1057 results about "Information analysis" patented technology

The invention provides a knowledge and data fused medical content image-text generation system and method. Relates to the technical field of digital medical treatment and artificial intelligence. The multi-modal feature extraction module is used for extracting multi-modal features from the multi-modal data; the multi-modal feature fusion module is used for carrying out cross-modal dynamic fusion on the multi-modal features to generate cross-modal high-consistency fusion features; the model training optimization module is used for configuring a soft and hard target loss function and a parameter optimizer; the information analysis and reasoning module is used for carrying out semantic matching on the fusion features, the disease classification and the clinical path based on a dynamic medical knowledge network, and generating disease prediction probability distribution and a semantic reasoning path; and the image-text report generation module is used for generating an image-text report containing a diagnosis conclusion and an interpretation basis according to the prediction probability and the semantic reasoning path. According to the invention, intelligent and precise generation of medical contents can be realized.

The invention relates to the field of enterprise risk early warning analysis, in particular to an intelligent risk early warning method and system based on multi-dimensional data analysis. The method comprises the following steps: acquiring a multi-dimensional enterprise data stream, performing heterogeneous index information analysis and logic hierarchy reconstruction, and constructing an enterprise running state sensing map; performing multi-index local fluctuation amplitude calculation on the enterprise operation state sensing map, and performing dynamic disturbance feature mining to construct a risk disturbance spectrogram; performing deep semantic analysis and node state abrupt change feature analysis on the risk disturbance spectrogram to generate a dynamic transition type of an abrupt change node; and performing full-period time sequence tracing on the risk disturbance spectrogram, performing potential risk node prediction based on the dynamic transition type, and identifying other potential risk propagation ports. Through accurate and efficient enterprise risk perception, the risk intervention decision is made in advance, and the anti-risk capability and the operation stability of the enterprise are improved.

The invention discloses a document analysis and query method based on a knowledge graph, and the method comprises the steps: carrying out the part-of-speech tagging of a received to-be-analyzed document, and obtaining a part-of-speech tagging result; extracting knowledge element information from the part-of-speech tagging result based on a preset power grid domain ontology knowledge base, and constructing an initial knowledge graph based on the knowledge element information; combining nodes in the initial knowledge graph to obtain a fused knowledge graph; constructing a mapping table according to the fused knowledge graph, and generating a candidate query template set based on the mapping table; receiving a natural language query statement input by a user, selecting a target query template from the candidate query template set based on the natural language query statement, and generating a target query statement; querying from the fused knowledge graph by using the target query statement, and outputting a query result; according to the method, the accuracy and comprehensiveness of information analysis can be effectively improved, the query intention of the user can be accurately understood, and the accurate query and analysis requirements of professionals on project documents are met.

The invention discloses a dialogue type data analysis method and device, a storage medium and electronic equipment, and relates to the technical field of data analysis. The method comprises the steps that a natural language text input by a user is acquired; obtaining corresponding semantic pre-analysis information based on the natural language text; matching a corresponding mode mapper based on the semantic pre-analysis information; obtaining corresponding semantic information based on a mode mapper; converting the semantic information into corresponding semantic information conversion parameters; analyzing the semantic information conversion parameter to obtain an index value corresponding to the to-be-queried index; performing anomaly detection on the index value corresponding to the to-be-queried index; and performing analysis result display on the index value corresponding to the to-be-queried index passing the anomaly detection. According to the method, information arrangement and information analysis are carried out on the natural language text input by the user, the intention of the user is known, the index needing to be queried by the user is fed back, the operation complexity is reduced, the interactivity and the real-time performance are improved, and convenience is provided for data analysis work.

The invention discloses a monitoring information analysis method and system based on artificial intelligence, and relates to the technical field of intelligent monitoring and information analysis, and the method comprises the steps: collecting a monitoring video stream from a monitoring device, and intercepting the monitoring video stream to obtain a monitoring image sequence; performing target identification and tracking on the monitoring image sequence by using a deep learning model, and extracting target motion feature parameters and spatial position information; constructing a spatial-temporal characteristic matrix, generating a target behavior track by using the spatial-temporal characteristic matrix, and inputting the target behavior track into a pre-trained behavior analysis model; and performing time sequence analysis on the target behavior track by adopting an attention mechanism, outputting an abnormal behavior probability value, and when the abnormal behavior probability value exceeds a preset threshold value, generating an abnormal event mark. According to the invention, at the video acquisition end, the improved adaptive white balance and multi-scale noise reduction algorithm is adopted to optimize the image quality, so that the problems of color restoration and noise interference in different scenes are solved.

The invention relates to the technical field of data sharing security, in particular to a government affair data security sharing method and system based on a block chain technology. The method comprises the following steps: acquiring user service handling information, analyzing user service requirements according to the user service handling information, and determining target multi-level department chain information; according to the target multi-level department chain information, performing multi-level encryption anchoring uplink storage on the user service handling information, and determining service multi-level department chain information; and based on an intelligent contract driving strategy, according to the user service demand and the service multi-level department chain information, performing multi-department chain type cooperative processing on the user service demand, and determining and outputting a government affair processing result. According to the application, the data sharing security among different hierarchy departments in the government affair processing process is improved, good balance between data security and government affair processing is effectively guaranteed, the working efficiency and experience of users are improved, and the government affair electronization process and efficient configuration of social resources are promoted.

The invention discloses a network security information analysis and statistics method based on a regulation and control cloud platform. Protocol identification, standardized mapping and blood relationship marking of multi-source security equipment data are realized through an edge layer protocol adaptation cluster and a metadata self-registration mechanism; constructing a real-time streaming and batch processing dual-channel framework based on regulation and control of cloud platform container resources, and fusing to generate a standardized security event object with a frequency weight and a hazard coefficient; designing a main ring-emergency ring double-path decision closed loop, respectively processing conventional events and high-risk threats, and realizing knowledge base iteration; extracting features by using a containerized architecture in combination with an XGBoost + isolated forest integrated model, detecting threats and generating rules; and a space-time-system-risk four-dimensional visualization engine is constructed, attack path drawing, event evolution display and high-risk area prediction are realized, and a management closed loop is formed. According to the network security information analysis and statistics method based on the regulation and control cloud platform, the intelligence and automation level of network security information analysis and statistics is improved.

The invention belongs to the technical field of electric power system information processing, and particularly relates to an electric power information analysis method based on big data, through semantic fusion of multi-source heterogeneous data and dynamic feature mining of a time sequence attention mechanism, in a load prediction scene, compared with a traditional single data source model, the electric power information analysis efficiency is improved. After the meteorological data, the user power consumption behavior data and the power grid operation data are fused, the prediction average error rate is reduced; in an equipment fault early warning scene, through multi-dimensional correlation analysis of vibration signals, oil temperature data and environmental factors, transformer latent faults can be early warned in advance, and the fault identification accuracy is improved; meanwhile, a self-adaptive modeling engine and a closed-loop feedback mechanism enable the system to have a self-evolution capability: when the power grid topology is adjusted or the new energy grid-connected proportion is changed, the model does not need to be manually retrained, and self-adaptive adaptation can be completed in two scheduling cycles through dynamic feature weight adjustment and meta-learner parameter optimization, so that the analysis performance is maintained to be stable.

The invention relates to a conference data intelligent analysis and decision support system. Audio data in a conference process are collected in real time; extracting conference information of the audio data by adopting a natural language processing technology, wherein the conference information comprises conference participant positions, conference themes, conference contents and voting results; and adopting a big data analysis model to predict an expected effect of meeting decision execution according to the meeting information. According to the invention, the problem of low working efficiency caused by the fact that the prior art depends on manual recording and summarization, effective information of the conference is difficult to extract and the execution effect of the conference decision is predicted according to the conference information is solved. The conference information variable set having significant influence on the execution effect is selected through the random forest model, and the efficiency and accuracy of conference information analysis are improved.

The invention discloses a document knowledge base LLM intelligent question and answer method, device and equipment and a storage medium. The method comprises the steps that dynamic partitioning is conducted on a to-be-processed document, and vectorization and index storage are conducted on knowledge blocks; vector retrieval and keyword retrieval are carried out according to the natural language question, a vector retrieval result and a keyword retrieval result are fused, an answer is obtained through LLM, and the answer is fed back to a user after being safely filtered; when it is detected that the to-be-processed document is updated, the vector library and the index are synchronously updated, and the cue word template and the partitioning strategy are periodically optimized, so that the problem of form picture information loss can be solved, the integrity of document information analysis is guaranteed, the situation that the partitioning strategy is single is avoided, the multi-hop recall rate is increased, and the problem of semantic missing is avoided; a partitioning mechanism is reasonable, retrieval precision is improved, updating cost is reduced, data security is improved, implementation is convenient, universality is good, and the speed and efficiency of LLM intelligent question answering of the document knowledge base are improved.

The invention belongs to the technical field of computer information processing, and relates to a scientific research performance information analysis and evaluation system and a processing method thereof.The scientific research performance information analysis and evaluation system comprises a data collection module, a weight distribution module, a real-time feedback module and an execution engine function module; weight distribution receives the first signal and analyzes a current strategic target priority identifier and a historical performance evaluation record contained in the first signal, a weight parameter space dynamically matched with a target priority is constructed through an online learning algorithm, and a second signal containing a real-time weight mapping relation is generated; real-time feedback is carried out, a multi-dimensional performance evaluation matrix is constructed based on the weight mapping relation in the second signal, and a third signal is generated; the execution engine receives the third signal, analyzes an abnormal positioning code of the third signal, and aggregates intervention records in a period to form a fourth signal; according to the method, the defects that traditional performance information analysis depends on static weight, the data dimension is single, and real-time dynamic adjustment is lacked can be overcome, and the analysis efficiency is improved.

The invention relates to the technical field of big data processing, in particular to a data acquisition and analysis system for network big data information analysis, which comprises a data acquisition module, a data preprocessing module, a data storage module, a data analysis module and a data visualization module, wherein the data acquisition module is used for acquiring original data from various data sources in real time through a network interface; the data preprocessing module is used for preprocessing the original data; the data storage module is used for carrying out storage and management by adopting a distributed database; and the data analysis module is used for performing deep analysis by applying a machine learning algorithm and a data mining technology to generate a trend prediction result. According to the method, real-time acquisition, automatic preprocessing, distributed storage and multi-algorithm fusion analysis of the multi-source data are realized, so that the problems of low data quality, poor processing efficiency, model isolation and the like in the prior art are solved, and the precision, efficiency and decision support capability of big data analysis are remarkably improved.

The invention provides a bulk cargo wharf intelligent equipment scheduling system and method, equipment and a storage medium. The scheduling system comprises a data acquisition module; an information analysis and strategy generation module; a joint scheduling calculation module; a scheduling execution module; an execution feedback module; a model updating module; and a rule induction module. According to the method, a closed-loop liberalization system fusing semantic understanding, strategy generation and scheduling execution is constructed, so that the problem that unstructured information cannot be effectively utilized by a scheduling system is solved; scheduling parameters can be accurately extracted from unstructured data, even scheduling characteristic parameters are directly extracted from the unstructured data and structured scheduling strategy suggestions are generated, the data threshold of system intelligent transformation is reduced, a scheduling model is driven together with the structured parameters, a feedback learning mechanism is introduced, and the scheduling efficiency is improved. And efficient, intelligent and self-learning management of equipment scheduling is realized, so that the system can adapt to complex and variable port operation environments, and has good expansibility and generalization ability.

The invention discloses a data analysis processing method and system based on multi-source data fusion, and relates to the technical field of data analysis fusion processing. Comprising the following steps: data acquisition and preprocessing: acquiring multi-source data, including user behavior data, content data and social data, related to APP pushing and cultural transmission from a plurality of data sources such as social software and an internet platform, after acquisition, preprocessing the multi-source data, generating preprocessed data, and establishing a dynamic credibility evaluation model; according to the method, the dynamic credibility evaluation model is established to distribute the weight for the data source, so that the interference of low-credibility data on the analysis result is avoided, and the information analysis of the user interest intensity, the content credibility and the cultural value based on the fused data is more accurate; therefore, a more reliable basis is provided for making an APP push strategy and a cultural transmission scheme.

The invention relates to the technical field of multi-source information analysis, in particular to a niobium-tantalum metal ore metallogenic evaluation system based on multi-source information analysis, which comprises a geologic structure association module, a mineral distribution interpretation module, a metallogenic environment adaptation module, a spatial feature analysis module and a potential region judgment module. According to the method, by introducing a multi-source data analysis and fusion method, the evaluation precision and comprehensive capability of resource exploration are effectively improved, analysis after information fusion is combined with relevance and spatial modes of different data types, it is ensured that mineralization potential evaluation is more accurate, the limitation of a single data source and manual analysis is overcome, and the method is suitable for popularization and application. According to the method, the identification precision and reliability of the mineralization law are improved, the potential area can be identified more accurately, resource potential analysis is optimized in combination with the adaptability of the mineralization environment, the efficiency and accuracy of determining the mineralization area are remarkably improved, the problems of information isolation and analysis deviation in a traditional method are avoided, and the scientificity and the practical application value of the exploration process are enhanced.

The invention discloses a multi-agent collaborative scheduling method and system oriented to science and technology intelligence analysis, and relates to the technical field of science and technology intelligence analysis, and the method comprises the steps that a task issuing layer outputs a standardized task description by executing task demand element analysis; after the intelligent coordinated scheduling layer receives the standardized task description, closed-loop collaborative decision making is carried out, and a task distribution instruction is output; and the professional agent execution layer drives the data acquisition agent group to acquire science and technology information data through a data access adapter of the data resource layer, executes a science and technology information analysis task, outputs a structured processing result, and visually displays the structured processing result to a user through the task release layer. The technical problem that in the prior art, a science and technology information processing system lacks intelligent task allocation, and consequently the information processing efficiency is low is solved, and the technical effects that four-layer architecture closed-loop cooperation of science and technology information analysis tasks and efficient dispatching of specialized intelligent agent groups are achieved, and the task allocation accuracy and the information processing efficiency are improved are achieved.

The invention provides a presentation document generation method and device, electronic equipment and a storage medium, relates to the technical field of artificial intelligence, and is suitable for the field of financial science and technology. The method comprises the following steps: performing information analysis on document generation indication information to obtain a document guide language and a document generation intention; selecting elements according to the document generation intention to obtain at least two document elements; generating a document outline structure according to each document element and the document guide language; wherein the document outline structure comprises a basic document page, and the basic document page is provided with a demonstration guide text; performing material selection on a pre-constructed structured database according to the demonstration guide text to obtain a target material and material attribute information; updating the basic document page according to the target material and the material attribute information to obtain a target document page; and replacing the basic document page in the document outline structure with the target document page to obtain a target demonstration document. According to the method, the presentation document generation accuracy can be improved, and personalized requirements of users are met.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a multi-modal information analysis and scheme reminding method, device, equipment and medium, which comprises the steps of receiving input data and converting the input data into multi-modal data, executing optical character recognition and image classification recognition to generate a recognition result, and sending the recognition result to a server; a natural language processing model is used for analyzing fuzzy description to generate an analysis result, a knowledge base is inquired, a knowledge graph is combined to generate an association result, the analysis result, the association result and user feature data are fused to generate an execution scheme, the execution scheme is compared with an abnormal list, supervision confirmation is triggered, and a compliance instruction is generated. And personalized reminding contents are generated. The information analysis integrity is improved through multi-modal recognition, natural language processing and the knowledge graph, supervision confirmation and personalized reminding are introduced, and intelligent, compliant and reliable reminding management is achieved.

The invention relates to the technical field of artificial intelligence, in particular to a big data information analysis method and system based on artificial intelligence, and the method comprises the following steps: obtaining a jump segment direction vector, classifying label nodes with consistent directions, splitting a path lacking a mapping relation to form an interruption segment, recognizing a node with continuous directions as a bridge segment entrance, and obtaining a bridge segment direction vector; according to the method, by means of classification according to the node sequence and the channel number in the segment hopping direction, direction aggregation boundary determination and semantic field combination path position interruption recognition, the node sequence structure positioning precision and the paragraph division reasonability are improved, and the focus analysis set is generated by combining the path segments. Bridge segment connection is screened based on direction consistency, path continuation logic, behavior tracks and aggregation numbers are kept in sequence and hierarchy regularization, a behavior aggregation sequence of a semantic chain is constructed, and the continuity of path recognition in a channel aggregation area and the stability of node attribution are enhanced.

The invention relates to a field information analysis method and system based on RAG and a knowledge graph, and belongs to the technical field of artificial intelligence, and the system comprises a multi-source heterogeneous data collection module which is used for collecting field-related original data; the intelligent document processing engine is used for carrying out cleaning and structured processing on the data and extracting entities, relationships and events; the multi-source knowledge graph construction and management module is used for constructing and fusing multi-sub-field knowledge graphs to form a unified knowledge graph; the RAG retrieval enhancement generation dynamic fusion sequencing module is used for receiving user query, performing multi-channel information retrieval by querying a text vector index and a knowledge graph, performing fusion resequencing on a result, and generating an analysis result by utilizing a large language model; and the agent workflow engine is used for decomposing query into subtasks and scheduling professional agents to cooperatively complete analysis and report generation. Deep semantic understanding, intelligent retrieval and automatic analysis of domain information are realized, and the accuracy and efficiency of information processing are improved.

The embodiment of the invention provides a test case sample cutting method, device and system and a storage medium, and relates to the technical field of network security testing. The method comprises the following steps: constructing an industrial control system attack tactical library; wherein the tactical library comprises classified and arranged attack techniques and corresponding security attributes; performing information analysis and semantic analysis on the test case sample to generate structured data of the test case sample and / or function points in the test case sample; and cutting the test case sample according to the security attribute and / or the structured data and / or the function point to obtain a test fragment corresponding to the security attribute and / or the function point. According to the method, classification-based attack techniques and security attributes are cut by constructing a tactical library, key information can be accurately extracted and test intentions can be understood through information analysis and semantic analysis, redundant tests are avoided, cut test fragments can concentrate on specific security attributes or function points, the test coverage range is more accurate, and the test efficiency is improved. And the distributed security test effect is improved.

The invention relates to the technical field of electrical fire information analysis and statistics scheme design, in particular to an electrical fire information analysis and statistics method and system based on a knowledge graph. According to the method, through the knowledge credibility evaluation model and the optimization algorithm, the accuracy of knowledge fusion is effectively improved, so that the constructed knowledge graph is more accurate and complete, and electrical fire information analysis and statistics work can be better supported. The introduction of the intelligent inference engine can deeply excavate the potential causal relationship and influence factors of the electrical fire, generates detailed and accurate analysis and statistics results, and provides more comprehensive information support for users. The establishment of a dynamic updating mechanism ensures that the knowledge graph can reflect new electrical fire information and knowledge in real time, the timeliness and effectiveness of the information are always kept, and the practicability and reliability of electrical fire information analysis and statistics are greatly improved.

The invention discloses an intelligent conference recording system, which has the following beneficial effects that the intelligent conference recording system comprises functional modules such as a conference information acquisition module, a data pre-cleaning module, a conference information transcription module, a conference content intelligent analysis module and the like; according to the invention, multi-modal data such as voice, images and texts can be deeply fused through the conference content intelligent analysis module, and structured data and intelligent analysis are provided for users; cross-conference association analysis can be supported, so that a user can be better supported to make a decision; in addition, the voice recognition precision and the handwritten note recognition precision can be effectively improved. Through the above mode, the invention provides the intelligent conference recording system which integrates efficient conference recording, intelligent information analysis and user personalized demand, can fill the blank of the existing conference recording tool, and better improves the overall working efficiency of conference recording.

The invention discloses an intelligent state information analysis system for centralized control station equipment monitoring, and mainly relates to the technical field of power systems and intelligent monitoring. Which comprises an information analysis management module and an event handling management module, and is characterized by further comprising a service tracking management and control module, the information analysis management module is used for carrying out event processing on alarm signals, and the information analysis management module is provided with a power monitoring knowledge base; and the power monitoring knowledge base is used for collecting, sorting, managing and analyzing data and knowledge related to monitoring, and supporting system monitoring, event management, problem diagnosis and decision making. The method has the beneficial effect that the health management level of the power transformation equipment can be effectively improved.

The invention relates to a circuit board on-line defect detection method and system, and the method comprises the steps: carrying out the synchronous collection and structural integration of multi-source technological parameters such as production line environment temperature and humidity, equipment operation states, material batches and the like, and defect detection images, and achieving the construction of large-sample original data in a production process; through standardization and de-noising preprocessing, multi-modal features are fused, and a distribution mapping model of process and defect features is established by using algorithms such as mutual information analysis and principal component analysis. Based on a feature distribution model and real-time data, a dynamic anomaly detection threshold is adaptively generated, Bayesian inference and evidence reasoning are combined, multi-level confidence levels and risk response suggestions are output, and self-learning evolution of the model and the threshold is realized through a closed-loop feedback mechanism. According to the scheme, the accuracy of anomaly detection, the response timeliness and the risk disposal intelligent level are improved, the method adapts to complex working conditions and batch changes, and the closed-loop optimization and safety control capability of the production process is remarkably enhanced.

The invention discloses a building facade three-dimensional surveying and mapping system and method based on an unmanned aerial vehicle and AI, and relates to the technical field of building surveying and mapping, and the system comprises a scene analysis module which is used for executing the information analysis of calibration scene information, and marking each surveying and mapping sub-region as a to-be-collected node; the acquisition planning module is used for calculating the node transition probability of each node to be acquired; the surveying and mapping search module is used for configuring a virtual unmanned aerial vehicle and performing selective iteration of surveying and mapping sub-regions by using pheromone concentration and heuristic factors; the clustering sharing module is used for carrying out three-dimensional surveying and mapping on the exterior facade of the building and establishing a shared information pool in a clustering manner; and the surveying and mapping optimization module is used for carrying out collaborative decision optimization on the local path and updating the acquisition path according to a collaborative decision optimization result. The technical problems of low surveying and mapping efficiency and large measurement error caused by difficulty in meeting large-scale and high-precision surveying and mapping requirements of modern buildings in the prior art are solved, and the technical effect of improving the surveying and mapping efficiency and precision of the buildings is achieved.

The invention discloses an intelligent shooting range training system based on real-time data acquisition, relates to the technical field of intelligent shooting range training based on real-time data acquisition, and is used for solving the problem that an existing intelligent shooting range training system based on real-time data acquisition only pays attention to a single aspect of a training effect. The system is difficult to provide personalized training suggestions according to specific conditions of trainees; and a traditional training method may lack scientific verification. Comprising a real-time information acquisition module, an information analysis module, a scene analysis module and an optimization processing module. The real-time information is acquired through the real-time information acquisition module, and the behavior and physiological data are analyzed by the information analysis module to obtain comprehensive and deep analysis, so that the pertinence and effectiveness of training are improved; the method comprises the following steps: identifying different scene mode factors and setting corresponding evaluation weights; personalized improvement suggestions are provided for trainees, the best physiological state can be kept, the training effect is comprehensively improved, and the training experience is optimized.

The invention discloses a data management system based on a monitoring video stream, belongs to the field of data analysis, and aims to solve the problems of camera connection acquisition, image quality optimization, pedestrian related information analysis and data storage retrieval and backup in video monitoring. The system comprises a data acquisition module, a target detection module and a data storage module. The data acquisition module is used for identifying and connecting a video monitoring camera, performing video stream data acquisition, adjusting an acquisition frame rate by estimating a data size, and evaluating and optimizing image quality to obtain a detection image data set; the target detection module is used for carrying out feature extraction, classification and marking on pedestrians in the detection image data set, recording pedestrian trajectory information, carrying out real-time tracking and updating, identifying a behavior mode according to the trajectory information, dividing a gathering area and obtaining the pedestrian flow; and the data storage module is used for classifying and labeling the data, constructing an index structure to guarantee efficient retrieval, dividing data grades according to multi-dimensional features, and dynamically adjusting a backup time interval.

The invention relates to the field of lamp holder module data analysis, in particular to an information analysis method and device capable of achieving communication storage of a lamp holder module. The method comprises the following steps: acquiring a historical operation monitoring log of a lamp holder module, and performing data cleaning and multi-window division to obtain monitoring logs of a plurality of time windows; performing transient abrupt change identification and multi-scale abnormal state deconstruction according to the monitoring logs of the plurality of time windows to obtain transient abrupt change state features of a plurality of scales; carrying out multi-time-point environment temperature fluctuation analysis on the monitoring logs of the plurality of time windows, and carrying out multi-scale quantitative correlation analysis according to the transient abrupt change state characteristics so as to obtain a quantitative correlation relationship between transient abrupt change and environment change; and performing multi-factor nonlinear correlation evolution according to the quantitative correlation, and constructing a multi-factor causal chain. According to the invention, real-time evaluation is carried out according to the working state of the current lamp holder module, and accurate fault risk and service life state evaluation is provided.

The invention discloses a time series anomaly detection method based on a neural network, and the method comprises the steps: obtaining to-be-detected multivariable time series data, and inputting the multivariable time series data into a spatial-temporal feature fusion unit, performing time domain information and attribute information analysis on the multivariable time sequence data by a time domain convolutional network and a graph attention influence network in the spatial-temporal feature fusion unit, and obtaining spatial-temporal fusion features through feature fusion; decomposing the multivariable time sequence data by adopting a self-adaptive time sequence decomposition algorithm to obtain a trend sequence and a periodic sequence; inputting the space-time fusion feature, the trend sequence and the periodic sequence into a time sequence reconstruction unit to obtain a decoding feature; performing anomaly detection on the decoding features through an anomaly detection unit to obtain an abnormal state of the multivariable time series data; according to the method, the reconstruction deviation between the potential abnormal data and the reconstruction data can be expanded, and the potential abnormal data in the multi-dimensional time sequence can be rapidly and accurately detected.