102 results about "Three dimensional matrix" patented technology

The invention relates to the field of methane change dynamic traceability analysis, and discloses a methane change dynamic traceability analysis and early warning system based on artificial intelligence, and the system comprises a data collection module which collects methane concentration data, constructs a two-state three-dimensional monitoring network, and calculates a relative standard deviation; the multi-source analysis module is used for merging calibration environment data, generating a three-dimensional matrix, iteratively updating a class cluster mean value and judging whether a burst leakage traceability process is triggered or not; capturing a time sequence dependency relationship, adding abnormal data optimization, analyzing and triggering residual drive and retraining; the anomaly recognition module is used for constructing a four-dimensional source feature matrix and dynamically adjusting the source feature weight; constructing an observation data matrix, and solving the contribution proportion of each source to the methane concentration; iteratively optimizing the source intensity parameter until convergence; and the early warning response module is used for dynamically updating a historical residual mean value and a standard deviation, judging a response level, reversely tracking an air mass track, positioning a potential emission source coordinate, and triggering a corresponding early warning response if an abnormal degree condition is met.

The invention belongs to the technical field of building project management, and particularly relates to a building curtain wall assembly management technology, in particular to a building engineering project management intelligent system and method. A three-dimensional matrix including component identification, material consumption, a planned entering time window and a material sensitivity label is constructed based on a component entering plan; meanwhile, a construction site space model is established, the occupation state of a three-dimensional matrix simulation material storage yard is loaded in the model according to a component entering plan, and component entering is dynamically optimized by comprehensively considering storage yard space overlapping and meteorological adaptability factors in combination with meteorological prediction data in an assembly time window; prejudgment and adjustment of the assembly plan before implementation are realized, and the change frequency in the actual execution process is effectively reduced, so that the waste of manpower and material resources is remarkably reduced, and the stability and efficiency of a construction organization are improved.

This method is applicable to the technical field of bridge construction and provides a method for real-time monitoring and evaluation of the force-bearing state during the casting process of a steel-pipe concrete arch bridge. The solution involves identifying environmental background points in the RGB three-dimensional matrix for the entire bridge within the range between the maximum and minimum RGB values ​​in the local RGB three-dimensional matrix for the steel pipe, representing environmental background temperature points in the temperature information matrix, and identifying concrete pouring points based on whether the unit matrix condition for the temperature of the steel dome pipe is met. The system also obtains the horizontal axis of the pixel at the center of the poured liquid surface in the left and right half arches in a Cartesian coordinate system, divides the entire arch rib to be poured into 2n equal parts, and calculates the cross-sectional displacement response of each structure based on the cross-sectional displacement caused by the load action of each segment. This allows for real-time, efficient, and accurate observation of the difference in concrete liquid surface level on both sides, allowing for the structural response during pouring to be determined and reducing the construction risk of arch bridges.

The invention discloses a medicine supply chain data management system and method based on data analysis, and relates to the technical field of data analysis. The system comprises a demand urgency evaluation module, an inventory authenticity verification module, a transportation path reliability evaluation module and an optimal allocation scheme screening module. According to the method, the demand urgency score is calculated by collecting the medical resource and material consumption data of the demand point; screening adaptive warehouses and verifying the authenticity of the inventory; evaluating the reliability of the transportation path; and a three-dimensional matrix is constructed, a comprehensive score is calculated through dynamic weighting, and an optimal'demand point-warehouse-path 'combination is screened. According to the invention, quantitative decision and global cooperation of emergency material allocation are realized, the response efficiency and accuracy are improved, and the method is suitable for material guarantee in public health emergencies.

The invention relates to the technical field of power communication network fault diagnosis, in particular to a power communication network fault intelligent diagnosis method based on dynamic topology simulation. The electric power communication network fault intelligent diagnosis scheme is implemented by six steps: firstly, collecting physical layer, protocol layer and topological data, and constructing an equipment-time-performance index three-dimensional matrix; decomposing the matrix to calculate a stability index, and primarily judging an abnormal time period and an abnormal area; mapping a physical topology, and accurately positioning a fault area by using a dynamic convex hull and a ray algorithm; extracting historical data to generate a characteristic curve, and matching a sample library to identify a fault type; the theoretical and actual parameters are iteratively compared to verify the reliability; and finally generating a report and matching a repair strategy. Rapid positioning, accurate identification and reliable diagnosis of faults are achieved, the defects of static analysis, data splitting and verification deficiency in the prior art are overcome, and the operation and maintenance efficiency and the safety level of an electric power communication network are improved.

An approach is provided for partnership optimization. Using a supervised machine learning model, a categorized profile of partners is generated based on feedback from clients and past performances of the partners. The categorized profile indicates strengths of the partners. A network graph is generated based on data about interactions between the partners and clients and the categorized profile. The network graph has nodes representing the partners and the clients and edges representing connections between the partners and the clients. Using the categorized profile and the network graph, a three-dimensional model is generated and represented by a three-dimensional matrix of cells. A given cell represents a part of a project and includes constraint(s) of the project. Using a machine learning algorithm based on Thistlethwaite's algorithm, the model is solved to optimally match the constraint(s) with strength(s) of partner(s) and strength(s) of connection(s) between the partner(s) and client(s).

The invention discloses a power distribution network self-healing strategy generation method and system which are used for solving the technical problem that when an existing power distribution network self-healing strategy generation method faces a fault, simple label matching is carried out only according to a fault type and a line basic structure, and the rapid power restoration quality of a power distribution network is poor. The method comprises the following steps: acquiring surface temperature distribution data of power distribution network equipment and abrupt change high-frequency transient signals of power distribution line nodes; constructing a dynamic topological graph of the power distribution network, and constructing a dynamic three-dimensional matrix according to the dynamic topological graph of the power distribution network, the surface temperature distribution data of the power distribution network equipment and the abrupt change high-frequency transient signals of the power distribution line nodes; generating a plurality of priority self-healing strategies according to a preset basic strategy library, the power distribution network optimization function and the power distribution network constraint conditions; and based on a fuzzy analytic hierarchy process, screening each priority self-healing strategy by adopting a power distribution network optimization function according to the dynamic three-dimensional matrix, and determining a target power distribution network self-healing strategy.

The invention discloses an identity authentication method based on a secure computer, which relates to the technical field of computer security, and comprises the following steps: deploying an authentication module, and pre-burning an excitation-response pair library of a physical unclonable function; chaotic mapping parameters are randomly initialized, and a chaotic sequence is generated through improved Logistic mapping; sending random excitation to the PUF to obtain an original response, segmenting the original response, and mixing the segmented original response with the chaos sequence; the confusion response is recombined into a three-dimensional matrix, nonlinear diffusion is achieved through a rotation transformation formula, and then the confusion response is flattened into a final registration response; after the user submits a user name, the system generates a random challenge and a current timestamp; calculating a first authentication factor based on the registration response and the timestamp, and recursively generating a factor chain; and the server repeatedly generates a factor chain for matching, updates a registration response if the matching is successful, and triggers a locking mechanism if the matching is failed. According to the chained dynamic authentication method based on PUF response chaos confusion, the dynamic unpredictability of each authentication session can be realized.

The invention discloses an image encryption method based on RNA extended coding and quantum chaos, and belongs to the field of information encryption, and the method comprises the steps: obtaining a plaintext image, coding the plaintext image to obtain initial coding information, and generating a secret key according to the initial coding information; according to the secret key, calculating by adopting a chaos equation to obtain a pseudo-random sequence, and transforming the pseudo-random sequence to obtain a sequence required by encryption; the method comprises the following steps: acquiring a three-dimensional matrix of a plaintext image, decomposing the three-dimensional matrix into a first high-bit matrix and a first low-bit matrix, carrying out block scrambling and RNA dynamic coding on the first high-bit matrix according to a sequence required by encryption, carrying out XOR calculation on the first low-bit matrix according to the sequence required by encryption, and carrying out XOR calculation on the first low-bit matrix according to the sequence required by encryption; carrying out cross iterative diffusion and synthesis on the matrix subjected to RNA dynamic coding and the matrix obtained by XOR calculation to obtain a color ciphertext image; the security and efficiency of information encryption can be realized.

The invention discloses a molecular dynamics modeling method and system for a porous medium, and relates to the technical field of molecular dynamics modeling, and the method comprises the following steps: recognizing pore voxel regions and non-pore voxel regions based on a three-dimensional matrix, and carrying out the boundary division of a plurality of non-pore voxel regions, and obtaining a boundary layer anchor point pool and a non-boundary layer anchor point pool; dividing the boundary layer anchor point pool and the non-boundary layer anchor point pool into a plurality of grid units, and filling the anchor points in the grid units through the to-be-filled molecules based on the target filling number and the target mask value; randomly rotating the current to-be-filled molecule, and if the distance between the current to-be-filled molecule and the placed atom is smaller than the corresponding minimum distance threshold value, abandoning the current placement; and after filling of all molecules is finished, counting space absolute coordinates of all atoms, and outputting a coordinate file. According to the method, accurate and non-overlapping placement of molecules in a complex pore structure is realized, and establishment of a porous medium complex random pore microcosmic molecular dynamics model can be realized.

The invention relates to the technical field of image encryption, and discloses a cross-channel image encryption method using fractal and chaos, a terminal and a medium. The method comprises the following steps: constructing a two-dimensional chaotic system, and obtaining two chaotic sequences with the same length; splicing the M * M * 3 plaintext color images P into an M * 3M two-dimensional image P1; generating a diagonal fractal sorting matrix F of which the dimension is greater than or equal to P1 based on diagonal transformation; the first M * 3M elements of the matrix F are taken and sorted, an index matrix F1 is obtained, the P1 is subjected to index scrambling through the F1, and a first scrambling image P2 is obtained; remodeling the chaos sequence xseq into an M * 3M two-dimensional matrix X, sorting the M * 3M two-dimensional matrix X to obtain an index matrix F2, and performing index scrambling on P2 by using F2 to obtain a second scrambling image P3; and remodeling the P3 into a three-dimensional image P4, remodeling the chaos sequence yseq into an M * M * 3 three-dimensional matrix Y, and carrying out V-like cross-channel diffusion on the P4 by using the Y to obtain an encrypted image PC. According to the invention, the problem of high inter-channel correlation caused by channel separation is effectively relieved.

The application relates to the fields of information security and image processing, and discloses a multi-image parallel encryption processing method based on an improved chaotic mapping, which comprises the following steps: separating and stacking each color channel of multiple images to be encrypted to construct a three-dimensional pixel matrix; extracting a matrix hash digest to be converted into a sub-key; inputting the sub-key into an improved chaotic mapping model of a historical state variable to iteratively generate a scrambling and diffusion sequence; performing sorting scrambling on the three-dimensional matrix in multiple orthogonal dimension sections by using the sequence; mapping the sequence into a shift step length to perform a cyclic shift and a bitwise XOR linkage diffusion on the pixels; and finally, outputting ciphertext images by segmentation. The application breaks the physical isolation of a single image to realize spatial depth mixing by constructing a three-dimensional matrix and performing cross-dimension scrambling; the chaotic dynamics degradation under limited precision is overcome by means of a historical state delay; and the efficiency of multi-image encryption and the system attack resistance are improved by using a shift and XOR linkage to realize bit-level depth confusion.

The present application discloses a method and device for predicting the health status of a battery pack. The method constructs a three-dimensional matrix of the battery pack based on the collected historical data of multiple cells in the battery pack, performs sliding window processing on the three-dimensional matrix of the battery pack, and generates model input data; determines a battery pack health status prediction model, wherein the battery pack health status prediction model includes a SE‑TCN network, a Performer encoder, and a spatiotemporal fusion layer; and inputs the model input data into the battery pack health status prediction model to obtain a predicted value of the health status of the battery pack. The present application captures the time-dependent characteristics of the time series data of multiple cells in the battery pack and the global dependency between the cells, and fuses the time series features with the spatial correlation features, so that the model can capture the complex interactive relationships between multiple cells, thereby greatly improving the accuracy and robustness of the battery pack health status prediction.

The application provides a cylindrical array sonar system and a target detection method based on high-resolution beam forming. The method comprises the following steps: converting a beam forming weight vector of a received sound wave signal into a Kronecker product, combining a joint probability density model to construct a negative log-likelihood function, and optimizing a vector in an azimuth dimension and an elevation dimension through a preset direction constraint condition to form a high-resolution beam; performing correlation analysis on echo signals reflected by a target at different azimuth angles and elevation angles and on transmitted sound wave signals at different time delays; constructing a three-dimensional matrix containing a distance, an azimuth angle and an elevation angle according to a correlation analysis result, performing normalization processing on the three-dimensional matrix to eliminate signal intensity differences, and outputting a target detection positioning result. Through the combination of Kronecker integral decomposition and three-dimensional matrix modeling, the application realizes high-resolution joint positioning detection of a target in an azimuth angle, an elevation angle and a distance dimension, effectively eliminates signal intensity differences, and improves positioning accuracy.

The invention discloses a power transmission line traveling wave fault positioning method and system based on data analysis, and relates to the technical field of big data analysis, and the method comprises the steps: firstly collecting fault original records, temperature, humidity and weather states, and building a historical library; carrying out time-frequency domain conjoint analysis on the traveling wave signal, and calculating a phase difference and a time difference; the signals are adaptively decomposed to different frequency bands to calculate fractal dimensions, and advanced features are extracted in combination with a deep convolutional neural network; associating the phase difference, the instantaneous electric field intensity and the magnetic field rotation direction to construct a three-dimensional matrix rotation graph structure, and forming a high-dimensional feature vector by using a graph attention network; and calculating a fault posterior probability according to the high-dimensional vector, dynamically adjusting a threshold value according to an environment parameter, and generating an adversarial network virtual sample to match a fault type when the probability is insufficient. The system comprises a data acquisition module, a time-frequency analysis module, a feature extraction module, a feature association module and a fault determination module, all the modules cooperate to realize data acquisition, feature analysis and fault positioning, and the positioning reliability is enhanced.

The invention discloses a multi-channel injection system and method for an ultra-large rock core hydraulic fracturing experiment. The system comprises a three-dimensional injection array module, a modular injection panel, a variable impedance regulation and control unit, a dual-medium consistency injection module and a fluid-solid coupling compensation control unit. The method comprises the following steps: constructing a three-dimensional matrix type injection network, preparing sand-carrying fluid with uniform concentration, configuring initial fluid impedance to realize multi-channel flow matching, starting synchronous injection, monitoring pressure and stress signals in real time, and dynamically adjusting the impedance of each channel to compensate the heterogeneity of the rock core. And finally, a uniform and stable volumetric pressure field is formed and maintained in the ultra-large rock core, and meanwhile, the concentration deviation of the sand-carrying fluid between the channels is controlled within a preset threshold value. The technical problems that a pressure field in a large-scale rock core is not uniform, proppant conveying is not stable and multi-channel interference is not stable are solved, and the method is suitable for complex crack expansion and proppant laying mechanism research.

The invention discloses a two-dimensional wave field reconstruction method based on compressed sampling, and belongs to the technical field of signal processing and sensors. According to the method, original time domain signals of a two-dimensional wave field are expressed as a three-dimensional matrix, random sampling is carried out through a Bernoulli distribution random sampling matrix, after the three-dimensional matrix is reduced into a two-dimensional matrix, a group sparse perception convolutional neural network is constructed to serve as a non-convex optimization solver, a real part and an imaginary part of a complex signal are processed, group sparse constraint is applied, and a non-convex optimization solver is constructed. And reconstructing the basis coefficient matrix to obtain an original signal reconstruction result, and finally raising the dimension to restore the original signal into a three-dimensional wave field. According to the method, the sampling rate is reduced, the reconstruction precision is improved, large-scale data set training is not needed, each training is an independent reconstruction process, and the method is suitable for the fields of acoustic imaging, seismic exploration and the like.

The invention provides a cylindrical array sonar system and a target detection method based on high-resolution beam forming. The method comprises the steps of converting a beam forming weighted vector of a received sound wave signal into a Kronecker product, constructing a negative logarithm likelihood function in combination with a joint probability density model, and optimizing vectors of an azimuth dimension and a pitching dimension through a preset direction constraint condition so as to form a high-resolution beam; correlation analysis is carried out on echo signals reflected by the target at all azimuth angles and pitch angles and transmitted sound wave signals under different time delays; and according to a correlation analysis result, constructing a three-dimensional matrix including the distance, the azimuth angle and the pitch angle, carrying out normalization processing on the three-dimensional matrix so as to eliminate a signal intensity difference, and outputting a target detection positioning result. According to the invention, through combination of the Kronecker integral solution and three-dimensional matrix modeling, high-resolution joint positioning detection of the target in the azimuth angle, the pitch angle and the distance dimension is realized, the signal intensity difference is effectively eliminated, and the positioning precision is improved.

The invention relates to a method (100) for compressing an image stack (PIL) comprising N images, each image being represented by a two-dimensional data matrix (U, V), each cell (u, v) of the matrix comprising a set of values representing a pixel of the image, which method (100) comprises the following steps: - stacking (110) the images in a three-dimensional matrix (U, V, W) comprising N planes W1-Wn in the dimension W, each plane Wi in the dimension W corresponding to an image, and each cell (u, v) in the plane Wi comprising a set of values representing a pixel of the image; and - compressing (120) the stack of images from the three-dimensional matrix, using a dictionary compression algorithm. The invention also relates to a computer program, a device, a system and a vehicle implementing such a method.

The embodiment of the present invention discloses a correction method and system for a gas volume flow measurement instrument for a flash evaporation process, which belongs to the field of oil refining and chemical industry. The method includes: obtaining the gas properties of the flash evaporation mixed gas after the composition changes at different temperatures and pressures of the flash evaporation equipment; based on the obtained gas properties, forming multiple three-dimensional matrix data about temperature, pressure, and gas properties; using the obtained three-dimensional matrix data, obtaining the gas properties of the flash evaporation mixed gas at the actual temperature and pressure of the flash evaporation equipment as calculation parameters of the gas volume flow measurement instrument; correcting the measurement results of the gas volume flow measurement instrument according to the calculation parameters to obtain a corrected flow measurement value. This method corrects the instrument measurement error caused by the composition change, and improves the measurement accuracy of the volume flow measurement of the mixed gas generated by the flash evaporation process at a low cost.

The invention discloses a porosity prediction method based on time-frequency characteristics, and belongs to the field of geological exploration. The method comprises the following steps: firstly, preprocessing each kind of logging data to generate a logging data curve; extracting spatial domain features and frequency domain features of the logging data curve and fusing the spatial domain features and the frequency domain features to obtain a fused feature vector; a three-dimensional matrix is constructed according to the fusion feature vectors of the multiple kinds of logging data, and then the three-dimensional matrix is expanded to obtain a two-dimensional matrix; and finally, respectively inputting the three-dimensional matrix and the two-dimensional matrix into two input ends of a porosity prediction model so as to obtain the porosity. According to the method, by fusing the time-frequency features and combining a specific model input mode, the porosity prediction precision is effectively improved.

The invention relates to a battery SOC prediction algorithm based on E3D-LSTM and battery cell position structure characteristics. The method comprises the steps that a three-dimensional matrix is established according to the position structure and battery parameters of batteries in a battery pack to serve as input data; performing standardization processing on the input data, and constructing a training set, a verification set and a test set by using the processed input data; constructing a battery SOC prediction model based on E3D-LSTM, and determining basic structure parameters of the model; and training, verifying and testing the battery SOC prediction model based on the E3D-LSTM by using the training set, the verification set and the test set. Through the prediction algorithm, prediction can be carried out under extra conditions that errors do not need to be accumulated, a system does not need to be in an open circuit state and the like, and in addition, the prediction method further has the advantages of being more comprehensive in applied original information, more accurate in prediction result and the like.

The invention belongs to the technical field of material science foundation, and discloses a single twinborn system dominated twinborn transmission probability prediction method. According to the method, aiming at the condition that a single twin system is started preferentially under specific texture and force field conditions, the uniqueness of the twin system is limited and activated, and a three-dimensional matrix expression system of specific twin system spatial orientation is constructed. And based on a judgment rule that twin crystal faces and twin directions of the two crystal grains are parallel, calculating the minimum orientation difference capable of realizing parallel twin systems among the crystal grains. According to the method, the twinborn orientation difference is provided as a key physical quantity for quantifying the twinborn transmission capability, and the regulation and control mechanism of single twinborn system activation on local stress redistribution is disclosed by eliminating the interference of a non-activated twinborn system. The method is applicable to a twin-dominated deformation system at low temperature or high strain rate, and provides a micromechanical basis for optimizing strain coordination at the grain boundary.

To provide a real-time monitoring and evaluation method of a force bearing state in a placing process of a steel pipe concrete arch bridge applied to the technical field of a bridge construction.SOLUTION: The real-time monitoring and evaluation method includes: identifying an environmental background point in an RGB three dimensional matrix of the whole bridge by using a range between a maximum value and a minimum value of RGB in a local RGB three dimensional matrix of a steel pipe; describing an environmental background temperature point in a temperature information matrix and identifying a concrete placing point according to whether or not a unit matrix condition of a multiple of a dome steel pipe temperature is met; acquiring a horizontal axis of a pixel at the center of a placed liquid surface of right and left half arches in an orthogonal coordinate system; and dividing the whole arch rib to be placed into 2n equal parts, and calculating each cross-section displacement response of a structure by referring to the horizontal axis of the pixel at the center of the placed liquid surface of the right and left half arches from the cross-section displacement from the load action of each segment. Therefore, a liquid surface difference of concrete on both sides can be observed in real time, efficiently and accurately, so as to obtain the structural response in a placing state and reduce the construction risk of the arch bridge.SELECTED DRAWING: Figure 1

The application discloses an Alzheimer's disease prediction method and system based on a millimeter wave radar. The method comprises the following steps: reorganizing original data of human gait collected by the millimeter wave radar to obtain a three-dimensional matrix block, and operating the three-dimensional matrix block to obtain multi-modal data; performing feature extraction, alignment and fusion on the multi-modal data and text data to obtain reweighted multi-modal data; training a GLM by using the multi-modal data and the text data to obtain a trained GLM, and inputting the reweighted multi-modal data into the model to obtain signal semantic features; inputting the signal semantic features and random noise into a diffusion model and training the diffusion model to obtain a trained diffusion model; and generating an image result by using the trained diffusion model, and combining a text prediction result to assist a user in predicting Alzheimer's disease. The application can combine the advantages of millimeter waves and multi-modal large models, improve the robustness and generalization ability of the model, and improve the early prediction ability of Alzheimer's disease.

The invention relates to the technical field of data management, in particular to a digitization-based operation data management method and system, which comprises a business processing layer and a business application layer, acquires multi-source data, performs preprocessing and format conversion on the acquired multi-source data to obtain standardized data, and simultaneously, performs operation data management on the basis of a set trigger condition. Performing relation mining on the standardized data based on the constructed knowledge graph model, and performing dynamic early warning at the same time; performing double-board collaborative analysis based on the standardized data, and performing task intelligent scheduling; early warning and visual display are carried out on a three-dimensional matrix of time, space and responsibility until a task is completed, unified analysis can be carried out on multi-source data, the multi-dimensional dynamic analysis capability is achieved, and the intelligence of decision making is ensured.

The invention discloses a method and system for realizing chip testing, and relates to the technical field of chip testing, and the method comprises the steps: assembling a chip testing daughter board, loading a plurality of chips to be tested in a chip loading area, configuring a switch matrix, a decoder and an activation control unit, and generating a chip mapping matrix; selecting a single chip to carry out a high-temperature operation lifetime test, monitoring the power consumption stability of the chip in real time, and calculating the power consumption deviation of the chip; executing a logic function test, a time sequence test and a multi-channel voltage output test, evaluating output consistency, and generating chip function test data; based on the chip power consumption deviation and the chip function test data, the entropy-based risk assessment method is adopted to calculate the failure probability of the chip to be tested, the failure probability distribution is analyzed by constructing a failure mechanism decision model, and the power consumption stability test and the function test of the chip to be tested are optimized. According to the method, the chip mapping matrix is generated through three-dimensional matrix operation, so that the test configuration time is shortened, and the test configuration complexity is reduced.

The invention discloses a water conservancy risk prediction method based on evolution characteristics, and belongs to the technical field of water conservancy projects. The method comprises the following steps: dividing a to-be-detected area into a plurality of grids, collecting and normalizing surface and internal water conservancy risk factors of each grid, constructing a surface and internal evolution incidence matrix, extracting collaborative strength and total evolution strength, and splicing to form an evolution characteristic matrix; determining an evolution characteristic transfer coefficient based on the distance between the to-be-predicted grid and the neighborhood grid, and obtaining a neighborhood evolution characteristic transfer matrix; and inputting the multi-moment evolution characteristic three-dimensional matrix and the neighborhood evolution characteristic transmission three-dimensional matrix into a water conservancy risk prediction network, and outputting a grid water conservancy risk score. According to the method, high-precision prediction of the water conservancy risk is realized by capturing a risk factor space-time evolution rule and a neighborhood transfer effect.

The invention discloses a knowledge base intelligent retrieval and knowledge reasoning method and system oriented to city styles and features, and the method comprises the steps: collecting multi-source city data of a preset city, and carrying out the preprocessing of the multi-source city data; constructing a three-dimensional matrix based on style stability, style freshness and development kinetic energy through the multi-source city data, dividing city modes according to the three-dimensional matrix to obtain mode data, and constructing a style topology network according to the multi-source city data and the mode data; a graph neural network is adopted to carry out community detection on the text topology network to identify a style and appearance cluster, the style and appearance cluster is evaluated according to a four-quadrant matrix to obtain a text value degree, and style and appearance causes are deduced according to the text topology network; and constructing an intelligent retrieval and knowledge reasoning model of the urban style and appearance knowledge base according to the value degree of the veins, optimizing the intelligent retrieval and knowledge reasoning model of the urban style and appearance knowledge base according to the causes of the style and appearance, and outputting a retrieval reasoning result.