12947 results about "Computer equipment" patented technology

The road crack detection method based on the improved RT-DETR comprises the following steps: shooting a road at a preset flight height by using an unmanned aerial vehicle to obtain an original road image containing a crack; a pre-trained crack detection model is utilized to carry out crack detection based on an original road image to obtain crack parameters, and the crack detection model is obtained through improvement and training based on an RT-DETR (Real-Time Detecting Transformer) model; the method for improving the RT-DETR model to obtain the crack detection model comprises the following steps: replacing a basic residual block at the tail end of a ResNet18 backbone network in the RT-DETR model with a dynamic snakelike convolution residual block (DSCRBlock); a cross-scale feature fusion module (CCFM) in a hybrid encoder in an RT-DETR model is replaced by a bidirectional diffusion focusing pyramid network (BDFPN), and the bidirectional diffusion focusing pyramid network comprises a primary focusing sub-network and a secondary focusing sub-network. The method can efficiently and accurately identify the road crack, can be applied to the unmanned aerial vehicle, and is easier to implement.

The invention discloses a multi-modal data retrieval method and device, a storage medium and computer equipment. The method comprises the following steps: collecting multi-modal original data; on the basis of description information of metadata of original data, all metadata belonging to the same associated items and logic relations among all the metadata are obtained, a metadata chain is constructed, a distributed graph database is constructed on the basis of the metadata chain, the metadata chain is expressed in the distributed graph database in the form of a graph, the graph comprises nodes and edges, the nodes represent the metadata, and the edges represent the metadata. The edge represents a logical relationship between the metadata; and when a data retrieval instruction is received, traversing each node in the metadata chain along the logical relationship of the metadata chain in the distributed graph database, obtaining a target node matched with a data retrieval requirement corresponding to the data retrieval instruction, and returning original data corresponding to metadata represented by the target node. Multi-modal data dynamic association retrieval can be realized, and cross-modal information mining efficiency and accuracy are improved.

The invention belongs to the technical field of network security, and relates to a network attack behavior chain construction and active defense method and device and computer equipment, and the method comprises the steps: collecting full-flow data and a multi-source log from a network environment, and carrying out the preprocessing of the full-flow data and the multi-source log; storing the preprocessed full-flow data and multi-source logs, and establishing an associated index; through a deep learning algorithm and an unsupervised model, abnormal traffic and attack behaviors are identified from the full-traffic data and the multi-source logs; reconstructing the fragmented attack events into a complete behavior chain through a graph neural network and a visualization mode; based on the AI model, a dynamic defense strategy is generated, and a response action is automatically executed; through time sequence prediction and a deep learning model, a future attack trend is predicted, and active defense is realized. The method improves the unknown attack detection capability, optimizes the traceability efficiency, enhances the defense initiative, guarantees the real-time performance and accuracy of network attack prediction, and has compliance adaptability.

The invention discloses an ink-jet printing control method and device for a perovskite battery and computer equipment, and the method comprises the steps: obtaining the time sequence characteristics of a current ink droplet in a process of falling to a perovskite battery substrate, and the spreading morphological characteristics of the current ink droplet on the perovskite battery substrate, the environmental characteristics are obtained in the process that current ink droplets are ejected by an ink-jet printer to form a film on a perovskite cell substrate; performing defect identification according to the time sequence features, the spreading morphological features and the environment features to obtain a current defect type; matching in a preset parameter adjustment rule according to the current defect type, and determining a target parameter adjustment strategy; and the printing process parameters are adjusted based on the target parameter adjustment strategy, and subsequent ink-jet printing is carried out based on the adjusted printing process parameters. Therefore, the problem of film forming defects caused by environmental fluctuation is solved, the uniformity of the perovskite cell film is improved, and the defect rate is effectively reduced.

The invention relates to a multi-agent cooperative recruitment method, system and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a target recruitment demand, and generating a task tree for the target recruitment demand through a preset dynamic decision-making mechanism in a main agent; determining a time sequence relationship and logic constraint information of each sub-task in the task tree, and calling target sub-agents in the sub-agents in sequence based on the time sequence relationship and the logic constraint information; the target sub-agent is used for executing the sub-task in the task tree; and generating a target recruitment task result until task execution results of the sub-tasks are obtained. By adopting the method, the recruitment efficiency can be improved.

The embodiment of the invention discloses a naked eye three-dimensional interaction method and device and computer equipment. The method comprises the following steps: determining at least one three-dimensional virtual object corresponding to a target preset naked eye three-dimensional interaction scene, and determining an initial display parameter corresponding to the at least one three-dimensional virtual object; controlling the at least one three-dimensional virtual object to perform motion display in the target preset naked-eye three-dimensional interaction scene according to the initial display parameter so as to generate a naked-eye three-dimensional picture corresponding to the at least one three-dimensional virtual object; obtaining interaction feedback information generated when the user interacts with the at least one three-dimensional virtual object according to the naked eye three-dimensional picture; and according to the interaction feedback information, generating an update display parameter corresponding to the at least one three-dimensional virtual object, and based on the update display parameter, controlling the at least one three-dimensional virtual object to perform motion update display in the naked eye three-dimensional picture. Therefore, a user watches and interacts with the three-dimensional virtual object which is movably displayed in the naked-eye three-dimensional picture, the sight distance can be improved and adjusted, and asthenopia can be relieved.

The invention relates to a BOM table generation method based on full life cycle management, computer equipment and a computer readable storage medium, and the method comprises the following steps: S1, generating a client matrix according to a product design document and an engineering material, and obtaining information in the client matrix; the customer matrix is presented in the form of a two-dimensional table, column information in the two-dimensional table represents serial numbers of product parts and / or components of different assembly levels, and row information at least comprises names, numbers, specifications and models of the product parts and / or components and parent component identifiers; s2, generating an in-plant BOM matrix according to the material key information, the in-plant material number, the in-plant inventory status and the supply chain constraint condition, inputting the in-plant BOM matrix into a preset management system to generate an electronic drawing and document database, and establishing a structured D-BOM; s3, comparing the client matrix information obtained in the step S1 with the D-BOM established in the step S2; s4, carrying out adjustment and optimization on the D-BOM; and S5, importing the optimized D-BOM into a client matrix, and generating a final BOM.

The invention provides a network security situation awareness method and system and computer equipment, and belongs to the technical field of network security. The method comprises the following steps: collecting and standardizing multi-source heterogeneous security data; constructing and dynamically updating a network asset and vulnerability knowledge graph; performing tactical labeling on the security event based on tactical, technology and process behavior model libraries to form a current attack context state; mapping the current state into a knowledge graph to deduce a potential subsequent attack path; performing quantitative risk assessment on the path, and calculating an initiation probability and a potential risk value; outputting situation awareness information containing the path and the probability and risk value thereof; and dynamically determining a key area needing to be updated preferentially in the knowledge graph according to an evaluation result, and triggering incremental updating. According to the method, the crossing from static monitoring to dynamic prediction is realized, the attack path can be actively deduced, quantitative risk assessment is carried out, meanwhile, the real-time performance of the knowledge graph is guaranteed through a focusing updating mechanism, and the initiative and accuracy of network security protection are improved.

The invention relates to the technical field of electric digital data processing, and provides a secondary development code cross-product transplantation method and device, computer equipment and a medium. The method comprises the steps of loading a source project, screening a to-be-transplanted source code file, identifying an original API type, determining a mapping relation between the original API type and a target API type, and generating an adaptation layer code framework according to the mapping relation; copying the to-be-transplanted source code file into the target project; on the premise of keeping the project hierarchical structure of the source project, replacing the calling node of the original API type with the calling node of the adapter type, and replacing the namespace reference with the corresponding namespace in the target project to obtain a migrated source code file; and obtaining a secondary development project of the target project based on the second product API according to the adaptation layer code framework and the migrated source code file. According to the method and the device, the transplantation efficiency and accuracy of the transplantation of the cross-product secondary development codes are improved.

The invention provides a water quality inversion method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring wide-area hyperspectral image data, regional multispectral image data and actually measured water quality parameters; performing correction and space-time registration processing on the wide-area hyperspectral image data and the regional multispectral image data, and performing feature fusion to generate a fusion feature vector; based on the fusion feature vector, performing inversion through a first inversion model to obtain a first type of water quality parameters; based on the first type of water quality parameters and the actually measured water quality parameters, performing inversion through a second inversion model to obtain second type of water quality parameters; a water quality parameter spatial distribution diagram is obtained based on inversion of the first type of water quality parameters and the second type of water quality parameters; and according to the water quality parameter spatial distribution map, when the actually measured water quality parameter is greater than a preset threshold value, generating an early warning signal. Based on the scheme of the invention, the precision, timeliness and automation level of water quality parameter inversion in a complex water area environment can be improved.

The embodiment of the invention provides a digital simulation modeling method and device of a tandem type hybrid electric propulsion system, computer equipment and a medium, and relates to the technical field of simulation modeling, and the method comprises the following steps: constructing a turboshaft prime mover model, constructing a generator model, connecting the turboshaft prime mover model and the generator model in series to generate a generator set, the power generation groups are connected in parallel to construct a turbine power generation system; constructing a propulsion system; constructing a battery energy storage system; constructing a power transmission and distribution system, and respectively connecting the power transmission and distribution system with a turbine power generation system, a propulsion system and a battery energy storage system; and constructing a comprehensive control and energy management system, and outputting a digital simulation modeling result through a turbine power generation system, a power transmission and distribution system and a battery energy storage system. According to the scheme, a simulation modeling method based on multi-physics field coupling double-power-source dynamic response and energy flow regulation and control provides reliable modeling technical support for engineering application of a tandem type hybrid electric propulsion system.

The invention provides a method and a system for detecting gas concentration in an epitaxial growth reaction cavity, computer equipment and a storage medium. The method comprises the following steps: acquiring a reflected light signal, a reference signal and a reaction cavity environment signal; carrying out wavelength calibration and intensity baseline calibration on the reflected light signal according to the reference signal, and generating an experimental absorption spectral line according to the calibrated reflected light signal; according to the reaction cavity environment signal, fitting the experimental absorption spectral line and a target absorption spectral line obtained by querying a preset database, and performing inversion to obtain concentration information of the gas to be detected. According to the invention, through double calibration of a reference channel, an experimental spectral line and a database target spectrum are strictly aligned on a frequency scale and an amplitude scale, interference of linear displacement and baseline fluctuation on fitting is reduced, and quantitative precision is improved; and meanwhile, an environmental condition is introduced as a physical constraint, so that parameter coupling is weakened, the identifiability and robustness of inversion are improved, the dependence on pure empirical correction is reduced, and the stability of detection data is improved.

The invention relates to a memory management method and device applied to a server-free data center, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: in response to a virtual memory application instruction, performing virtual memory allocation in a local computing resource pool to obtain a virtual address space; in response to the virtual address access instruction, acquiring cache information of the computing resource pool, and triggering missing page interruption under the condition that data corresponding to the virtual address is not hit in the cache information; the cache information comprises locally cached cache data and page table information; acquiring physical memory resources in a memory resource pool according to the virtual address and the page table information under the condition of triggering missing page interruption of the anonymous page; and updating the page table information and the cache information according to the physical memory resources. By adopting the method, the processing delay of the data center can be reduced while the decoupled memory management logic is used for improving the resource utilization rate.

The invention relates to a six-eye camera panoramic video real-time splicing method and system and computer equipment, and the method comprises the steps: synchronously carrying out the image collection through a six-eye camera array, and adding a timestamp to each video frame image; performing real-time feature extraction on the video frame image, and establishing a feature matching relationship in a view field overlapping region of adjacent cameras; based on the feature matching relationship, mapping each video frame image to a unified splicing coordinate system through projection transformation; performing splicing processing on the video frame images after projection transformation through multi-band fusion, and eliminating splicing traces at the boundary of the field of view; and reconstructing the panoramic frame images obtained after splicing processing according to a time sequence, and outputting a continuous panoramic video stream so as to realize real-time and seamless splicing and correction of six paths of high-definition video streams and finally output a global panoramic video stream with no visual fracture and consistent time and space.

The embodiment of the invention discloses a report generation method and device, computer equipment and a readable storage medium, and the method comprises the steps: displaying a graphical user interface to prompt a report requester to input report demand information; report demand information is obtained, semantic analysis is carried out on the report demand information through a large language model LLM to obtain report generation indication information, and the report generation indication information at least comprises a data range, a data type, a data statistical parameter and a report display type; searching a database through the LLM to obtain a plurality of business data matched with the data range and the data type, and obtaining business indexes of the plurality of business data based on the data statistical parameters through the LLM; and determining report basic parameters based on the report display type through the LLM, and outputting a target report based on the report basic parameters, the multiple pieces of business data and the business indexes. By adopting the method, the technical threshold of data analysis processing can be reduced, the report generation efficiency is improved, and the method is simple, efficient and high in applicability.

The embodiment of the invention provides a prediction method and device for the outlet temperature of an aero-engine combustion chamber, computer equipment and a medium, and relates to the technical field of performance evaluation and prediction.The method comprises the following steps that input parameters related to combustion chamber operation and combustion chamber structure are collected in batches, an optimal parameter set is generated, and the optimal parameter set is stored; working condition vectors are constructed through combustion chamber working conditions; constructing a stable parameter set through the optimized parameter set and the working condition vector, screening all parameters in the stable parameter set, and adjusting weights corresponding to the parameters in the working condition vector through an adaptive weight model; and constructing a physical constraint coupling prediction model, training the physical constraint coupling prediction model based on the physical constraint, generating a trained physical constraint coupling prediction model, and outputting the unevenness of the temperature distribution of the outlet of the combustion chamber through the model. According to the scheme, high-precision prediction of the temperature distribution unevenness of the outlet of the combustion chamber can be realized under the conditions of different pressures, temperatures, equivalence ratios and the like.

The invention discloses an obstacle avoidance motion planning method and system for redundant drive of an intelligent process of a welding robot and computer equipment. According to the method, firstly, a motion path of a robot is planned based on welding process redundancy, then a sampling strategy that the position and posture of a welding gun are separated is adopted, then the sampled posture is mapped to a planar two-dimensional space, and the relevance between an obstacle collision boundary and the obstacle avoidance posture of the welding gun is constructed; an incremental extreme gradient lifting model is adopted to carry out probability modeling on the collision boundary and obstacle avoidance attitude relevance, nearest neighbor search and new planning node expansion are carried out based on target cost to obtain new planning nodes, collision detection is carried out on the new planning nodes, and the new planning nodes passing the collision detection are used for incremental learning of an obstacle avoidance model; and finally, an optimization strategy of spherical linear interpolation and cosine slow motion time mapping is adopted to ensure continuity and smoothness of a motion planning path trace. The problem that in the prior art, it is difficult to quickly calculate and generate a collision-free welding track is solved.

The invention discloses a multi-mode federated learning method and system, computer equipment and a readable storage medium, and belongs to the technical field of federated learning. The multi-modal federated learning method comprises the following steps: on each client node, mapping local data of various modals into a plurality of vectors in a unified semantic space, determining an incidence matrix of the data of the various modals, and fusing the plurality of vectors according to the incidence matrix to obtain a local semantic vector; training a local model by using the local semantic vector to obtain local model parameters, and uploading the local model parameters to a server; on the server, identifying the difference degree between the data distribution condition of each client node and the global data distribution condition, and determining the node weight vector of each client node; and performing weighted aggregation on the corresponding local model parameters by using the node weight vector of each client node to generate global model parameters for next federated learning. Therefore, the performance of the training model can be improved.

The invention provides a sand and dust scene atmosphere pollution source identification method and system, computer equipment and a medium, and belongs to the field of environmental pollution analys.The method comprises the steps that the types of volatile organic compounds and the types of fine particulate matter PM2.5 in the atmosphere of a sand and dust scene to be identified in a target area are identified, and the concentration of the volatile organic compounds and the concentration of the fine particulate matter PM2.5 are measured; carrying out mineral dust proportion calculation on the types of the fine particulate matters PM2.5 and the concentration of the fine particulate matters PM2.5 to obtain a mineral dust quantification result, and determining a dust source contribution weight according to the active metal increment in the mineral dust quantification result; and performing positive matrix decomposition prediction on the types of the volatile organic compounds, the concentration of the volatile organic compounds, the types of the fine particulate matters PM2.5 and the concentration of the fine particulate matters PM2.5 based on the dust source contribution weight, and determining the pollution source contribution proportion of the atmosphere of the sand and dust scene to be identified. According to the method, the accuracy of pollution source identification is guaranteed, and a basic guarantee is provided for subsequent pollution source treatment.

The invention relates to a man-machine interaction method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring interaction content input by a user; scene recognition is carried out on the interaction content through a large language model, and a scene label of the interaction is determined; determining a target long-term memory partition corresponding to the scene tag from a plurality of long-term memory partitions preset for the user; inputting target long-term memory content in the target long-term memory subarea and short-term memory content stored in a short-term memory area preset for the user into an intelligent agent; the intelligent agent is used for generating reply content for the interaction content according to the target long-term memory content and the short-term memory content. By adopting the method, effective association and collaborative calling of different scene memories can be realized, and the dynamic requirement of a user on coherent interaction in multi-scene switching is met.

The invention discloses an intelligent evaluation method and device for an RAG system based on a large model, and computer equipment. The method comprises the following steps: acquiring a knowledge base source file required by a to-be-evaluated RAG system; analyzing and converting the knowledge base source file, creating a structured document block set, and executing preprocessing operation to obtain an intermediate knowledge base; automatically generating an evaluation data set including the question, the answer and the document block of the corresponding evidence according to the intermediate knowledge base based on LLM; performing performance evaluation on the to-be-evaluated RAG system by using an NLP evaluation index and an LLM-based multi-dimensional scoring mechanism based on the evaluation data set to obtain an evaluation result; and generating a report according to the evaluation result, and outputting the report. By implementing the method provided by the invention, the performance evaluation and iterative optimization of the RAG system can be comprehensively and accurately improved at low cost.

The invention relates to a charging pile system, a power scheduling method and device thereof and computer equipment. The method comprises the steps that under the condition that a first charging gun is connected with a load, a switch of an access between the first charging gun and a target power module is closed, a target charging gun corresponding to the target power module is different from the first charging gun, and the target charging gun is in an idle state; and under the condition that the charging demand power of the first charging gun is greater than the output power of the first power module, controlling at least one target power module to provide charging power for the first charging gun. The target power module can be quickly used for providing power for the first charging gun, so that the response speed to the power requirement is improved, and the charging efficiency is improved.

The invention relates to the technical field of energy storage system scheduling, in particular to an energy storage system scheduling method and device, computer equipment and a medium, and the method comprises the steps: obtaining battery operation parameters and prediction data of an energy storage system, inputting the battery operation parameters into a pre-established battery digital twinborn life model, and calculating a life loss factor, and according to the life loss factor and the prediction data, determining a scheduling optimization strategy which enables the objective function to be optimal, and according to the scheduling optimization strategy, controlling the energy storage system to execute charging and discharging operation. Therefore, according to the method, the digital twin model and the battery operation parameters are fused, the multi-objective optimization function is constructed, and the scheduling optimization strategy is dynamically adjusted, so that the operation state of the energy storage battery can be accurately sensed in real time, and the dynamic optimization balance of the scheduling strategy between the economic benefit and the battery life loss is realized; therefore, the scheduling accuracy and the operation stability of the energy storage system are improved.

The invention discloses a battery risk judgment method based on lithium battery life prediction and computer equipment, and the method comprises the steps: obtaining multi-source heterogeneous data of a whole life cycle of a battery, achieving the alignment of a time domain and a space domain through a self-alignment engine, extracting data which is strongly related to capacity attenuation, carrying out the fusion of the data to generate a health factor, and carrying out the calculation of the health factor. Realizing characteristic standardization: inputting data into a co-evolution framework, performing co-evolution through a dual model formed by a materialization channel model and a data driving channel model, predicting the service life of the battery, and outputting an SOH predicted value; calculating the confidence degree based on the difference degree of the dual-model prediction distribution P and Q; according to the confidence coefficient, different methods are adopted to determine an SOH final prediction value and the confidence coefficient; and according to the final SOH prediction value and the confidence coefficient, combining a historical label comparison result, and outputting a risk warning of the battery. According to the invention, the battery life prediction precision is improved.

According to the movie and television play table book extraction method and device, the storage medium and the computer equipment provided by the invention, after an audio and video file of a movie and television play is split into a video file and an audio file, feature recognition is performed on the video file to obtain a subtitle text, speaker face information and a video understanding text; performing voice understanding on the audio file to obtain a voice transcription text and a voice understanding text; wherein the voice transcription text can be corrected into the standard transcription text with high accuracy through the subtitle text. Therefore, based on the face information of the speaker, the line segment of each speaker in the standard transcriptional text and the audio and video file is aligned, so that speaker information with accurate segmentation and semantic coherence can be obtained; and then, through combination with a character side-writing text generated by side-writing analysis on the speaker based on the video, the voice understanding text and the speaker information, table book information is constructed, and related feature description of the character can be covered on the basis of containing the line content, so that the content and depth of the table book are enriched.

The invention relates to the technical field of psychological health, and discloses a psychological health multi-modal evaluation method, system and device and computer equipment, and the method comprises the steps: obtaining multi-modal data, and carrying out the feature extraction of the multi-modal data, and obtaining multi-modal features; performing emotion-oriented cross-modal attention mechanism analysis on the multi-modal features to respectively obtain a preset-dimension emotion scale vector, an emotion semantic feature, a multi-dimensional emotion feature and an uncertainty quantitative feature; fusing the preset dimension emotion scale vector, the emotion semantic feature, the multi-dimensional emotion feature and the uncertainty quantitative feature to obtain a multi-modal fusion feature; and obtaining a mental health assessment result based on the multi-modal fusion features and a preset multi-task learning framework. Through a cross-modal attention mechanism, deep semantic fusion of five modals of vision, audio, physiology, text and behavior is realized, and intelligent mapping from original multi-modal data to accurate psychological state judgment is realized through a deep learning technology.

The invention provides a spectral data optimization method and device, computer equipment and a storage medium, and relates to the technical field of semiconductor detection.The method comprises the steps that original spectral data output by a spectrograph is obtained, and the central wavelength value of the original spectral data of each frame is calculated; querying from a preset database according to the central wavelength value to obtain a corresponding instrument linear function; and processing each frame of original spectral data and the corresponding instrument linear function by adopting a deconvolution algorithm to obtain optimized real spectral data. According to the scheme, algorithm compensation is carried out on each frame of spectral data, so that system distortion introduced by the spectrometer can be accurately compensated in a full spectrum range, the extraction precision of spectral features is greatly improved, and the magnitude order improvement of measurement precision is realized; in addition, the optimized spectral data more truly reflects the physical characteristics of the tested sample, the dependence of an optical model on empirical parameters is reduced, and the generalization ability and prediction reliability of the model are improved.

The invention relates to a risk behavior early warning method and device based on adaptive time sequence slicing, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: collecting user operation behavior data aiming at each service in a service system, and obtaining user information and service characteristics of each service in the service system; generating a service activeness index; adjusting the length of a time interval between time sequence slices of the user operation behavior data; according to the adjusted time sequence slices, integrating the user operation behavior data, generating a user behavior sequence, and constructing a user behavior dependency graph; generating a normal behavior pattern of the user according to the time sequence slice intervals of different granularities, the user behavior sequence and the user behavior dependency graph; and according to the normal behavior mode, carrying out risk behavior early warning on the user actual operation behavior of each service in the service system. By adopting the method, the risk behavior prediction accuracy can be improved.

The invention relates to a safety air bag ignition control method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps that the running state of the automobile safety air bag control system is configured through the safety control state machine; under the condition that the running state is the normal state, the ignition function of the automobile safety air bag control system is configured to be in a forbidden state through a safety control state machine; in response to the fact that the automobile safety air bag control system is powered on for the first time and / or a watchdog error is detected, the running state is switched to a watchdog error protection state from a normal state through a safety control state machine; and under the condition that the operation result of the sensor data processing unit exceeds a preset threshold value, the operation state is switched from the normal state to the safety air bag ignition enabling state through the safety control state machine, and the ignition function is switched to the starting state. By adopting the method, the low-delay and high-precision response requirements of the chip on the ignition control instruction can be met.

The invention discloses a multi-source unmanned aerial vehicle track fusion method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring unmanned aerial vehicle monitoring data; performing analysis and feature extraction on the unmanned aerial vehicle monitoring data, and forming a standardized data feature vector; generating a confidence score of each sensor at each moment based on the data feature vectors; dynamically adjusting parameters of a UKF or PF algorithm according to the confidence score, and performing trajectory fusion based on the adjusted parameters to obtain an initial trajectory fusion result; and performing optimization based on the initial trajectory fusion result, and dynamically adjusting computing resources according to a system load and a confidence score to obtain a final trajectory fusion result. By implementing the method provided by the invention, the fusion precision, the system robustness and the real-time calculation efficiency in a complex environment can be remarkably improved, and intelligent multi-platform data processing without manual intervention is realized.