706 results about "Management process" patented technology

The invention discloses a BIM-based building electromechanical full life cycle management platform and an optimization strategy thereof, relates to the technical field of building informatization management, and solves the defects of the existing BIM technology in the aspects of processing efficiency, model precision, data synchronization and change management. According to the invention, a data layer is used for data cleaning and standardization through a machine learning model, and distributed storage is realized through a cloud management system; the model layer constructs and updates a high-precision BIM model; the synchronization collaboration layer ensures the consistency and traceability of data by using a real-time synchronization mechanism and a block chain technology; the decision analysis layer performs data analysis and prediction through a deep learning algorithm; the full life cycle management layer integrates historical data and current data and automatically triggers a management process; according to the method, the data processing efficiency and the model precision are greatly improved, and the seamless sharing capability of information and the transparency of data synchronization and change management are remarkably improved, so that the overall collaborative efficiency and the management level of a project are enhanced.

The invention discloses a building operation and maintenance management method and system based on big data, and relates to the technical field of building intellectualization, and the method comprises the steps: collecting multi-source heterogeneous data, executing data standardization processing, and generating a standard data stream; constructing a virtual building model based on a digital twinning technology, mapping the standard data stream to a corresponding device node of the virtual building model, and generating a device feature matrix; inputting the equipment characteristic matrix into a deep learning network, training to generate an energy consumption prediction model, and outputting an energy consumption prediction sequence; a multilayer perceptron health scoring model is constructed based on the energy consumption prediction sequence, and a fault early warning priority list is generated in combination with an equipment weight coefficient; and automatically generating a maintenance work order according to the fault early warning priority list. Through the maintenance effect evaluation and secondary maintenance mechanism, a complete closed-loop management process is formed, the maintenance quality is ensured, the maintenance strategy is continuously optimized, and the overall operation and maintenance management level is improved.

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

The invention relates to the technical field of electric line fault detection, and discloses a power transmission line fault early warning system and method based on big data driving, and the system comprises a state prediction module, a risk assessment module, an early warning decision module and a management execution module. The state prediction module constructs a prediction model by using historical operation data, environmental conditions and line parameters, and outputs future state indexes; the risk assessment module comprehensively considers multi-source information such as real-time operation data and historical maintenance records, and assesses a current fault risk index; the early warning decision-making module models the management process into a Markov decision-making process, and carries out early warning decision-making based on the output of the two modules; and the management execution module is responsible for managing and executing the decision result in real time. By comprehensively utilizing the big data technology, the accuracy and the real-time performance of power transmission line fault early warning are improved, the defects of a traditional fault management mode are overcome, and a powerful guarantee is provided for safe and stable operation of a power system.

The invention relates to the technical field of consumable traceability, and discloses an SPD medical consumable intelligent monitoring and traceability management system, which comprises a consumable warehousing module for inputting information through a UDI code and updating the inventory; the receiving plan generation module is used for calculating the demand quantity of each department for different types of consumables according to the demands of clinical departments, and generating a receiving plan according to the demand quantity; according to the distribution and use module, the SPD system distributes the consumables according to the receiving plan and selects the earliest batch for distribution according to the FIFO principle or the FEFO principle; and the refund processing module is used for re-evaluating the remaining period of validity when the unused consumables are refund. According to the method, UDI coding runs through the whole consumable management process, a complete closed-loop management process of intelligently analyzing and predicting future demands, dynamically optimizing inventory, recording consumable circulation information in the whole process, generating and finally purchasing execution is introduced, an informatization means and a management optimization strategy are combined, and the SPD medical consumable management level can be effectively improved.

The invention relates to the technical field of campus management, and particularly discloses a smart campus management system based on big data, an event-driven data management architecture is used for dynamically collecting, integrating and associating multi-source heterogeneous data in a campus, and generating a standardized event stream; the dynamic resource scheduling engine is in communication connection with the event-driven data governance architecture, generates a resource allocation instruction based on event types and priorities in event streams, and dynamically deploys campus resources; the closed-loop evaluation optimization module receives a resource scheduling result of the dynamic resource scheduling engine and generates a multi-dimensional evaluation index, and the multi-dimensional evaluation index is fed back to the data governance architecture through root cause analysis so as to optimize a subsequent decision; the privacy enhancement processing unit integrates a federated learning framework and a differential privacy algorithm, performs collaborative analysis on cross-system data and ensures the anonymity of individual data; through three core technologies of dynamic data management, intelligent resource scheduling and closed-loop evaluation optimization, intelligent upgrading of the whole campus management process is realized.

An agent management platform for providing a runtime environment for the execution of agents can be used to manage process deployments. The agents can be configured to perform specific tasks on software applications within defined objectives. Using an obtained execution request, the agent management platform can associate agents with one or more nodes by comparing node constraints against agent constraints. The nodes can include computers equipped with containers that provide isolated runtime environments for agent execution. The agent management platform can instantiate agents in corresponding containers on the computers of associated nodes, and / or execute the instantiated agents to perform corresponding tasks.

The invention discloses a wire harness manufacturing management system and method based on artificial intelligence, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: inputting a structured feature vector and a process constraint condition into a multi-target reinforcement learning model, and generating a process parameter instruction; the process parameter instruction is executed, the product yield is monitored in real time, and cross-process quality tracing is carried out on the abnormal product yield; historical data of abnormal batches in crimping, assembling and testing procedures are traced, the defect root cause probability of each procedure is calculated based on a Bayesian causal network, and primary and secondary root causes of quality defects are obtained and analyzed; and dynamically updating process constraint conditions according to primary and secondary root cause analysis results, adjusting a reward function of the multi-target reinforcement learning model, and re-optimizing a process parameter instruction. According to the invention, the operation state of the production equipment is accurately captured, the production process is optimized and adjusted in real time, and a closed-loop management process is formed, so that the production flexibility, efficiency and product quality are remarkably improved.

The invention discloses a decentralized public key infrastructure constructed based on a block chain and a trusted network, and belongs to the field of information security PKI public key infrastructure, and the method comprises the following steps: 1, building a decentralized CA mechanism; 2, a user submits a certificate application / update / abolish request; the user certificate request is submitted to a decentralized CA mechanism, and the decentralized CA mechanism service calls the block chain to generate / update / abolish the digital certificate; and 3, verifying the user certificate request by using a block chain technology. The certificate request is validated using a smart contract technique. The decentralized public key infrastructure constructed based on the block chain and the trusted network aims to solve the problems of single-point failure, non-transparent certificate, time-consuming certificate revocation and the like existing in a CA mechanism in a traditional PKI system, and emphatically realizes that the problem that the PKI trusted system collapses due to the failure of the CA mechanism in a certificate life cycle management process of the CA mechanism is solved; and meanwhile, certificate transparency is realized, and certificate revocation efficiency is improved.

The invention provides an urban construction and traffic engineering investigation and design enterprise product quality management system and method. The system comprises a cross-project type quality data fusion module, a dynamic defect evolution prediction module, an intelligent layered spot check engine, a three-dimensional quality situation deduction module, a conference knowledge graph construction module, a result influence evaluation module and a self-adaptive file management system. All the modules are connected through a unified data bus to form a closed-loop management process of quality data acquisition, analysis, decision and feedback. According to the system, through the functions of multi-modal data fusion, defect prediction, intelligent spot check, situation deduction, knowledge precipitation, achievement evaluation, file management and the like, the whole-process intelligent management and control of the project quality are realized, and the management efficiency and the decision scientificity are improved.

The invention relates to the technical field of workflow optimization, in particular to an enterprise management process optimization method and system, and the method comprises the following steps: obtaining the length of an approval task queue, the average approval time and the number of pending tasks, calculating a task backlog rate, calling task flow fluctuation to set a node load state coefficient, and generating a load distribution state of approval nodes. According to the invention, the task circulation priority is calculated based on the time constraint and the service weight, so that the emergency task is circulated preferentially, the approval efficiency is improved, the approval path is sorted through the node processing capability and is adjusted and optimized, the task circulation adapts to the load change, the flow blocking risk is reduced, and the task state change record is screened based on the circulation path. The data screening accuracy is improved, the effectiveness of task execution data is ensured, the abnormal detection is combined with the time sequence trend and abnormal node analysis, abnormal task tracking is more efficient, problem nodes are traced accurately, and abnormal task processing is accelerated.

The invention discloses a power grid material sampling inspection management method for realizing whole-course tracing based on intelligent sample sealing, and relates to the technical field of electric power material management and intelligent perception, and the method comprises the following steps: S1, an initialization stage: executing a sample sealing coding segmentation pre-configuration process, distributing independent numbered segments to each sample sealing terminal, and the central control module synchronizes the use state of the terminal code to realize distributed isolation of code generation. According to the invention, coding uniqueness is realized through segmented pre-configuration and global duplicate checking, identity information security is guaranteed by adopting chip one-time write protection and tamper-proof technologies, and sample packet switching and data counterfeiting are effectively prevented by combining automatic acquisition and multi-round consistency comparison. Abnormal recognition and closed-loop processing ensure that abnormal events are frozen in time and responsibility is traced, and irregular samples are prevented from flowing into subsequent links. The whole-process auditing and dynamic optimization enable the management process to be self-perfected, and the intelligence, standardization and reliability of sampling inspection of the power grid materials are remarkably improved.

The invention discloses a big data-based natural gas pipeline maintenance optimization method and system, relates to the technical field of natural gas pipeline maintenance, and aims to construct a structured monitoring data set, construct a graph model of pipeline states and risk factors, establish a prediction model, introduce a memory mechanism to process low-frequency anomalies, and generate and optimize a maintenance scheduling scheme. According to the natural gas pipeline maintenance optimization method provided by the invention, the map model and the prediction model are constructed based on the multi-source monitoring data, the causal path between the pipeline operation state and the external risk factor can be identified, and the maintenance efficiency is improved. Maintenance task generation, early warning triggering and terminal linkage operation are completed through risk level evaluation and scheduling optimization, collected monitoring data are used for model training and map updating after being processed, a closed-loop management process is formed, and the method is suitable for natural gas pipeline state recognition and maintenance scheduling in various operation environments.

The invention discloses a warehouse in-out rechecking management system based on automatic visual scanning, which relates to the technical field of warehouse rechecking management, and comprises a pose acquisition unit, a visual calibration unit, a cargo reading unit, a record management unit, a warehouse-in rechecking unit and a warehouse-out rechecking unit, the pose acquisition unit is used for acquiring a color image and a depth image of a target cargo in a to-be-identified area so as to obtain pose information of the cargo, and the visual calibration unit is used for obtaining a relation matrix of a camera coordinate system and a mechanical arm coordinate system by calculating a rotation matrix and a translation matrix. And space coordinates in an image collected by the camera are converted into a mechanical arm coordinate system. The automatic visual scanning and mechanical arm technology are combined, the intelligent level in the warehouse management process can be greatly improved, the method is more suitable for actual complex warehouse scenes, the cargo warehouse-in and warehouse-out speed can be increased, and the cargo checking accuracy can also be improved.

The invention discloses a software and hardware combined data interaction method and system based on a Modbus communication component. According to the method and the system, different types of Modbus slave devices are managed through a unified communication configuration file and a point table configuration file, so that compatible access to heterogeneous devices is realized; through an optimized point table analysis mechanism, efficient and self-adaptive data acquisition of discontinuous register addresses is supported, and fine processing and conversion are performed on different data types; a graphical configuration management tool is provided, and the equipment configuration and point table management process is simplified; and a standardized command model is used, so that unified control and data interaction of an upper-layer application on Modbus equipment are facilitated. According to the invention, the flexibility, usability and data interaction efficiency of Modbus communication can be remarkably improved, the system integration and operation and maintenance cost is reduced, and an efficient and reliable Modbus communication solution is provided for the field of industrial automation.

The invention relates to the technical field of big data analysis and data processing, and provides an intelligent power utilization load management method based on big data analysis, which constructs an accurate power utilization load prediction model by integrating historical power utilization data, climate data, a power grid equipment state and user behavior data. According to the method, the security and traceability of prediction data are improved by adopting a block chain technology, and automation of an electrical load management process is realized by means of an intelligent contract. The method comprises the specific steps of data acquisition and preprocessing, load prediction model construction and verification, prediction data storage and hash value generation, intelligent contract writing and execution, and process node data processing and evaluation. The method effectively solves the problems of load data abnormity and model errors, and improves the stability and management efficiency of a power grid system.

The invention discloses a cross-platform self-adaptive internationalization language dynamic switching method based on a database. According to the method, a multi-language resource database table structure is constructed, multi-language resources are stored in a unified mode, and data association and a unique identifier are established; providing a unified universal language request interface, receiving a request query database to obtain resources, writing the resources into a cache layer, and generating a version identifier; establishing a multi-terminal adaptation mechanism, realizing incremental updating of the front-end application according to the cache version identifier, and adapting to different platform and equipment requests; seamless updating of the interface is achieved by means of an event mechanism, and reloading of the application is avoided; an expansion management platform is established, and addition, deletion, modification and check, batch import and automatic translation interface integration of language resources are supported. According to the invention, the problems of dispersed language resource management, inconvenient switching, poor cross-platform compatibility and the like in the prior art are solved, the management process can be simplified, the cost can be reduced, the system performance and expandability can be improved, and smooth and convenient multi-language use experience can be brought to users.

The invention discloses a government affair department knowledge base access authority control method based on a block chain, and relates to the technical field of block chains and information security, distributed nodes jointly participate in decision making, the performance bottleneck of a single control point and the single point fault risk are effectively eliminated, and the reliability and stability of a system are remarkably improved; when a plurality of departments need to collaboratively update a strategy, the intelligent contract based on the threshold multi-signature mechanism can automatically execute voting aggregation and a strategy effective process without depending on manual operation of a central administrator, so that the efficiency and the automation level of cross-department collaboration are greatly improved, and the instantaneity and the consistency of strategy change are ensured; the inherent non-tampering and traceable characteristics of the block chain provide powerful auditing guarantee for the whole authority management process; and each policy update request, voting process, final decision and policy version switching are completely recorded on the chain to form a non-repudiated audit clue.

The invention provides a professional online collaborative editing method and system for hydropower project cost schemes. The professional online collaborative editing method comprises a standard management process, an intelligent collaborative editing process and a release state synchronous updating process. The standard management process comprises the steps of performing automatic analysis and data standardization conversion on an industrial standard file based on a deep learning model, generating a system rule set and storing the system rule set in a database; and based on the system rule set, automatically generating a standardized filling template of each specialty. According to the micro-service architecture-based intelligent online collaborative editing method and system for the hydropower engineering, a natural language processing NLP technology, a deep learning algorithm and a transaction management mechanism are combined, and the system has the functions of real-time grammar and spelling inspection of filled content, intelligent recommendation, semantic understanding, real-time difference detection, multi-user conflict processing and version control; the problems that communication cost is high, version control is difficult, data verification is not strict and multi-user cooperation is not smooth in water-power engineering cost scheme compiling are solved.

The invention relates to the technical field of data processing, in particular to a financial data synchronization method and system, computer equipment and a storage medium, and the method comprises the following steps: based on input financial data, performing formatting and data cleaning, preprocessing the data, analyzing fund flow data, and performing consistency verification on the fund data; inconsistent data are identified and recorded, and a consistency verification result is generated. According to the method, by analyzing the data and extracting the incremental data needing to be synchronized, the synchronization efficiency is improved, real-time updating of the data is ensured, prediction of synchronization task time is carried out in combination with calculation resource requirements and real-time system loads, the synchronization priority is calculated, the reasonability of resource use is improved, the synchronized data is comprehensively verified, and the synchronization efficiency is improved. Data missing, repetition and inconsistency are found and corrected in time, the accuracy and consistency of financial data are ensured, the efficiency of financial data synchronization is improved, accurate and timely transmission and updating of the data are ensured, and the financial management process is optimized.

The present invention discloses a supply chain logistics information management system based on artificial intelligence, specifically related to the field of artificial intelligence technology, including a linear fitting module, a non-linear fitting module, a dual-mode construction module, a distribution verification module, and a management intervention module. The linear fitting module obtains linear conventional coefficients according to linear scenario information, the non-linear fitting module obtains non-linear special coefficients according to non-linear scenario information, the dual-mode construction module constructs a dual-mode management model based on the linear conventional coefficients and non-linear special coefficients and outputs a time cost delay index, the distribution verification module classifies the delay status in the supply chain logistics information management process, and the management intervention module conducts intervention management according to the classification results. This application predicts the time cost of the most time-consuming and laborious customs declaration and tax payment links in the supply chain logistics information management process, improving the management effectiveness and real-time performance of the entire logistics information management chain.

The invention provides an electromechanical equipment full-life-cycle management system, and the system comprises an obtaining module which is used for obtaining the current stage of a full life cycle of electromechanical equipment, and determining equipment variable parameters and equipment measurement parameters which need to be monitored at present; the offset module is used for acquiring the running state and the environmental parameters of the electromechanical equipment, and determining a measurement parameter offset value based on the running state and the environmental parameters; offset is carried out on the equipment measurement parameter based on the measurement parameter offset value, and an offset measurement parameter is obtained; the measurement module is used for determining corresponding parameter measurement equipment based on the equipment variable parameters; controlling parameter measurement equipment to measure equipment variable parameters of the electromechanical equipment according to the offset measurement parameters to obtain a parameter set; and the control module is used for analyzing the parameter set and controlling the operation of the electromechanical equipment based on an analysis result. According to the invention, the defects of inaccurate data measurement and resource waste in the current full life cycle management process are overcome.

The invention provides a multi-core parallel simulation method and device and electronic equipment, and relates to the technical field of computer simulation, and the method comprises the steps: determining all simulation entities in a simulation environment; all simulation entities in the simulation environment are respectively packaged into independently running entity processes, and a message manager module, an object manager module and a time manager module are respectively packaged into independently running management processes; running each entity process and the management process in parallel on respective pre-allocated operation cores, and monitoring each operation core; according to the resource use data and the task completion progress of the entity process and the management process on each operation core, determining an overloaded operation core; and dynamically adjusting the execution sequence and resource allocation of the entity process and the management process on the overloaded operation core. According to the invention, through real-time monitoring and dynamic adjustment, load balancing is effectively realized, and the situation that some cores are overloaded and other cores are idle is avoided.

The invention provides a time sequence data compression-based database monitoring operation and maintenance method and system, which realize real-time monitoring of various index data of a database platform through an efficient data acquisition and compression technology. The system can efficiently collect various performance data generated in the operation process of the database, optimizes time series data through a compression algorithm, and reduces redundant storage of the data. In a data storage and management process, a primary differential sequence and a secondary differential sequence are calculated, so that the stored data volume is reduced; according to the method, a trend in an original data sequence is removed by using difference, so that a subsequent difference sequence is easier to compress, and meanwhile, for non-constant difference, by setting a dynamic threshold value and only recording a difference value greater than the threshold value, small changes are ignored and the compression ratio is improved on the premise of ensuring that important data information is not lost. And on the other hand, the regularity of the differential sequence is judged through Srelative, and a compression strategy can be selectively applied, so that proper compression methods can be specifically applied to time sequence data with different characteristics, and the processing efficiency is improved. Through the design, the storage and processing efficiency of the compressed data is improved, the system can decompress and analyze the data more quickly, and the running state of the database is monitored in real time.

The invention relates to a comprehensive management process design system and method based on AI code interpretation, and belongs to the technical field of computer networks. The system comprises a process design console, an AI code interpreter and a business logic execution framework, the flow design console is used for providing a Web interface, so that a user can design and manage a flow in an interactive form, including interactive natural language programming, real-time feedback and preview, flow deployment and management, and historical record and version control; the AI code interpreter is used for converting business requirements and processes expressed by a user in a natural language form into executable codes, and comprises a natural language understanding sub-module, a code generation sub-module and a security verification sub-module; the business logic execution framework comprises a code execution sub-module, a data access sub-module and an exception handling sub-module. According to the method, the technical threshold of process design is lowered, personnel can easily master, and organic combination of intelligence and humanization is achieved.

The invention discloses a code version management method based on multi-person collaboration, belongs to the technical field of software development, and in the code version management method based on the GIT distributed version control system, efficient work is guaranteed through modes of code submission, combined submission, code combination and the like. According to an existing cooperation mode, in the development process of one iteration cycle, developers can submit codes for multiple times, and after iteration development is completed through cooperation of multiple persons, many submission records appear, and therefore the code submission records are disordered. Through the technology, after each developer completes the respective task, the submission records are combined into one, so that the readability of submitted information is greatly improved. By means of code submission, merging submission, code merging and the like, high efficiency of work is guaranteed, the code submission management process is standardized, many benefits are brought to software development teams, and the method is an important means for improving software development efficiency and quality.

The invention relates to the technical field of safety production management, and discloses a safety production hidden danger closed-loop management and control supervision system and a risk assessment early warning method, and the system comprises an environment modeling module which is used for building a digital model of a production unit and calculating a systematic instability coefficient based on historical data; the risk assessment module is used for quantifying the initial risk potential energy in combination with the coefficient and the hidden danger inherent attribute; the risk evolution module is used for dynamically updating risk potential energy according to a time and space coupling rule; the closed-loop verification module is used for judging the actual effectiveness of the intervention measure by comparing the management entropy before and after the intervention after the intervention measure is implemented; and the self-adaptive feedback module is used for automatically updating the systematic instability coefficient in the environment model according to the judgment result. According to the method, risk quantification, dynamic early warning, effect verification and model self-optimization are integrated, a complete closed-loop management process is formed, and the scientificity and foresight of safety production management are remarkably improved.

A change management task automation system reduces manual effort required for change audits and streamlines the change management process, enforcing preventative compliance with change management best practices. A plurality of automation modules provides change management task automation functionality for several processes, including software change management, database change management, key report change management, data lake change management, patch change management, and controlled version document repository management automation.

The invention relates to the technical field of information security, in particular to a key management system and method based on a medical block chain, and the system comprises a state evaluation module, a reverse tracking module, a foresight analysis module, an intelligent alarm threshold adjustment module, a resource priority scheduling module, a reliability analysis and fault tolerance module, and a process optimization and decision support module. According to the method, risk assessment and classification are effectively carried out and a key access control strategy is adjusted by adopting a support vector machine, a decision tree algorithm and a deep learning algorithm, a key use trend is predicted by utilizing an autoregression integral moving average model and a long-short-term memory network, and the key access control strategy is optimized through an isolated forest and a deep learning network. An alarm threshold value is dynamically adjusted, the early warning capability of the system for potential security threats is improved, a key management process is optimized through a genetic algorithm and a particle swarm optimization technology, a security decision and a response strategy are executed in combination with a rule engine and a machine learning model, and the response efficiency and the decision accuracy are improved.

The invention discloses an airport operation and maintenance data storage method and device based on a block chain and electronic equipment, and relates to the field of airport operation and maintenance data security management.The method comprises the steps that a first hash value is calculated for collected original operation and maintenance data, and a probe private key is used for conducting double-layer digital signature, transmitting the signed operation and maintenance data packet to an intelligent operation and maintenance system by adopting a preset encryption communication channel, calling a block chain intelligent contract through the intelligent operation and maintenance system under the condition that the integrity verification of the single piece of original operation and maintenance data is passed, and verifying the legality of the double-layer digital signature; and performing structured processing on the original operation and maintenance data passing the signature verification, and storing the original operation and maintenance data to a block chain network. According to the method and the device, the technical problems that data among multi-source heterogeneous systems is insufficient in credibility in a management process of airport operation and maintenance data, the security of data transmission cannot be guaranteed, and data leakage is easily caused in related technologies are solved.