic mouse sensitivity adjusting parameters are calculated according to physical mouse sensitivity setting; obtaining original three-dimensional motion data of the inertial measurement unit and executing multi-stage preprocessing to generate a standard motion feature flow; selecting parameters from the standard motion feature flow as basic cursor control input based on current human-computer interaction situation information; according to the system detection condition, determining a current effective sensitivity mapping mode in at least two preset sensitivity mapping modes; and using the basic sensitivity parameter as an adjusting parameter, and processing the basic cursor control input by applying a preset mapping algorithm corresponding to the current effective sensitivity mapping mode to generate a mouse cursor moving instruction. The method has the advantage that the operation efficiency and the user experience of the IMU-based cursor control in multiple scenes are improved.

The invention discloses a cloud mobile phone equipment fingerprint disguising method and related equipment, and relates to the technical field of cloud mobile phone security, and the method comprises the steps: obtaining hardware entropy source data which comprises current timestamp data, a hardware unique identifier hash value and an environment noise sampling value; non-linear transformation is carried out on the hardware entropy source data based on a preset chaotic mapping algorithm, a virtual parameter set is generated, and the virtual parameter set meets a preset equipment parameter rule; covering the virtual parameter set to a multi-level system interface of the real equipment fingerprint through kernel-level injection operation; monitoring the use state of the virtual parameter set based on a preset life cycle model, and determining a parameter updating trigger condition; and when a parameter updating triggering condition is met, the nonlinear transformation is executed again to generate an updated virtual parameter set, and the updated virtual parameter set covers the multi-level system interface.

The invention discloses an electronic medical record data structuring standard method, and belongs to the technical field of medical information, the electronic medical record data structuring standard method comprises the following specific steps: 1, data acquisition and format unification: a system receives text data from outpatient records, hospitalized medical records and inspection reports, and sends the text data to a server; the method comprises the following steps of: uniformly converting text data into UTF-8 codes and removing redundant symbols according to time sequence data streams of CT (Computed Tomography), MRI (Magnetic Resonance Imaging) medical images and vital sign monitoring; through the BiLSTM-CRF model and the dynamic term mapping algorithm, the medical entity recognition accuracy is greatly improved, the term standardization rate is remarkably improved, texts, images and time series data are associated through a hierarchical model, cross-modal query is supported, an API interface is constructed based on the HL7 FHIR standard, seamless connection with HIS, PACS and other systems is achieved, the data exchange error rate is greatly reduced, and the data exchange efficiency is greatly improved. The hybrid storage architecture reduces the storage cost, and supports the lateral extension to a million-level medical record scale.

The invention relates to the technical field of signal processing of intelligent voice equipment, and discloses an equalization method and system for a Chirp modulation signal of audio equipment, and the equalization method for the Chirp modulation signal of the audio equipment comprises the steps: analyzing the non-stationary characteristic of the Chirp modulation signal through an information geometric mapping algorithm, and generating non-stationary complexity mapping; processing the Chirp modulation signal by using a multi-scale entropy analysis algorithm to generate a multi-scale complexity spectrum; extracting long-range correlation characteristics of the Chirp modulation signals by adopting a fractal analysis algorithm, and outputting Hurst index characteristic mapping; constructing a complexity-perceived adaptive equalization system; a time-frequency joint optimization algorithm is constructed, and global optimization and adaptive adjustment of equalization parameters are realized; signal complexity characteristics are quantized by using a multi-scale entropy analysis algorithm, and the adaptability of the equalization system to signals with different complexities is enhanced.

The invention provides a multi-level PDN modeling optimization method and system based on advanced packaging, and belongs to the technical field of electrical packaging design, and the method comprises the steps: in multi-level packaging including a chip level, a packaging substrate level and a PCB level, under the condition that actual electromagnetic parameters, power supply layout, wiring topology and the actual length of a power supply loop of materials are considered, the actual length of the power supply loop is calculated; obtaining a PDN model for completing voltage stability and power supply capability under each level; through a three-dimensional loop path mapping algorithm and a target impedance rule, obtaining a PDN model of stable power supply of a power supply network in a full frequency band under different levels; obtaining a plurality of PDN optimization models under each level; and inputting one model under each level into the simulation tool at the same time to obtain an optimal PDN model under each level. The invention aims to solve the problem that only the mutual influence between electronic devices in the PDN model of each layer is considered when the PDN model is carried out on a PCB (Printed Circuit Board), a semiconductor and a chip.

The invention discloses a method and equipment for realizing mouse and virtual key control based on an inertial measurement unit, and a computer readable storage medium. The method comprises the following steps: acquiring original three-dimensional motion data of the inertial measurement unit to generate a standard motion feature flow; forming screen key layout information according to the screenshot of the current active application program; determining an inferred running state of the current active application program to obtain an effective virtual key set containing function annotations; determining a current effective interaction mode according to the updated human-computer interaction situation information, the updated current application program inference operation state and a user input instruction; and selecting a mapping algorithm to process the standardized motion feature flow according to the currently effective interaction mode to generate at least one of a mouse cursor movement instruction, a mouse key instruction and a virtual key operation instruction. The method has the advantage that the operation efficiency and the user experience of IMU-based mouse control in multiple scenes are improved.

The invention relates to the technical field of land resource management, in particular to a land stock index management method based on data analysis. The method comprises the following steps: establishing a cross-data-source data sharing mechanism through a block chain technology, and obtaining multi-source land data; performing natural resource, planning and building information fusion on the multi-source land data based on a knowledge graph to obtain a geographic space semantic network; performing multi-scale space-time clustering on the geographic space semantic network through a self-organizing mapping algorithm, and performing key feature capture of land utilization change based on an attention mechanism to obtain land utilization change feature data; and performing land utilization mode identification according to the land utilization change characteristic data to obtain a land utilization dynamic characteristic spectrum. Through a multi-agent system and a hierarchical reinforcement learning algorithm, a complex land utilization decision process can be simulated, and an optimal decision scheme is realized.

The invention discloses an industrial smart energy multi-energy evaluation visualization system and method, and relates to the technical field of energy big data visualization crossover, and the method comprises the steps: collecting and preprocessing multi-source heterogeneous data, and generating space-time aligned high-dimensional energy data through a space-time hash coding method; based on the three-dimensional manifold coordinate model, converting equipment energy efficiency parameters into an equivalent energy mass field, and through an energy field reconstruction and geometric optimization method, generating a curved manifold space and identifying an optimal transmission path and a distortion strength cloud picture; and based on the distortion strength cloud picture, generating a thermodynamic color gradation through a thermodynamic color gradation mapping algorithm, rendering three-dimensional gradient field distribution of the equivalent energy mass field by adopting a ray tracing method, and generating a visual energy evaluation interface. According to the method, space and time hash codes are generated through a space-time hash coding method, the equipment-grid mapping relation is established in combination with GeoHash coding, and accurate space-time alignment of multi-source heterogeneous data is achieved.