1636 results about "Informatization" patented technology

The invention discloses a power grid equipment state sensing driving dynamic response method based on the Internet of Things technology, and relates to the technical field of power system automation and informatization, and the method comprises the following steps: S001, collecting original multi-dimensional state signals of a plurality of sensors deployed in a power grid equipment state sensing channel, constructing an electromagnetic disturbance recognition model, and carrying out the recognition of the original multi-dimensional state signals; frequency domain and time domain feature extraction is carried out on the signals, and a feature comparison parameter set used for distinguishing electromagnetic interference and real faults is generated. Frequency domain and time domain features are extracted through an electromagnetic disturbance recognition model, dynamic threshold judgment and response strategy adjustment are achieved in combination with multi-source sensing data, interference and faults can be accurately distinguished, early warning and protection logic can be corrected in real time, protection actions can be accurately triggered, closed-loop control is achieved, the delayed fault tolerance and multi-source verification capacity is achieved, and the method is suitable for large-scale popularization and application. The false operation rate and the false stop risk are effectively reduced, and the intelligence, the safety and the stability of power grid operation are improved.

The invention relates to the technical field of informatization processing, and provides an IT asset intelligent management system and an implementation method thereof, and the system comprises an asset discovery subsystem which outputs a standardized asset list through a feature comparison and deduplication fusion program; the unified modeling subsystem forms an asset topological graph by processing association and dependence between information technology assets; the intelligent analysis and prediction subsystem outputs insight results and prediction indexes about resource capacity prediction, anomaly detection, cost optimization suggestions, risk trends and the like; the life cycle management subsystem drives an automatic operation and maintenance workflow through a strategy engine to realize closed-loop management of the information technology asset state; the security and compliance subsystem generates an alarm, a repair suggestion or executes an automated repair policy. According to the invention, intelligence, automation and safety compliance of information technology asset management are realized, and the efficiency and reliability of information technology operation, maintenance and management are significantly improved.

The invention belongs to the technical field of tunnel and underground engineering intelligent construction and geotechnical engineering informatization, and discloses a high-energy geological environment surrounding rock classification and decision-making method based on digital twinning and multi-source feedback. The problems caused by difficulty in realizing surrounding rock state dynamic sensing, multi-source data fusion classification and construction decision closed-loop linkage in the prior art in a high-energy geological environment are solved. The method comprises the following steps: firstly, constructing a tunnel three-dimensional geology-structure digital twinborn body based on initial survey data; in the construction process, multi-source data such as geology, construction disturbance and surrounding rock response are collected in real time through the Internet of Things technology and mapped to the digital twinborn body, and virtual-real synchronous updating is achieved. And then, constructing a deep learning-parameter inversion hybrid model on the basis of the multi-source fusion data, outputting a dynamic surrounding rock classification index DRCI and key mechanical parameters, inputting the DRCI and the key mechanical parameters into a multi-objective optimization module, and giving a self-adaptive drilling and blasting scheme. And finally, reversely correcting the model through a construction feedback result to realize closed-loop self-learning.

The invention relates to the technical field of building informatization and intelligent construction, and discloses a building engineering digital twinning progress management and control method and system.The building engineering digital twinning progress management and control method comprises the steps that multi-source heterogeneous data in the building engineering construction process is collected; carrying out fusion processing on the original data set by adopting a space-time alignment network; updating the digital twin body by adopting an incremental state estimation method; predicting a future progress by adopting a model fusing a graph neural network and a time sequence attention mechanism; a multi-level detection mechanism is adopted to identify progress deviation and analyze a root cause; generating an optimized resource scheduling scheme by adopting a reinforcement learning method; an intelligent decision support system is constructed, and visual display and interaction functions are provided; according to the method, the graph neural network and the time sequence attention mechanism are fused, the progress prediction model capable of capturing the task topology dependency relationship and the time sequence evolution characteristics at the same time is constructed, and the accuracy of progress prediction is improved.

The invention discloses a water conservancy facility full-period informatization management method and system based on digital twinning, and relates to the technical field of water conservancy informatization management, and the method comprises the steps: collecting water conservancy facility data, constructing a water conservancy facility digital twinning model, constructing an interactive structure body through employing three-dimensional geometric modeling, topological coding, material attribute and operation state fields, and constructing a water conservancy facility digital twinning model. Node mapping, attribute inheritance and time evolution rules are established; on-site progress, quality and deviation data are collected through a construction period sensing device, a state-driven mapping mechanism is designed, various data are dynamically mapped to a digital twin model of the water conservancy facility, and a structure-environment collaborative sensing mechanism is constructed in an operation stage; based on the digital twinborn model data of the water conservancy facility, a risk identification model is established, and the dam break risk, gate clamping stagnation, pump station failure and channel clogging are predicted. According to the method, linkage of water conservancy facility multi-source sensing, digital twin mapping and risk identification is realized, and the operation safety monitoring precision and the regulation and control efficiency are improved.

The invention relates to the technical field of constructional engineering informatization management, and discloses a constructional engineering full-period collaborative management and risk prediction system, which comprises a resource token definition module, a resource token generation module, a resource management module and a risk prediction module, and is characterized in that physical elements are mapped into discrete resource tokens configured with unit time delay charge rates; the process transactional modeling module is used for packaging the process into an atomic transaction unit containing a request and a release instruction; the discrete event rehearsal simulation engine executes circulation in the virtual time axis and records the hanging duration; the deadlock detection module monitors the occupancy topology in real time to identify a loop waiting closed loop; according to the dynamic priority arbitration logic, an accumulated lag weight value is calculated according to the product of the rate and the duration, resources are forcibly allocated accordingly to eliminate deadlock, the dynamic arbitration algorithm based on the time value gradient is constructed, the physical lag cost is converted into the calculation weight, and the capacity of the system for automatically converging to the optimal solution under complex constraints is improved.

The invention discloses an engineering project full-cycle cost intelligent accounting system based on a BIM technology, and relates to the technical field of constructional engineering informatization, and the system comprises a BIM visualization platform which is in communication connection with the following modules: a dynamic optimization scheduling module which is used for fusing a target engineering project BIM model and a real-time digital twinborn body, and introducing a bat algorithm to carry out dynamic optimization on construction resource nodes influenced by risks. According to the method, a dynamic resource topology network is constructed by fusing a BIM model and real-time digital twinborn data, accurate tracking and state perception of construction resources are realized, on the basis, a bat algorithm and a graph neural network are introduced to perform dynamic optimization and conflict coordination on resource configuration in a multi-risk concurrent scene, and the resource allocation efficiency is improved. And a rescheduling scheme and an optimal cost increment which conform to actual engineering logic are generated, the limitation of traditional static risk conduction simulation is broken through, and the adaptability of resource scheduling and the refinement level of cost control are remarkably improved.

The invention relates to the technical field of informatization management systems, and particularly discloses an AI-aid decision-making product full-life-cycle informatization management system which comprises a full-link data sensing module, a digital main line construction module, an AI decision-making center module, a service execution interface module and a man-machine collaborative interaction module. The method comprises the following steps: collecting multi-source heterogeneous data of each stage of a full life cycle of a product through a full-link data sensing module to form a full-amount data sequence with a space-time stamp; and in combination with a data fusion engine, an association graph construction unit and a twinborn model driving unit of the digital main line construction module, data cleaning, alignment, semantic fusion and cross-stage association are realized, a dynamically updated product digital twinborn model is constructed, real-time mapping of a physical entity and a virtual model is achieved, and the real-time mapping of the physical entity and the virtual model is realized. Unified and complete data support is provided for full-link decision making, and the problems of data fragmentation and prominent collaborative barriers of a traditional system are thoroughly solved.

The invention discloses a data processing method and system based on intelligent correction and electronic equipment, and relates to the technical field of educational informationization, and the method comprises the steps: analyzing a standard answer through natural language processing, extracting a standard knowledge point node and a connection edge, distributing a logic priority, calculating a node weight, and constructing a standard cognitive path map; analyzing student answers, mapping student knowledge point nodes through semantic matching, and constructing a student cognitive path map; comparing the two maps, and generating a score mark through a node matching state and sequence offset; detecting and complementing missing nodes and fracture paths, and constructing an atlas residual error scoring structure atlas; and calculating a structured score, and generating a report containing explanatory feedback. The system comprises five corresponding modules, and the equipment comprises a memory and a processor. The correction accuracy and interpretability are improved, the output report adapts to student feedback and teacher rechecking, and the method is suitable for education informatization automatic correction.

The invention discloses a building construction quality on-line monitoring system based on digital twinning, particularly relates to the field of building engineering informatization, is used for solving the problem of quality judgment deviation caused by dislocation breakpoints of multi-source evidences on a construction site, and is characterized in that a process event label is triggered through an event anchoring module to limit a window boundary and record an event identifier; the object binding module is used for immediately binding and generating object event table alignment records according to a component identity list and a positioning line, and the sequential judgment module is used for extracting a video key point frame and a sensing track, calculating an action synchronization difference and a form coincidence difference, constructing a deviation sequence and inputting the deviation sequence into a single-side CUSUM to obtain a judgment signal and fragment positioning; the judgment issuing module reads a signal calling rule base to generate quality judgment disposal guidance and recheck script issuing execution, and the recheck write-back module receives result write-back, lightly updates a fragment boundary and responds to a neighborhood record version to realize compact transmission from evidence obtaining to judgment execution to write-back so as to form a stable and traceable quality closed loop.

The invention discloses a component identifier matching method and system based on NLP semantic segmentation and a multi-level word library, and relates to the field of constructional engineering informatization, and the method comprises the steps: building a standard main word library and a preset compensation word library, carrying out the semantic segmentation of an input component identifier, and obtaining a segmented lexical element sequence, calculating semantic similarity and morphological similarity between the segmented lexical element sequence and entries in a standard main word bank, and performing standard term mapping based on the semantic similarity and the morphological similarity to obtain a standard term mapping result; carrying out structured data conversion on the segmented lexical element sequence which does not complete the standard term mapping by utilizing a regular expression mode to obtain structured data, and carrying out AI extension library matching on the segmented lexical element sequence which does not complete the structured data conversion to obtain a synonym matching result; and combining the standard term mapping result, the structured data and the synonym matching result to obtain component identification description. By implementing the method, the matching accuracy of the component identifier names in the engineering project can be improved.

The invention relates to the technical field of water conservancy informatization and intelligent early warning, in particular to a river network water regimen big data intelligent analysis early warning system which comprises a dynamic data fusion module, a topology sensing module, an overload propagation analysis module, an intelligent early warning decision module and an early warning execution module. Wherein the dynamic data fusion module is used for collecting multi-dimensional data of a river network area in real time; the topology sensing module is used for dynamically constructing a real-time topological relation graph of the river network connectivity; the overload propagation analysis module is used for extracting an overload coefficient of each node and outputting a risk diffusion path set; and the intelligent early warning decision module is used for generating a three-level early warning instruction by combining the positions of the engineering vulnerabilities in the real-time topological relation graph. According to the method, through fusion of the multi-source water regimen data and the dynamic topological structure, linkage of accurate identification and hierarchical response of the risk path is realized, and the intelligent early warning and rapid disposal capability of the sudden water regimen of the river network is remarkably improved.

The invention relates to the technical field of chemical enterprise production management, in particular to a chemical enterprise safety production informatization management system which comprises a sensing network layer architecture, a digital twin management platform, a risk management and control and decision center, a process closed-loop management center and an emergency cooperative processing platform. According to the chemical enterprise safety production informatization management system and method, through construction of a chemical knowledge graph, on the basis of a dynamic risk matrix and an AI prediction model library, equipment remaining service life prediction, process tiny anomaly capture and accident consequence simulation processing are realized; meanwhile, a root cause analysis module is used for associating low-level alarm and traversing a knowledge graph to automatically infer a fault root, physical equipment and a virtual model are bound through an entity-model mapping engine, the model state is dynamically updated in combination with a real-time rendering technology, and technological parameter optimization, accident deduction and scheme verification can be completed in an analogue simulation engine; and the management intuition and the decision-making scientificity are effectively improved.

The invention relates to the technical field of artificial intelligence and judicial informatization, and particularly discloses a multi-format document intelligent retrieval and semantic association system driven by a large model. Comprising a multi-modal document intelligent analysis module, an intention-driven semantic retrieval module, a knowledge graph enhanced association recommendation module, a retrieval result visualization and interaction module, a reinforcement learning-driven system optimization module and a multi-format document data storage module. According to the method, the multi-format judicial document is intelligently analyzed through a large model technology; the query intention of the user is accurately understood by means of a semantic retrieval technology Semantic association among the documents is deeply mined through the knowledge graph technology; a retrieval result is visually displayed through a visualization and interaction interface; and the retrieval strategy and model performance are continuously optimized according to user feedback by relying on a reinforcement learning algorithm, so that the retrieval efficiency and semantic association capability of the multi-format document in the judicial field are effectively improved, and the development of judicial informatization is promoted.

The invention provides a traditional Chinese medicine electronic medical record natural language processing and knowledge graph construction method and system. The method belongs to the technical field of the crossing field of traditional Chinese medicine informatization, artificial intelligence natural language processing and knowledge engineering, and comprises the following steps: performing multi-granularity semantic unit division on the traditional Chinese medicine electronic medical record to generate traditional Chinese medicine text semantic unit data; constructing a multi-granularity semantic decoupling engine according to the traditional Chinese medicine text semantic unit data so as to construct a traditional Chinese medicine text semantic analysis framework; performing traditional Chinese medicine unstructured text deep analysis according to the traditional Chinese medicine text semantic analysis framework, and performing multi-dimensional semantic feature extraction to obtain traditional Chinese medicine text semantic feature data and medical record time sequence data; through multi-granularity semantic unit division and deep analysis, the unstructured text in the traditional Chinese medicine electronic medical record can be effectively converted into structured semantic data, and the ability to understand and process traditional Chinese medicine clinical information is further improved.

The invention discloses a rice straw decomposition process full life cycle monitoring system based on a cloud platform, and relates to the field of agricultural informatization, and the system comprises a field data collection terminal which is used for collecting near infrared spectrum data, image data and operation and environment data of a straw decomposition process; the layered identification and modeling unit is used for identifying initial mass proportions and decomposition progress of soluble components, cellulose components, hemicellulose components and lignin components of the straws, and establishing a layered progress bar; the fusion progress calculation unit is used for weighting each layered progress bar based on the initial mass ratio to generate an overall decomposition progress bar; the progress output unit is used for simultaneously outputting a layered progress bar and an overall decomposition progress bar; and the mode mining unit is used for clustering the historical layered progress bars, forming a progress category prototype library and outputting potential blocking reasons. The problems that the field straw decomposition process is difficult to monitor in real time and the blocking reason is difficult to identify are solved.

The invention relates to a ship user behavior self-learning recommendation system based on a large model, and relates to the technical field of ship informatization. According to the system, through collection and fusion of multi-source heterogeneous ship user behavior data, a large-scale pre-training language model (large model) is utilized to carry out deep understanding and semantic mining on massive ship field text information and user behavior sequences, and a ship field knowledge graph or semantic vector space is constructed. The large model can identify and predict potential demands, behavior patterns and preference changes of ship users, and generates highly personalized, accurate and prospective ship service, product, route or information recommendations in combination with real-time operation data and external environment factors. Besides, a user feedback self-learning mechanism is introduced into the system, recommendation strategies and model parameters are continuously optimized according to interaction behaviors and explicit evaluation of the users in modes of reinforcement learning or continuous learning and the like, and intelligent iteration of the system and continuous improvement of the recommendation effect are achieved. According to the method, the challenges of a traditional recommendation system in the aspects of data complexity, semantic gaps and dynamic demand adaptability in the ship field are effectively solved, and the ship operation efficiency and the user satisfaction degree are remarkably improved.

The invention belongs to the technical field of artificial intelligence and educational informatization, and relates to a multi-mode knowledge graph enhanced intelligent teaching-assistant question-answering system. According to the method, the knowledge graph construction technology, the multi-modal content analysis technology and the large language model reasoning enhancement technology are comprehensively applied, and the semantic understanding, knowledge integration and reasoning generation capabilities of the intelligent teaching assisting system in an education and teaching scene are improved. The related technology comprises layout analysis of textbook documents, semantic description generation of image content, entity and relation extraction of text content, multi-modal knowledge graph construction and question and answer reasoning and natural language generation combined with the knowledge graph. Through cooperative application of the technologies, semantic interconnection can be carried out on various modal information such as texts, images and tables in the textbook, and a searchable and traceable textbook-level knowledge network is formed.

The invention discloses an informatization system dynamic verification method based on a zero-trust architecture, and the method comprises the steps: collecting and standardizing user operation requests of all business systems, and achieving unified resource and organization identification; a distributed encryption operation log link is constructed through an end-to-end encryption protocol, and safe synchronization and tampering prevention of an operation behavior abstract are guaranteed; extracting a multi-dimensional right decision variable, inputting the multi-dimensional right decision variable into an adaptive artificial intelligence decision model, dynamically generating a reversible permission factor set, and supporting fine-grained and rollback permission authorization and real-time automatic revocation; the log chain is encrypted and recorded in the whole process, intelligent abnormity monitoring and end-to-end traceability are combined, the consistency and compliance auditing of the global permission state are supported, and the security, traceability and intelligent self-adaptive treatment capacity of sensitive operation in the multi-organization cooperation environment are effectively improved.

The invention discloses a bridge fabrication machine construction full-period informatization management system based on an AI technology, and the system comprises a bridge fabrication machine global sensing subsystem which is used for collecting construction parameters in the construction operation process of a bridge fabrication machine; the edge processing subsystem is used for performing edge processing on the construction parameters acquired by the bridge fabrication machine global sensing subsystem; the digital twinning subsystem is used for establishing a digital twinning model for simulating the whole construction period of the bridge fabrication machine and synchronously mapping the construction parameters subjected to edge processing to the digital twinning model; and the safety monitoring subsystem is used for monitoring the working safety of the bridge fabrication machine based on the digital twin model. The method is used for solving the problems that in the prior art, the monitoring and analysis capacity of the construction process of the cantilever bridge fabrication machine is poor, and operation safety is not facilitated, and the purposes of informatization management of the construction process of the bridge fabrication machine and improvement of the safety and scientificity of the construction process of a continuous beam are achieved.

The invention discloses a wide-area time traceability credible authentication method in a power heterogeneous network environment, and belongs to the technical field of power system informatization and automation. Comprising the following steps: acquiring various high-precision time source information in a power heterogeneous network environment, and acquiring an initial time reference of the power system time synchronization device; generating uniform reference time, and embedding a digital watermark containing time source information and credibility thereof for each timestamp by using the digital watermark embedding module; controlling the power system time synchronization device to sequentially generate time transmission fingerprints at all levels of network nodes; constructing a unique time fingerprint chain covering the whole link; packaging the time fingerprint of each time transmission node and the traceability information thereof, and performing uplink storage; precise prediction and optimal control of time transmission errors are realized; if the overall cumulative time error exceeds a range of + / -10 [mu] s, the predictive correction is maintained until the error is controlled within + / -10 [mu] s.

The invention discloses an ERP (Enterprise Resource Planning) data intelligent supervision method based on the Internet of Things, which relates to the technical field of enterprise informatization, and comprises the following steps: constructing a time sequence integrity observation layer in an Internet of Things data acquisition link, embedding a mirror image time anchor in each sensor sampling point, recording electromagnetic interference, time service offset and queuing delay, generating a phase fingerprint time baseline, and obtaining a phase fingerprint time baseline; constructing a unified time reference framework; operating a causal coherent analysis mechanism based on a unified time reference frame, comparing instantaneous offsets of a mirror time anchor and a real-time timestamp, identifying a phase inversion region, extracting information of a corresponding sampling node, a production line position and an energy consumption unit, generating a high-risk time slice list, and determining a time correction boundary. According to the method, a time sequence observation layer and a time reference frame are constructed, phase abnormity is identified, a data trend is reconstructed, a regulation and control instruction draft is generated, sampling time sequence recovery and scheduling convergence are realized through time inversion control, data consistency and decision accuracy are improved, and a closed-loop control system is constructed.

The invention discloses an electronic medical record data synthesis method based on semantic processing, and relates to the technical field of medical informatization, and the method comprises the following steps: S1, constructing a probabilistic medical knowledge graph; s2, generating a semantic representation vector; s3, constructing a multi-dimensional dynamic space-time atlas; s4, generating a discrete personalized disease course event sequence with space-time coordinates; s5, taking the discrete personalized disease course event sequence and the corresponding medical entity semantic representation vector as condition input, guiding the improved TSDiff model to execute an iterative denoising process, and outputting a multi-dimensional random disease course trajectory; s6, forming multi-modal electronic medical record data; and S7, performing multi-dimensional quality evaluation on the multi-modal electronic medical record data. According to the method, the limitations of logic inconsistency, modal splitting and model capability solidification in a traditional synthesis method are overcome, and an efficient and accurate solution is provided.

The invention relates to the technical field of power supply services, in particular to a method and system for monitoring the business expansion process of a power supply enterprise in real time. The mobile terminal collects field data, and the edge data server generates a feature sequence to be subjected to compliance comparison; and the rule fusion container fuses the rule base and the historical problem base to generate compliance data. On the basis of field standardized mapping and version abstracts, existence, applicability, consistency and validity period verification is executed on the forced / recommended attributes, and compliance, element missing or non-compliance items are output; and generating positioning information for the non-conformity items, including an informatization problem identifier of a version and a rectification suggestion, converting the positioning information into a work order with a time limit, caching the work order in a weak network, and performing reconciliation and bidirectional verification with a central server after the network is recovered. And the nodes finish event triggering compliance record uploading, and the center summarizes and archives to form process-level compliance. According to the scheme, rule upgrading controllability, evidence chain traceability and process compliance closed loop are realized, and accuracy and efficiency are improved.

The invention relates to the technical field of constructional engineering informatization and data security, and particularly discloses a BIM and block chain-based whole-process engineering cost data collaborative management system, which comprises a data analysis and dependency graph construction module, which is used for analyzing BIM model component attributes and association relationships and constructing a directed dependency graph; the loop dependency detection and resolution module is used for identifying and resolving a loop dependency structure in the graph; the topological sorting processing module is used for generating an ordered calculation sequence of the components; the cryptographic abstract calculation module is used for generating a unique abstract value of each component in sequence; the global abstract generation module is used for aggregating and generating a global cryptographic abstract representing the overall logic state of the model; and the block chain evidence storage module is used for combining the global abstract and the related metadata to perform uplink evidence storage.

The invention discloses a power failure event cooperative processing method, system and device based on geographic information and a medium, and relates to the technical field of power system power distribution network fault processing and informatization. The method comprises the following steps: when a power failure event occurs, acquiring multi-source heterogeneous data from an associated system; performing fault analysis on the multi-source heterogeneous data through a fault diagnosis model, and outputting fault positioning information and a fault type; obtaining associated maintenance resource state data and real-time traffic road condition data according to the fault positioning information; the maintenance resource state data comprises a rush repair team position, a skill level and a vehicle state; and based on the fault positioning information, the fault type, the user attribute, the historical work order data, the maintenance resource state data and the real-time traffic road condition data, generating an optimal maintenance scheduling scheme through a reinforcement learning scheduling model. The cross-department and cross-business cooperative processing is realized, and the first-aid repair efficiency and the resource utilization rate are remarkably improved.

The invention discloses a construction management system and method based on multi-source data analysis, and relates to the technical field of building construction informatization and intelligent management and control, and the method comprises the steps: capturing a front path task completion signal and a subsequent task starting instruction; obtaining preposed task completion time, a dynamic condition type and a threshold parameter; executing time logic verification based on the dynamic condition type, and judging a construction dynamic context ready state; bIM design coordinates, field positioning coordinates and space tolerance parameters of the construction machinery are obtained, and space logic verification is executed by calculating space deviation; when both the time verification and the space verification pass, subsequent task state conversion is allowed, and otherwise, blocking is carried out; and finally generating a structured report containing all verification parameters and results.

The invention relates to the technical field of medical informatization and intelligent scheduling, and particularly discloses a ward nursing process prediction and dynamic scheduling method and system.The ward nursing process prediction and dynamic scheduling method comprises the steps that firstly, a digital twinborn simulation environment synchronized with a physical ward in real time is established, and a nursing process is simulated through a multi-agent network; carrying out multi-time sequence deduction based on the environment, generating a prospective scheduling instruction set, and issuing and executing the prospective scheduling instruction set; calculating a prediction mismatch degree index by collecting actual execution data and comparing the actual execution data with a plurality of dimensions of an expected state; when the index exceeds a dynamic threshold value, a meta control layer is triggered to carry out self-adaptive adjustment on simulation environment parameters, and the self-adaptive adjustment comprises reconstruction of an agent behavior logic weight or switching of a scene deduction mode; and deducing and generating an updated instruction set again based on the adjusted environment to form closed-loop optimization.

The invention provides a production process configuration method and device for a manufacturing execution system in the technical field of industrial manufacturing informatization. The method comprises the steps that S1, customized information is extracted from order data to generate a production task instruction; s2, matching resource requirements based on the production task instruction to generate a resource allocation list; s3, generating a flow configuration file based on the resource allocation list and the production task instruction, and issuing the flow configuration file to a corresponding production execution unit to execute production operation; s4, collecting production data from each production execution unit in real time, recording production logs in real time, and carrying out standardized processing and unified storage on the production logs; and S5, carrying out real-time monitoring on a production task state, a production resource state, a system operation state and a change condition of order data, and dynamically reconstructing a process configuration file. The method has the advantages that the flexibility, the automation level and the response efficiency of production process configuration are greatly improved.

The invention provides an intelligent building energy-saving control system based on AI energy consumption prediction, and the system comprises a data construction module which is used for designing a sensor network and a building information model, and collecting a standardized multi-dimensional data set; the behavior recognition module is used for analyzing a user moving track and a space behavior mode, constructing a three-dimensional thermodynamic diagram and predicting a people number density sequence; the energy consumption prediction module is used for predicting short-term energy consumption, medium-term energy consumption and long-term energy consumption; the energy-saving control module is used for designing a target function and obtaining a control strategy set by using an NSGA-III algorithm and a digital twinborn simulation platform; the distributed execution module is used for performing control adjustment and real-time feedback on the building equipment by utilizing an edge controller; and the maintenance management module is used for visual interaction, control strategy execution and building equipment maintenance management. According to the invention, a personalized energy-saving strategy, active control adjustment, multi-dimensional energy consumption prediction and intelligent optimization can be realized, and refined and informatization management and maintenance of energy-saving control can be realized.