674 results about "Data splitting" patented technology

Provided are an anomaly detection method and system for multi-source heterogeneous data, an electronic device, a vehicle, a computer-readable storage medium, a computer program product, and a computer program. The method comprises: performing statistical modeling on multi-source heterogeneous data, and obtaining background distribution features of multi-source heterogeneous data distribution through a data splitting method; preprocessing the background distribution features by using a preset sliding window to obtain a background image sequence on a specific time series; on the basis of the size of a target in the background distribution features, performing adaptive partitioning on the background image sequence to obtain an adaptive partitioning result, and identifying single source points of each partition in the adaptive partitioning result through a decoupling representation method; and on the basis of the identified single source points, determining the location of anomalous data in the background image sequence, and on the basis of a comparison calculation result of the multi-source heterogeneous data and the background image sequence from which the anomalous data is removed, obtaining an anomalous data location of the multi-source heterogeneous data.

The invention relates to the technical field of construction engineering cost management, and discloses an intelligent engineering cost calculation system based on multi-source heterogeneous data fusion, and the system comprises a multi-source data collection module which is used for collecting structured data and unstructured data from a design file, a market database, a construction monitoring system, a contract document, and a historical project library; and the heterogeneous data fusion module is connected with the multi-source data acquisition module and analyzes the risk terms in the contract text by adopting a natural language processing technology. According to the invention, the multi-source data acquisition module is used for widely collecting data in multiple aspects of design, market, construction, contract and the like, the problems of data splitting and information isolated island in traditional cost management are solved, integration of multi-source heterogeneous data is realized, and the heterogeneous data fusion module utilizes advanced technologies of natural language processing, image recognition and the like, so that the cost management efficiency is improved. Contract texts and design drawings can be efficiently analyzed, the processing capacity of unstructured data is improved, and the error rate and omission rate of manual interpretation are reduced.

The invention discloses a screening and evaluating system and method for cognitive impairment of old people, and belongs to the technical field of intelligent medical treatment. According to the system, electroencephalogram, VR / AR interaction, physiology and gait data are collected through the multi-modal acquisition module, the data processing module carries out data processing, dynamically selects a scale and carries out fusion analysis, the man-machine interaction module realizes natural interaction, and the output module generates a visual report and carries out early warning. The core algorithm comprises dynamic scale selection, multi-modal fusion evaluation and the like. The evaluation method comprises the steps of data acquisition, scale selection, data fusion, confidence verification, output and the like. Compared with a traditional method, the method overcomes the defects that subjectivity is high, and static evaluation, data splitting and base layer application are limited. The cognitive impairment assessment method can accurately and dynamically assess cognitive impairment, improves assessment accuracy, realizes full utilization of data, is simple and convenient to operate, is suitable for various scenes, provides efficient and reliable support for diagnosis, monitoring and intervention of cognitive impairment, and promotes development of intelligent medical treatment.

The invention discloses an image-text content auditing method and system based on a multi-modal large model, and the method achieves the deep semantic understanding and cross-modal integration of unstructured data through the cooperative work of all modules. A semantic association graph is generated through a multi-modal large model, the association recognition precision of the system on situations and information of images, texts, audios and videos is improved, and the problem that an existing system is inaccurate in semantic understanding is solved; the multi-modal data integration module realizes unified alignment of cross-modal data and layered mapping of information density, situation correlation and semantic consistency, and constructs an image-text association vector space, so that data splitting in an auditing process is eliminated; the content abnormity quantification module is combined with the intelligent control module, multi-level auditing decision is carried out through quantitative calculation and comparison of an auditing weight value Hqwz and a content abnormity index Cxzs, manual rechecking is automatically triggered, automatic issuing is directly carried out, the auditing efficiency is effectively improved, and the manual auditing burden is reduced.

The invention discloses an enterprise multi-modal data intelligent processing system fused with an RAG technology and an intelligent processing method of the enterprise multi-modal data intelligent processing system, and relates to the technical field of enterprise-level multi-modal data intelligent processing. And the data processing module is configured to respectively process the structured data and the unstructured data through the dynamic heterogeneous encoder and output unified semantic representation by adopting a cross-modal adversarial alignment mechanism. According to the enterprise multi-modal data intelligent processing system fused with the RAG technology, the problem of enterprise multi-modal data splitting is solved through dynamic adversarial semantic alignment and a stepped fusion mechanism. Semantic gaps are eliminated through self-adaptive convergence of cross-modal features in a hidden space, deep association of heterogeneous data is achieved based on concept mapping and credibility arbitration of an ontology network, key information of unstructured data is accurately extracted and converted into structured knowledge, and the accuracy of cross-modal association analysis and decision reliability are improved.

The invention discloses a single-cell multi-omics cell type annotation method based on pre-training, and belongs to the technical field of biological information, and the method comprises the following steps: obtaining a gene expression matrix of paired scRNA-seq data and a chromatin accessibility peak matrix of scATAC-seq data, and preprocessing the gene expression matrix and the chromatin accessibility peak matrix, then inputting a pre-trained feature extractor, and obtaining a query feature matrix fused with multiple omics by adopting a multi-head cross attention network of the pre-trained feature extractor; the feature extractor comprises a multi-head cross attention network and two classifiers; and inputting the query feature matrix into a classification model, performing data splitting by adopting a linear layer, then inputting the query feature matrix into a Transform encoder to perform multi-omics genetic feature extraction, and then inputting the query feature matrix into a classifier to perform cell type annotation. According to the cell type annotation method, the problem of deviation of cell type annotation in an existing method is solved.

The invention relates to the technical field of electric power risk control, and discloses an anti-bidding risk control system platform based on a large model technology, and the system platform comprises the steps: collecting bidding data, splitting the bidding data into bidding text data, behavior data and enterprise background data, carrying out the semantic extraction of the bidding text data, obtaining a core data set, and carrying out the calculation of the core data set; performing similarity score calculation on the core data set to obtain a similarity score; constructing a bidding relationship network by utilizing the behavior data and the enterprise background data; performing data synthesis by using the bidding relationship network, the similarity score and the core data set to obtain contrast data; and performing comparative analysis on the comparison data and the bidding data to obtain an abnormal behavior, and performing risk control scoring on the abnormal behavior to obtain an anti-bidding risk control result. According to the invention, the problems of low efficiency and poor adaptability of an existing anti-flipping risk control system platform based on a large model technology can be solved.

The invention discloses a data processing method and device. The method comprises the following steps: any computing node in a set communication cluster receives a first data slice sent by a previous computing node, executes a computing task according to the received first data slice, and splits to-be-sent task data independent of the computing task into a plurality of second data slices without a dependency relationship; the second data slices are sent to the next computing node in sequence, so that the next computing node receives the subsequent second data slices while executing the computing task according to the received second data slices; after the calculation task is executed according to all the task data in the calculation node, a target calculation result is obtained. According to the scheme, the overall efficiency of data transmission and calculation of the set communication cluster is effectively improved.

The invention discloses an intelligent interaction system based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence and intelligent interaction. According to the system, data processed by a data acquisition and preprocessing module is stored in a local knowledge warehouse in a three-layer nested structure; the multi-modal semantic understanding module constructs a knowledge system in which a triple knowledge graph and a vector database are complementary by optimizing a BERT model and performing dual-channel analysis; the intelligent interaction module realizes natural language interaction and business task automatic triggering based on an RAG technology and a dialogue memory mechanism; the information change identification and analysis module generates a personnel change risk report and performs early warning; and the summary report automatic generation module outputs a structured report. According to the method, the problems of data splitting, complex interaction and slow response in traditional enterprise management are solved, the functions of system intelligent question answering, personnel change risk analysis, structured report automatic generation and the like are realized, and the management efficiency and the information consistency are improved.

The invention discloses a training reasoning method of a decision model, a product, electronic equipment and a medium, and relates to the technical field of artificial intelligence. In the method, when the training reasoning process of the decision model is divided into a plurality of calculation tasks to be distributed to different cluster nodes, the load pressure on the nodes is reduced; and the plurality of data subsets obtained by splitting the input data corresponding to the calculation task are allocated to different calculation nodes, so that the load pressure on the calculation nodes is reduced, the utilization rate of node resources is improved, parallel processing of the data subsets corresponding to the input data is realized, and the efficiency of training reasoning is improved. When the training reasoning process of the decision model is divided into one calculation task, the plurality of data subsets obtained by splitting the input data corresponding to the calculation task are distributed to different calculation nodes, so that the load balance on the calculation nodes is ensured, the load is reasonably distributed to the nodes in the cluster, and the calculation efficiency is improved. And the utilization rate of node resources is improved.

The invention discloses a supply chain collaborative management method and system for a whole-industry link platform, and the method comprises the steps: constructing a distributed supply chain data warehouse through employing a block chain and lightweight encryption; generating a multi-dimensional matching degree score table to recommend suppliers; decrypting and storing the encrypted bidding file, and calculating a comprehensive score according to a quantitative index and an expert qualitative index; constructing a hierarchical prediction model, and outputting a three-dimensional prediction result; calculating a supply-demand gap according to a supply-demand elastic coefficient coupling algorithm, automatically generating an order, and synchronizing the order to each end in real time; building a supply chain digital twinborn model, and dynamically planning an optimal transportation route through an intelligent fusion road condition algorithm; early warning information is automatically sent to generate a coping strategy, and full-link operation data are integrated for visual display; the objective of the invention is to solve the problems of existing supply chain data splitting, low supplier matching efficiency, low demand prediction precision, rigid logistics planning, risk monitoring lagging and poor collaboration of all links.

The invention provides a hydropower station AI supervision system and method based on a multi-modal large model, and relates to the technical field of intelligent hydropower. The system comprises a multi-modal data acquisition module, a cross-modal space-time alignment module, a multi-modal feature extraction module, a multi-modal large model processing module and an intelligent reasoning and decision module. A neural differential equation model is introduced to carry out space-time alignment on asynchronous sensing data, networks such as Vision Transformer, MelCNN, TCN and the like are utilized to extract multi-modal features, cross-modal fusion analysis is realized by combining a local and global attention mechanism and dynamic weight distribution, and equipment abnormality is further reasoned based on a reconstruction error, a mahalanobis distance and a knowledge graph and a maintenance strategy is generated. According to the method, high-precision anomaly detection, fault root cause positioning and dynamic maintenance optimization of key equipment of the hydropower station are realized, diagnosis errors caused by traditional manual inspection and data splitting are avoided, and the operation and maintenance intelligence level and the equipment operation reliability are improved.

The invention discloses a geological disaster risk intelligent pre-judgment method based on deep learning, and relates to the technical field of geological disaster monitoring and early warning. According to the method, high-precision alignment and feature extraction can be automatically performed on monitoring data with different temporal-spatial resolutions and different physical meanings, such as optical remote sensing, radar measurement, laser point cloud and the like, uniform and information-rich representations are generated, a solid data foundation is laid for subsequent accurate prediction, and the limitation of data splitting application in a traditional method is overcome; a space-time diagram with slope units as nodes is constructed, an attention mechanism diagram convolutional network with hydrological directivity introduced is utilized, and the model can accurately describe the spatial propagation process that slope substances migrate and accumulate along with a confluence path and block a river channel under the rainfall condition; meanwhile, the time sequence module effectively learns the influence of the past hydrological state on the future evolution trend.

The invention relates to a gold mine air-ground-in-well rapid collaborative exploration method, belongs to the field of geological exploration, and aims to solve the technical problems of data splitting, low target area positioning precision, insufficient deep prediction capability and the like in traditional gold mine exploration. By integrating air remote sensing, surface geological survey and underground detection data, a multi-source data standardization processing flow is established, and a progressive exploration system from wide-area screening to accurate positioning is realized by combining geological, geophysical and geochemical comprehensive analysis methods. The system adopts a dynamic feedback mechanism to optimize an exploration process, forms closed-loop analysis and prediction, improves exploration efficiency and accuracy, and reduces resource waste and exploration cost. The method is suitable for gold ore resource exploration under complex geological conditions, has remarkable economic benefits and application value, and can be widely applied to the field of mineral resource development.

The invention provides a drug identification information efficient query method and system based on distributed cache. The method comprises the following steps: firstly, receiving and analyzing a drug identifier query request to generate a dynamic cache routing key, then positioning a target cache node, then matching a cache data block corresponding to a drug unique code in the target cache node, if matching succeeds, extracting a drug full life cycle record in the cache data block, and sending the drug full life cycle record to the target cache node; if the matching fails, initiating a cross-node retrieval request to the drug block chain database to return drug source data, splitting the drug source data into a core attribute set and an extended track set, and finally executing a dynamic combination operation on the core attribute set and the extended track set to generate a drug tracing result set and returning the drug tracing result set to the user terminal; according to the technical scheme provided by the invention, the query fluctuation defect of a single storage architecture is eliminated from the source, so that the whole system simultaneously meets three drug traceability core requirements of high concurrency, cross-mechanism and tamper-proofing.

The invention discloses an intelligent data splitting and optimizing method and system based on multiple dimensions. The invention relates to the technical field of data splitting. And dividing the number and size of the sub-tasks based on dimensions and metrics required to be split, and dynamically scheduling the dependency relationship and the execution sequence among the sub-tasks. Based on the execution efficiency of the dimension combination and the data skew condition, dynamically adjusting the splitting strategy of the dimension combination, for example, increasing the number of subtasks of hot dimension combinations, optimizing the processing logic of the dimension combination with serious data skew, and the like; through a task splitting and dynamic scheduling mechanism, a large task is decomposed into a plurality of small tasks to be executed in parallel, distributed computing resources are fully utilized, and data processing and analysis time is remarkably shortened. By optimizing the data storage structure and utilizing the ETL tool to clean and compress the data, the occupied physical storage space is reduced, the storage cost is reduced, and meanwhile, the data access speed is increased.

The invention relates to an optimization method for intelligent ISO drawing output based on an external platform. The optimization method comprises the following steps: S1, importing a model and judging a model type; importing a model, and judging whether the model is a two-dimensional model or a three-dimensional model; s2, verifying the three-dimensional model: verifying the three-dimensional model; s3, model data splitting: splitting the verified three-dimensional model; s4, generating a pipeline component file; s5, processing the generated PCF file through an ISO # algorithm; s6, generating an ISO map of the pipeline according to the data processed by the ISO # algorithm; s7, generating a unique reference number and coordinates; S8, establishing data version management, and establishing a data version management mechanism; s9, when the three-dimensional model is modified, automatically updating the two-dimensional model data and the ISO map; and S10, auditing and publishing: auditing the generated ISO map. By efficiently processing two-dimensional and three-dimensional model data in an engineering project, automatic generation of the ISO drawing is achieved, the method is widely applied to the field of CAD design and the like, and the working efficiency and the drawing accuracy are improved.

A method performed in a wireless communication device (1500) having a data buffer and connected to three network nodes in a radio communication system includes connecting (1001) to three different cell groups where the wireless communication device is configured to use a primary transmission path in a first cell group of the cell groups, a secondary transmission path in a second cell group of the cell groups, and a tertiary transmission path in a third cell group of the cell groups; receiving (1003) a configuration having first and second data split threshold values for modifying a data transmission path; and transmitting data via only the primary transmission path (1007), via only the primary transmission path and the secondary transmission path (1011) and via the primary transmission path, the secondary transmission path, and the tertiary transmission path (1013) based on the first and second data split threshold values.

The invention discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning method, which comprises the following steps: deploying a sensing network, and collecting and processing personnel data and equipment data; evaluating the health state of the equipment based on the equipment data; cleaning the personnel data and then constructing a trajectory model; performing risk coupling analysis based on the three-dimensional risk identification model to obtain a comprehensive risk value; and performing grading response based on the comprehensive risk value and judging whether to perform model optimization or not. The invention further discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning system which comprises a sensing layer, the sensing layer is connected with an analysis layer through a network layer, the analysis layer is connected with an execution layer, and the execution layer is connected with the sensing layer. The invention discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning method and system, solves the technical bottlenecks of data splitting, response lag and poor environmental adaptability of a traditional monitoring system, and reduces the accident false alarm rate by more than 35% through spatial coupling analysis.

The invention relates to the field of emerging software and information technology service, in particular to an artificial intelligence-based application system integrated management method, which comprises the following steps of: analyzing an API (Application Program Interface) log, structured data, an unstructured document, business work order data and business image data by pre-training a large model, and generating a unified semantic representation in combination with multi-modal contrast learning; a knowledge distillation technology is adopted to migrate the large model capability to a lightweight neural network, and a domain knowledge base is generated based on fine tuning of business work order data; a user multi-mode instruction is analyzed, a DAG service agent template library is matched, and an execution chain is dynamically combined based on a reinforcement learning strategy, so that text processing, multi-system collaborative reasoning and RPA service process automation are realized; and collecting an execution log, and updating lightweight network parameters and an intelligent agent strategy library through an online distillation algorithm to form a closed-loop optimization mechanism. According to the method, the service response efficiency can be improved, and the problems of enterprise multi-service system data splitting and process stiffness are solved.

The invention discloses a brand propagation index construction system, and particularly relates to the technical field of brand analysis. A data processing system; an analysis model system; a visualization system; a feedback optimization system; and dynamically updating the system. By constructing a full-link intelligent closed-loop system, the problems of data splitting and strategy lagging in traditional brand propagation analysis are solved, the system integrates cross-platform data sources to achieve efficient fusion of multi-source heterogeneous data, the limitation of data islands is broken through, the collaborative application of dynamic factor analysis and generative adversarial networks is achieved, and the analysis efficiency is improved. The system can perceive propagation scene changes in real time, dynamically adjust data weights and model parameters and ensure that analysis results are adaptively optimized along with market situations, meanwhile, a linkage mechanism of an A / B test engine and a genetic algorithm enables strategy recommendation, parameter optimization and version iteration to be automatic, decision response time is remarkably shortened to the minute level, and the market development efficiency is improved. And real-time and accurate decision support is provided for brand management.

The invention discloses a building engineering multi-dimensional monitoring system based on panoramic imaging, and relates to the technical field of building engineering monitoring and sensing. Comprising a panoramic image acquisition module, an image splicing and panoramic reconstruction module, a multi-source data synchronous acquisition module, an image-data fusion construction module, an image-physical association modeling module and a risk identification and intelligent response module, an image acquisition array formed by high-resolution cameras is installed at key positions of a building structure, images of all the cameras are obtained, and an original image sequence covering a monitoring area is output. According to the invention, through fusion of the panoramic image and the multi-source sensing data, visualization, intelligent identification and risk prediction of the structure state are realized, a closed-loop monitoring system is constructed, the problems of single traditional monitoring means, data splitting and the like are solved, and the safety monitoring intelligent level of constructional engineering is improved.

The invention discloses a hybrid far and near field communication beam and power joint optimization method based on rate splitting, and relates to the technical field of wireless communication and novel multiple access. The designed hybrid near-far field communication beam and power joint optimization method comprises the following four steps: S1, establishing a far-field user and a near-field user channel model in a hybrid near-far field communication scene; s2, splitting data of near-field users into public information streams and private information streams by using a rate splitting multiple access technology; s3, pre-configuring beams of the public information flow and the private information flow of the near-field user by using a zero breaking algorithm, so that the far-field user occupies the beams of the near-field user to carry out information transmission; and S4, establishing an optimization problem by taking maximization of the reachable sum rate as a target, and designing an iterative optimization algorithm to jointly process beam allocation of the near-field users and transmission power allocation variables of the near-field users and the far-field users and the near-field users. According to the invention, the throughput and connectivity of the communication network can be obviously improved.

The invention relates to the technical field of rural space governance and intelligent decision making, in particular to a rural space planning method and related equipment, and the method comprises the steps: obtaining multi-source data of a target rural, the multi-source data comprising land data, population data and rural economic data of the target rural; performing fusion processing of space-time alignment on the multi-source data to obtain fusion data; constructing a spatio-temporal knowledge graph based on the fused data, and extracting entity attributes and spatial relationships; and inputting the entity attributes and the spatial relationship into a pre-trained planning optimization model, iteratively optimizing a rural space matching strategy according to rigid constraints, and outputting an optimal planning result, the technical problems that in the prior art, rural planning faces data splitting, element analysis isolation, planning scheme staticization and actual development requirements are disjointed, the decision making process depends on subjective experience, and economic-ecological benefit tradeoff is difficult to quantify are effectively solved.

The invention relates to the field of intelligent control, and discloses a refrigerator multi-parameter collaborative awareness and resonance intelligent wakeup control method, which comprises the following steps: dynamically acquiring temperature, humidity and door state signals and adjusting the weights of the signals, extracting the resonant frequency offset by combining the vibration spectrum of a compressor, and performing intelligent wakeup and refrigeration duration prediction based on the characteristics. And credibility evaluation, a self-learning mapping model and an interference filtering mechanism are introduced. Compared with a traditional single-parameter or fixed threshold value control mode, the control logic is driven through physical quantity changes, under triggering of a door state event, a three-dimensional linkage relation of an environment state, a physical signal and a control decision is formed, timely sensing and accurate response to changes of the internal thermal characteristics of the refrigerator are achieved, and the problems of data splitting and lag control are solved.

The invention discloses an electronic medical record intelligent coding method, device and system, and a storage medium. The method comprises the following steps: respectively carrying out entity extraction, feature coding and homomorphic encryption transmission on an electronic medical record text, a medical image and structured inspection data; according to the preprocessed data, performing multi-modal feature alignment, ICD semantic mapping and real-time medical insurance rule injection through a dynamic knowledge fusion coding engine; generating a three-dimensional visual evidence chain of the text evidence, the image evidence and the policy evidence through the interpretable traceability matrix; through a multi-role cooperative workflow engine, generating a code according to a confidence threshold routing AI, and auditing the code to a clinician or a professional coder; rare disease data are synthesized through an adversarial training enhancement module, and policy mutation is simulated for model adaptability training. By adopting the technical scheme of the invention, the problems of multi-modal data splitting, policy lag and non-traceability in the prior art are solved.

The present disclosure provides a data processing system and method, a computer device and a storage medium. The method includes: reading first data from a first memory space of a target memory space and splitting the first data to obtain multiple segments of second data; determining check information corresponding to each segment of the second data, and storing the check information of each segment of the second data as third data in a second memory space of the target memory space; generating a data assembly instruction based on a data assembly order for the second data and the third data; and sending the data assembly instruction to a storage acceleration module, enabling the storage acceleration module to write the fourth data into the hard disk based on read data and the target data structure.

The invention discloses a compression method and device for generic semiconductor industry operation and maintenance data, electronic equipment and a medium, and relates to the technical field of data compression. The method comprises the following steps: acquiring to-be-compressed generic semiconductor industrial operation and maintenance data; identifying the time sequence of the generic semiconductor industrial operation and maintenance data to be compressed, and judging whether the generic semiconductor industrial operation and maintenance data is time sequence data or not according to the time sequence; and if the to-be-compressed generic semiconductor industrial operation and maintenance data is time series data, splitting the to-be-compressed generic semiconductor industrial operation and maintenance data into a time data set and a feature data set, and compressing the time data set and the feature data set respectively. According to the compression method, different compression strategies are adopted for different types of data, the compression efficiency of the data is improved, and the balance between the compression rate and the calculation efficiency is optimized.

The invention relates to the technical field of power equipment safety inspection. The power inspection fault diagnosis method and system based on the unmanned aerial vehicle multispectral image are provided, and the method comprises the steps: carrying out the multispectral data collection of power equipment, and obtaining a visible light image, multispectral reflectivity data and infrared thermal image data; dynamically correcting emissivity change caused by oxidation or dirt on the surface of the equipment to generate a dynamic emissivity correction coefficient table; according to the dynamic emissivity correction coefficient table, temperature calibration is carried out on the infrared thermal image data, and a calibrated temperature distribution diagram is generated; and fusing the calibrated temperature distribution diagram, the preprocessed visible light image and a multispectral reflectivity distribution diagram obtained by preprocessing the multispectral reflectivity data, performing multimodal fault diagnosis, and outputting fault types and positions, so as to solve the problems that single spectral data is easy to misjudge, emissivity static assumption errors are large, and the accuracy is high in the prior art. And the problem of insufficient confidence caused by multi-modal data splitting analysis is solved.

The invention relates to the technical field of signal noise reduction, in particular to a processing method, system and device for preventing ultrasonic signal noise and a medium, and the method comprises the steps that parameter adjustment is conducted on initial configuration parameters based on a preset parameter configuration rule, a starting instruction is generated after parameter adjustment is completed, and a transducer of an ultrasonic gas meter is controlled to be started; determining at least one group of original ADC waveform data based on the ultrasonic signal, performing data splitting on the at least one group of original ADC waveform data to obtain signal ineffective area waveform data and signal effective area waveform data, and performing assignment processing on waveform parameters of the signal ineffective area waveform data to obtain signal effective area waveform data; and carrying out data splicing and recombination on the signal ineffective area waveform data and the signal effective area waveform data after assignment to obtain at least one group of to-be-sent ADC waveform data, sending the at least one group of to-be-sent ADC waveform data to a target terminal, and controlling to display the waveform data. The data acquisition precision and the flow calculation accuracy of the ultrasonic gas meter are improved.