201 results about "Differential analysis" patented technology

The invention relates to the technical field of financial data processing, in particular to a multi-source heterogeneous fund data processing method and system, and the method comprises the steps: recording source information through building a data source registry, and marking a unique identifier for data; performing differential analysis on the fund data in different formats to generate standardized column type storage data; traversing column type storage data to extract statistical characteristics, performing field classification through metadata analysis and financial dictionary matching, analyzing business connotations of fields difficult to classify in combination with a localized large language model, and mapping the business connotations to a header fusion knowledge graph; generating a mapping rule from the source field to the enterprise-level data model by applying a rule engine template on the basis of field classification and semantic recognition results; converting the data structure according to the mapping rule and executing standardization processing; the quality is further optimized through data cleaning; and finally, the data are verified, standardized fund data supporting data traceability are output, and the strict requirements of financial supervision application are met.

The invention discloses a river sediment multi-parameter sensing self-adaptive sampling method and system, and relates to the technical field of environment monitoring, and the method comprises the following steps: S1, synchronously collecting the pH value, electrochemical potential, heavy metal binding state proportion, water body flow velocity and hydrodynamic parameters of sediment through a sensing device, and establishing a multi-parameter response baseline; and S2, based on the multi-parameter response baseline, collecting monitoring data in real time and executing differential analysis, and identifying a high-risk time period when the pH value change rate exceeds a threshold value and the heavy metal binding state proportion fluctuates. By constructing a multi-parameter response baseline and a linkage recognition mechanism, early sensing and accurate sampling of heavy metal release are realized, a closed-loop response system is constructed by combining chemical form analysis, self-correction and data feedback optimization recognition model, and the accuracy and intelligent level of pollution monitoring are improved.

The invention relates to the technical field of bridge safety monitoring, and comprises a bridge safety monitoring analysis system based on big data, and the system comprises a data collection processing module, a manifold feature dimension reduction module, an entropy change partition evaluation module, a health state dynamic analysis module, and a bridge safety early warning module. According to the method, a bridge measuring point topological relation matrix is established, measuring point spatial distribution characteristics are analyzed, spatial relevance of a bridge structure is reflected, measuring point local curvatures are calculated, a local curvature matrix is established, a neighborhood similarity matrix is combined, low-dimensional projection transformation is executed, local topological consistency of data is kept in the dimensionality reduction process, an entropy change partition matrix is established, and the spatial relevance of the bridge structure is reflected. The health states of different structural parts of the bridge are subjected to differential analysis based on mechanical characteristics, the entropy change trend and damage probability of a measuring point are calculated, and the overall safety state level of the bridge is judged through a damage risk threshold, so that the local damage severity of the bridge can be comprehensively considered in safety assessment, and the stability and adaptability of safety state judgment are improved.

The invention relates to the technical field of traditional Chinese medicine drying process automatic control, and discloses a traditional Chinese medicine low-temperature belt type drying control system and method. A closed-loop control strategy integrating multi-point moisture sampling, trend analysis, target and fluctuation control, temperature feedforward, belt speed feedback, vacuum collaboration, stability criterion freezing and tail detection archiving is provided. A plurality of sampling points are arranged along the conveying belt, moisture is monitored in real time, and time sequence differential analysis is combined, so that static moisture content deviation is captured, the drying rate and trend are sensed dynamically, and multi-channel coordinated adjustment of temperature, belt speed and vacuum is achieved. The system is provided with a safety boundary and a minimum resolution, and it is guaranteed that control operation can be executed and is accurate. The stable interval criterion effectively avoids frequent invalid adjustment, and the tail multi-point detection and whole-course data archiving provide a solid basis for quality tracing.

The invention discloses a fire-fighting pipe network pressure dynamic monitoring method and system combined with the Internet of Things and a medium, and relates to the technical field related to pressure monitoring, and the method comprises the steps: deploying a pressure sensor and an auxiliary sensor at a fire-fighting pipe network monitoring node, and building a topology sensing structure through wireless Internet of Things communication; carrying out adaptive sampling adjustment and then establishing a node sampling data set; transmitting the data to a multi-time window pressure evolution model to execute sliding differential analysis, and calculating an abnormal trend index; configuring a neighborhood broadcast request and performing broadcast consistency verification; abnormal trend index enhancement correction is carried out, and group resonance detection is carried out to establish linkage cooperative early warning; and a fire-fighting pipe network pressure abnormity early warning signal is reported. The technical problems that in the prior art, dynamic abnormal data of the fire-fighting pipe network are difficult to sense in real time, cooperation is lacked, response lags, and pressure monitoring accuracy and reliability are poor are solved, and the technical effects that real-time and accurate dynamic monitoring is achieved, and the pressure monitoring accuracy and reliability of the fire-fighting pipe network are improved are achieved.

The invention provides a soil pollutant detection system and method, and the method comprises the steps: carrying out the continuous spectrum compensation of a target compensation region of a soil Raman spectrum signal of a to-be-detected soil sample, and obtaining soil Raman spectrum compensation data; identifying a background baseline response interval in the soil Raman spectrum compensation data through iterative differential analysis, and segmenting the soil Raman spectrum compensation data into a plurality of peak-containing spectrum segments according to the background baseline response interval; determining a signal fidelity constraint of the soil Raman spectrum signal during smooth iteration; recognizing a local background baseline corresponding to each peak-containing spectrum section based on an incremental smooth window in combination with signal fidelity constraint, and determining a clean characteristic spectrum according to all background baseline response intervals and the local background baselines; and identifying according to the clean characteristic spectrum to obtain the pollutant concentration of the to-be-detected soil sample. According to the technical scheme provided by the invention, adaptive fidelity extraction can be carried out on the pollutant characteristics under the condition of the violently changing background base line.

The invention discloses a switch cabinet electric arc light detection method and system based on multispectral fusion, and relates to the technical field of electric power system intelligent detection, and the method comprises the following steps: S1, building a cross-spectrum unified time reference, and carrying out the synchronous comparison of an infrared light signal, a visible light signal and an ultraviolet light signal, extracting a temperature transition trigger feature and a strong light disturbance spectrum feature, and generating a time synchronization deviation vector; and S2, constructing an anti-fact spectrum playback model based on the time synchronization deviation vector, generating a shadow spectrum sequence, positioning an infrared response threshold lifting reason through energy difference analysis, calculating a spectrum overlapping risk interval and duration, and outputting a threshold disturbance distribution diagram. According to the method, infrared anomalies are identified through cross-spectrum time alignment, anti-fact playback and differential analysis, channel recovery is guided in combination with springback prediction and time sequence correction, and a spectrum broken chain window is constructed through dislocation sampling and phase regulation and control, so that the accuracy and the anti-interference capability of arc identification are effectively improved.

The invention provides a river sediment physical habitat evolution identification method, device and system and a medium. The method comprises the following steps: acquiring a multi-temporal remote sensing image and hydrological data (flow Q, water level Zw and slope S), screening and other hydrological condition image pairs; extracting a water surface range, and calculating the average width B of the main groove; deducing the average water depth h by using a Manning formula, and calculating the riverbed elevation zbed by combining the Zw; the difference value delta zbed of zbed in different periods is calculated, and the substrate state is judged according to the difference value delta zbed and a threshold value epsilon; and performing segment processing along the center line to output a spatial distribution result. On-site measurement is not needed by relying on conventional data, and consumption is reduced; water level interference is eliminated through equal hydrological condition matching, and comparability is ensured; water depth inversion and differential analysis directly reflect scour deposition and quantitatively reveal rules; long-distance automatic processing improves space-time coverage capability and precision, and provides a basis for river regulation, ecological restoration and drainage basin management.

The invention discloses an unplanned secondary operation decision support method and system based on EMR analysis. According to the method, firstly, multi-source EMR data are collected in real time through an HL7 FHIR standardized interface, differential analysis is conducted through a time sequence analysis algorithm and a BioBERT model fused with a medical knowledge graph, and standardized clinical indexes are generated; secondly, the indexes are matched with an unplanned secondary surgery thematic knowledge graph in real time, multi-path probabilistic reasoning is carried out based on a Bayesian network, and a risk conclusion with confidence and a reasoning chain are output; and generating a structured report including risk early warning, core basis, possible reasons and processing suggestions, and pushing the structured report in multiple channels. And finally, collecting clinical feedback, optimizing the knowledge graph and the analytical model, and forming a closed loop. According to the invention, dependence on experience of doctors is reduced, and accuracy and timeliness of risk research and judgment are improved.

The invention relates to the field of metal heat treatment and industrial automation control, in particular to a normalizing air cooling system of a metal continuous heat treatment furnace, and particularly relates to an ideal field reconstruction module which is used for obtaining steel plate parameters and environmental parameters, introducing a thermodynamic phase change dynamics principle to calculate a phase change latent heat release process and constructing an ideal pure temperature flow field matrix; the fault simulation generation module is used for calling a fault mechanism model to convert an equipment fault into a parameterized interference coefficient matrix, and superposing the parameterized interference coefficient matrix to an ideal matrix to generate a theoretical damaged state matrix; the double-track differential analysis module is used for collecting real-time data to construct an observation matrix, and respectively calculating a first difference between the observation matrix and the ideal matrix and a second difference between the theoretical damaged matrix and the ideal matrix to obtain a real and theoretical difference matrix; the feature coupling judgment module is used for extracting the difference matrix features, calculating the coupling degree, judging that the abnormality belongs to a real fault or environmental noise, and generating an air cooling regulation and control instruction; according to the method, non-linear fluctuation misjudgment is eliminated through phase change latent heat calculation, dual-track differential stripping environment common-mode interference is utilized, and micro equipment abnormity is accurately captured in a noisy environment.

The invention relates to the field of data decision analysis, in particular to a unit internal control management decision method and system based on multi-modal data analysis. The method comprises the following steps: collecting heterogeneous original data streams of a plurality of heterogeneous data sources; performing space-time dimension entropy change differential analysis and multi-dimensional entropy change characteristic mining, performing multi-level semantic analysis on the heterogeneous original data stream, performing layer-by-layer abnormal mode semantic deconstruction, and constructing a precise semantic feature portrait of each abnormal mode; performing multi-target coordination request analysis and dynamic target priority evaluation on the cognitive entropy change reference characteristic spectrum to obtain a coordination request priority; and carrying out maximum decision capacity calculation on the cognitive entropy change reference feature map, and carrying out dynamic optimal decision boundary calculation based on the coordination request priority and the accurate semantic feature portrait so as to generate a dynamic tradeoff constraint range. Through multi-target collaborative decision analysis, the decision target conflict is smoothed, and the decision demand execution efficiency of the user is improved.

The invention belongs to the technical field of electronic search, and relates to a radio reconnaissance method and system based on multichannel parallel processing and intelligent clustering, and the method comprises the steps: carrying out the multi-phase filtering digital channelization processing of a broadband radio signal, so as to obtain adjacent channel sequences with overlapped frequency bands; performing square law detection and constant false alarm detection on each channel sequence to generate an initial pulse description word; establishing a candidate corresponding relationship in adjacent channels based on arrival time similarity and noise consistency, and determining a cross-channel merging relationship according to frequency range continuity and frequency-time relationship slope consistency to generate a complete pulse description word; performing hierarchical clustering sorting based on the arrival angle and the pulse width; and performing multi-stage differential analysis on a clustering result to extract a repetition frequency sequence and determine a repetition frequency type. According to the technical scheme, the stability and consistency of cross-channel pulse merging and sorting results can be kept under the broadband high-density condition, and the radio search processing precision under the complex electromagnetic environment is improved.

The invention relates to the field of quality detection of mechanical parts, in particular to an intelligent recognition system for surface defects of mechanical parts based on deep learning. Comprising a data acquisition module, a differential geometric feature extraction module, a small sample learning module, an automatic labeling module, a data reinforcement learning module, a neural network training module, a defect identification module and a defect quantitative evaluation module. Extracting geometric features including curvature features and differential invariant features; small sample learning is adopted to solve the problem of sample scarcity; the efficiency is improved by utilizing automatic labeling; simultaneously capturing microcosmic details and macroscopic morphology through a multi-scale differential analysis framework; organic fusion of surface image information and depth geometric information is realized; according to the method, the problems of insufficient samples, difficulty in labeling, inaccurate defect evaluation and the like in industrial production are effectively solved.

The application discloses a kind of active fault borehole stratum comparison methods combined with high-resolution logging data, it is related to stratum comparison technical field, comprising: first respectively obtaining test fault region and test bottom layer region;Real-time data acquisition is carried out based on electrical imaging logging, and differential analysis model is established;The differential analysis model is optimized, and the ground fault comparison model is obtained;Active fault borehole stratum comparison method is obtained based on the data in ground fault comparison model;The application is used to solve the problem of low precision and efficiency in the existing active fault borehole stratum comparison method.

The invention relates to the technical field of monitoring and alarming, in particular to an intelligent orthopedic rehabilitation training monitoring system based on multi-modal sensing, which comprises a basic data synchronous acquisition module, a dynamic stiffness differential analysis module, a defensive contraction judgment module and a load boundary dynamic reconstruction module. According to the method, a time sequence is constructed by synchronously collecting joint angle and moment data, an instantaneous dynamic stiffness change trend is analyzed by combining a moment and angle difference value, a Savitz-golay filter is used for carrying out second-order differential processing on dynamic stiffness to capture a stiffness second-order derivative mutation point, and the critical moment when defensive contraction pain occurs to the joint of a patient is recognized. The maximum activity angle upper limit is dynamically reconstructed based on the critical angle and the safety buffering difference value, a control instruction is directly fed back to a driving end to execute reverse braking, crossing from single-position monitoring to multi-dimensional mechanical state sensing is achieved, it is ensured that the activity boundary is automatically adjusted according to real-time physiological feedback of a patient, and the safety performance of the patient is improved. And secondary injury caused by forcibly breaking through a pain threshold value is prevented.

The invention provides a portrait beautifying real-time processing method based on a deep neural network, and the method comprises the steps: carrying out the age classification processing of a face region in a feature map through an initialized age recognition neural network module, analyzing the face age indication features of the face of a user, judging the age group of the user, and outputting an age classification label; performing differentiation analysis on each face age indication feature according to the age classification label, taking a differentiation analysis result as a weight distribution basis, distributing weight coefficients to different face age indication features according to importance degrees, and obtaining face feature vectors for different age groups; and according to an eye processing strategy in the personalized beautification processing scheme, performing refined processing on the eye region, and adjusting eye contour enhancement strength and color saturation parameters according to the age group of the user to obtain image data subjected to eye beautification processing.

The invention provides a power transmission line icing image sharpening method based on visual high and low frequency characteristics, and belongs to the technical field of power transmission line monitoring. Frequency domain feature extraction and guide image restoration are carried out through the frequency domain feature extraction sub-network; performing spatial domain feature extraction and multi-scale expression through the spatial domain feature extraction sub-network; and carrying out joint optimization on the output of the frequency domain feature extraction sub-network and the output of the spatial domain feature extraction sub-network through cross-domain feature fusion connection, and outputting a power transmission line icing clearness image after defogging and snow removal through an image reconstruction module. The method has the advantages that an innovative architecture with cooperation of frequency domain feature separation and spatial domain feature extraction is provided, and the image restoration effect is remarkably improved; the high-frequency component optimizes texture expression through key details, the low-frequency component models global distribution characteristics of non-uniform fog and snow noise based on an improved Transform module, and differential analysis and collaborative optimization of complex degradation features are achieved through combination of the high-frequency component and the low-frequency component.

The invention relates to the technical field of gas detection, and discloses a portable gas chromatograph mine harmful gas detection system and method, the system comprises a chromatographic data processing module, a signal feature extraction module, a chromatographic signal difference module, a dual-channel construction module, a working curve construction module and a harmful gas concentration acquisition module, collecting original chromatographic data, and removing baseline drift and random noise to obtain standard chromatographic data; identifying a baseline interval, inserting signal features according to the time sequence position to obtain a dynamic baseline signal, and performing differential analysis on the standard chromatographic data and the dynamic baseline signal to obtain a net chromatographic signal; selecting a background gas chromatographic peak as an internal reference channel, and taking a preset standard gas response factor as an external reference channel; correcting the response factor of the target harmful gas so as to evolve into a real-time quantitative working curve and obtain harmful gas concentration information; the mine harmful gas detection accuracy can be improved.

The invention relates to the technical field of firmware upgrading, and particularly provides a commercial vehicle remote online differential upgrading method, system, device and medium, a hardware identifier reported by a vehicle-mounted terminal and a current firmware version are received through a cloud server, new and old versions of firmware are automatically matched for difference analysis, and a customized differential package is generated. And the cloud side intelligently selects a transmission strategy according to a network state, and issues a differential packet by adopting a self-adaptive fragmentation and breakpoint resume mechanism. And after the vehicle-mounted terminal receives the data, dynamically evaluating local resources, selecting a merging strategy, integrating the differential package into a new firmware file, and writing the new firmware file into an A / B system partition for standby application. And validity verification is executed before upgrading, so that service continuity and system reliability are ensured. The method significantly improves the upgrading efficiency, reduces the bandwidth consumption, and guarantees the operation stability of the vehicle.

The invention provides a power equipment component detection method and device based on infrared thermal imaging, and belongs to the technical field of power equipment detection, and the method comprises the steps: collecting an infrared thermal imaging image and a visible light image which comprise the global temperature and structure texture information of a power equipment component based on an infrared thermal imaging camera and a visible light camera; inputting the corrected infrared thermal imaging image and visible light image into a semantic segmentation model, extracting and fusing temperature features and appearance features, and identifying different types of components; selecting corresponding temperature indexes and appearance indexes from a pre-constructed database according to the types of the parts, and performing detection; the database configures differentiated detection indexes for different types of components. Therefore, pixel-level accurate identification of the power equipment component is realized by adopting a mode of combining double cameras with semantic segmentation, and the component state detection accuracy is improved through multi-dimensional differentiation analysis.

The invention discloses an iron tower PS pixel point simulation and differential interference deformation monitoring method and system based on three-dimensional point cloud data, and the method comprises the steps: obtaining the point cloud data of an iron tower body structure under a radar coordinate system through a radar distance Doppler positioning method through the three-dimensional point cloud data of the iron tower body structure; identifying pixels containing the iron tower point cloud data in the SAR image as iron tower PS pixel points; constructing a radar scattering weight model based on elevation information of the iron tower point cloud data, and obtaining an iron tower PS pixel point scattering intensity value through weighted summation in combination with a weight adjustment parameter; constructing a complex value of the point cloud data of the iron tower according to the interferogram parameters and a radar scattering weight model, and obtaining a simulation interference elevation phase of the PS pixel point of the iron tower by using complex field summation; differential interferometric phases of iron tower PS pixel points in the interferogram are obtained through difference; and performing statistical analysis on the differential phase map of the iron tower PS pixel point set region in the time sequence interferogram to obtain a deformation result.

The invention relates to the field of network security, and particularly provides a security cooperation system and method in a hybrid cloud environment. The system comprises a unified security management module, a security solution cooperation module and a security function module. The unified security management module analyzes a self-healing algorithm through a policy graph, carries out graph modeling on a multi-cloud security policy, automatically identifies policy conflicts and drifts through graph difference analysis, and realizes continuous consistency and self-healing of a cross-cloud policy. And the security solution cooperation module is embedded into a reinforcement learning agent, dynamically decides an optimal deployment scheme of security resources according to a reward function by sensing a threat situation, a resource utilization rate and response delay, and realizes intelligent self-adaptive arrangement of protection resources. The security function module is used for micro-servitizing and containerizing security capability based on a cloud native technology, transparent injection is realized through a service grid, an automatic compliance repair and verification mechanism is built in, and a compliance closed loop for detection, repair and verification is formed. And the management efficiency and the protection accuracy of the security policy are improved.

The invention provides an inflection point prediction method and an inflection point prediction device applied to the health life of a battery, and a computer storage medium. The inflection point prediction method comprises the following steps: acquiring an original capacity sequence of the battery in a cyclic charging and discharging process; inputting the original capacity sequence into an XLSTM network architecture for training and prediction to obtain a preliminary capacity prediction value; inputting the residual error sequence of the preliminary capacity prediction value and the true value into a multi-output Gaussian process error correction model to correct a prediction result to obtain a residual error correction value; generating a capacity attenuation curve according to the initial capacity prediction value and the residual error correction value; performing high-order differential analysis on the capacity attenuation curve, and determining the curvature of the capacity attenuation curve; and performing fusion identification on a high-order differential analysis result and the curvature by adopting double criteria, and determining a capacity attenuation inflection point of the battery. Through the inflection point prediction method, early, accurate and reliable inflection point prediction is realized.

The invention discloses a drug jet milling self-adaptive modeling control method and system based on particle size distribution, and relates to the technical field of self-adaptive control, and the method comprises the steps: building a mixed digital twinborn model; connecting a particle size monitoring network, establishing particle size distribution data according to the collection and monitoring distribution relationship, and obtaining process parameters; process parameters are input into the mechanism model for crushing state simulation, model parameter iteration updating is carried out through the data driving model based on particle size distribution data, and parameter updating is carried out on the mixed digital twinborn model in an interactive mode; carrying out difference analysis, and determining a crushing compensation target particle size; and a reverse optimization model is established, self-adaptive search of reverse crushing parameters is carried out according to the crushing compensation target particle size, crushing control parameters are obtained, and the crushing control parameters are fed back to a controller for crushing airflow self-adaptive control. The technical problems that in the prior art, the particle size deviation is large and the stability is poor in the medicine airflow smashing process are solved, and the technical effect of achieving real-time accurate control over particle size distribution is achieved.

The invention provides a rural house wall defect detection method, system and device based on visual inspection, and relates to the technical field of visual inspection.The method comprises the steps that dark field scattering image data of the surface of a wall is obtained, and a suspected crack area is determined through visual enhancement processing and multi-scale differential analysis; a crack binary mask is output by utilizing a jump connection mechanism of a U-Net network and fusing multi-level features, a crack morphological parameter set is generated through morphological post-processing and skeleton extraction, a rural house wall defect evaluation report is finally generated, and early warning detection is particularly carried out for cracks of rural house walls, so that dangerous house detection is facilitated. The method improves the accuracy of rural house wall crack detection, and is more practical.

This invention discloses a three-dimensional quantification method for transmission line defects based on RGB-D point clouds and PointNet++, aiming to solve the technical problem that traditional two-dimensional visual inspection can only qualitatively identify defects and cannot achieve accurate quantification of physical parameters. The method includes constructing a dual-modal data acquisition framework of RGB texture and dense point cloud, achieving pixel-level spatiotemporal alignment through an online calibration algorithm for heterogeneous sensors; building a semantic segmentation model based on PointNet++ to accurately segment key components of the transmission line; and establishing a differential analysis mechanism between the standard equipment 3D model and the measured point cloud model to automatically calculate key parameters such as icing thickness, hardware corrosion volume, and insulator damage area. This invention breaks through the limitations of traditional two-dimensional visual qualitative identification, realizing a leap from visual inspection to physical quantification of defects, filling the gap in three-dimensional quantitative assessment in the industry, and providing accurate data support for the digital operation and maintenance of transmission lines.

The invention discloses a mobile robot control method and system based on multi-source fusion dynamic trajectory re-planning. The method comprises the steps that vehicle kinematics data and environment characteristic observation data are acquired in real time; state prediction is carried out based on a kinematic model; performing multi-dimensional feature extraction and confidence evaluation on the environment features; carrying out measurement updating by utilizing extended Kalman filtering; performing time domain differential analysis on the posterior state; when the state jump is detected, generating a smooth dynamic transition track by taking the current posterior state as a starting point; acquiring predicted curvature information of the front path from the global map; inputting the confidence score and the predictive curvature into a fuzzy logic controller, and calculating the adjustment amount of PID control gain; and calculating a motor control instruction based on the dynamic transition trajectory by using an adaptive PID algorithm, and outputting a final control signal. According to the method, high-precision positioning and stable control can be realized only by depending on a low-cost vehicle-mounted sensor, the cost is low, the universality is high, and the method is suitable for various complex indoor scenes.

The application provides a hidden PMU reverse engineering general framework based on differential analysis and simulation verification. The framework can efficiently analyze the function and underlying micro-architecture behavior of Intel processor hidden PMU events. By observing the count change of the entire event space during the execution of a carefully designed instruction fragment, the underlying micro-architecture behavior related to these events is inferred. Based on these initial inferences, a logically equivalent simulator is implemented to model these events. Through the differential analysis between the simulator count and the real CPU count, the simulator is gradually optimized to be consistent with the real CPU behavior, enabling us to reveal the micro-architecture features behind the hidden PMU events. The application has wide application prospects in the fields of performance monitoring, micro-architecture research and security detection, not only improving the hardware resource utilization efficiency of performance counters, but also significantly expanding the ability range of processor performance analysis.

The application discloses an analysis method, device and equipment of core molecules in the aging process, and a medium, and relates to the technical field of aging analysis. The method comprises the following steps: obtaining original data, dividing the original data into a control group and a plurality of experimental groups, and preprocessing the original data; performing aging mode clustering on the preprocessed original data to obtain a clustering result; performing duplicate removal GO enrichment analysis on each clustering mode, and visualizing the analysis result; taking the union of the molecular data of each experimental group after missing value screening and the molecular data of the control group after missing value screening, and analyzing the molecular data in the union through a differential analysis method to obtain a differential analysis result; performing correlation analysis on each clustering mode to obtain a correlation analysis result; and determining core molecules related to aging according to the correlation analysis result and the differential analysis result. The method can improve the accuracy of aging analysis.