41 results about "Optimal management" patented technology

The invention provides a Docker Registry management optimization mode. The Docker Registry management optimization mode comprises the steps that based on Docker Registry management requirements, a Docker Registry native management mode corresponding to the management requirements is determined; based on the management requirements, a corresponding optimization management mode is determined; optimization is conducted on the native management mode through the optimization management mode, and corresponding Docker Registry management operation is conducted through an optimized operational order. According to the embodiment, the problems that the native Docker Registry control operational mode is unfriendly, management operation is complex, and the network operation and maintenance cost is too high are solved. For example, storage catalogs of mirrored documents are changed to cluster-type share mirrored storage equipment from a local storage area, namely, single-machine mirrored storage is changed to cluster-type mirrored storage, and on the condition of large-scale cluster-type machinery equipment, the mirrored document maintenance cost can be greatly lowered. For another example, by means of the mode that multiple Registry service operation is simplified, the operating difficulty of Docker Registry management is lowered, and the network maintenance operational experience is improved.

The invention discloses a medical equipment full-life-cycle management system based on a digital twinning technology. The medical equipment full-life-cycle management system comprises four modules. The digital twinborn model construction module constructs and updates a simulation medical equipment digital model in real time; the intelligent data acquisition and monitoring module is responsible for data acquisition, transmission, monitoring and interface design; the intelligent decision and maintenance module realizes fault prediction, maintenance plan generation and record management; and the comprehensive analysis and optimization management module performs data analysis, optimization decision and life cycle planning. The system has the remarkable advantages that when equipment is used, the running state of the equipment is adjusted in time through real-time monitoring and intelligent analysis, and the fault rate and the maintenance and replacement frequency are reduced; in the aspect of cost control, a maintenance strategy and a purchase decision are optimized, and expenditure is reduced; at the medical service quality level, stable and efficient operation of equipment is guaranteed, patient safety is improved, and reasonable utilization of medical resources is achieved.

The invention discloses a safe penetration type management method and system for an engineering construction project, and relates to the technical field of constructional engineering, and the method comprises the steps: collecting engineering entity data in real time, carrying out the preprocessing, and generating an engineering state vector; based on the engineering state vector, constructing a digital twinborn model, calling multi-physics field coupling simulation to simulate the whole construction process, and generating a risk early warning report; uploading the risk early warning report and historical construction data to a federated platform, and constructing a dynamic security knowledge graph; performing hierarchical feature learning on nodes in the dynamic security knowledge graph, simulating decision behaviors of a manager, and generating an optimal management and control rule; based on the optimal management and control rule, driving a construction site management mechanism to operate, and forming a closed loop report; by using the digital twin model and the multi-physics field simulation technology, the accurate prediction of potential safety hazards possibly occurring in the construction process is realized, and the accuracy and timeliness of risk early warning are greatly improved.

The invention provides an intelligent construction site equipment remote monitoring management method and system based on the Internet of Things, and relates to the technical field of monitoring management, and the method comprises the steps: collecting the operation parameters of target construction site equipment through an Internet of Things sensor; constructing a life monitoring model in combination with the operation parameters; performing remote monitoring on the target construction site equipment based on the life monitoring model to obtain an equipment operation condition; and performing equipment maintenance management according to the equipment operation condition. According to the invention, the technical problem that the construction progress and the engineering efficiency are further influenced due to the lack of personalization and precision of maintenance decisions caused by insufficient management of the life cycle of construction site equipment in the prior art can be solved, the technical targets of intelligent monitoring and optimal management of the whole life cycle of the equipment are achieved, and the purposes of improving the operation efficiency of the equipment and reducing the construction cost are achieved. And the technical effect of finishing the project on time is ensured.

The application discloses a kind of management methods and systems to cope with nursing rehabilitation service, it is related to nursing management technical field;The method includes the steps of: collecting and maintaining the personal information of all users;Regular health assessment is carried out to target user, and obtains rehabilitation state data set;Its technical points are: the daily nursing time length fine tuning operation when the nursing level has reached the limit is constructed, and the ideal range deviation degree of Barthel index, PEI value and body state evaluation value is introduced therein, so that the overall scheme can flexibly adjust the nursing time length under the premise that the nursing level is unchanged or cannot continue to adjust, to adapt to the rehabilitation trend change, on the one hand, individualized nursing resource allocation is realized according to functional state difference, while maintaining the stability of nursing level, enhance service flexibility, on the other hand, avoid the nursing disjointedness phenomenon caused by level limit, complete the optimization management operation of nursing operation.

We provide the system. [Solution] A means of communication for receiving information on the health status of residents, An analytical means for analyzing the aforementioned health status information and extracting estimated diseases, A means for presenting management methods that proposes the optimal management method based on the analysis results, A monitoring system for collecting residents' biometric information and detecting abnormalities, A warning generation means that generates a notification when an anomaly is detected, A report generation means for generating an evaluation report including the aforementioned analysis results and management method, A system that includes this.

The invention provides a data center pipeline optimization management method and system, and belongs to the technical field of optimization management, and the method specifically comprises the steps: according to the coincidence condition of the distribution data of a harmonic monitoring abnormal time period and the data processing busy time period of a corresponding server, when it is determined that the optimization processing of a matched optical cable line does not need to be carried out, carrying out the optimization processing of the matched optical cable line; and determining an abnormal condition of a data processing result of the corresponding server in the harmonic monitoring abnormal time period based on the distribution data of the harmonic monitoring abnormal time period, and determining an interference risk server in the servers based on the abnormal condition, according to the method, the optimal management method of the matched optical cable line is determined according to the interference risk server data in different harmonic monitoring abnormal time periods and the data processing busy time periods of different interference risk servers, so that the operation reliability of the servers is improved, and the risk of electromagnetic interference is reduced.

The system according to the embodiment aims to simulate multiple scenarios and derive an optimal management pattern. [Solution] A system according to an embodiment includes a setting unit, a judgment unit, an evaluation unit, and a derivation unit. The setting unit sets a job title, personality, and judgment tendency. The judgment unit makes a management decision based on the job title, personality, and judgment tendency set by the setting unit. The evaluation unit evaluates the management decision made by the judgment unit. The derivation unit derives an optimal management pattern based on the evaluation results obtained by the evaluation unit.

The invention provides an ultrasonic amplitude-change pole optimization management method and system. The method comprises the following steps: receiving a performance target parameter set which is set when the system is initialized; dividing the amplitude-change pole into an input section, a middle transition section and an output section to construct a structure design model, and reversely optimizing the structure design model through a performance prediction module to generate a corresponding parameter set; sLM process parameters are collected, the parameter set is combined to be input into a pre-constructed error prediction module, and manufacturing error prediction is generated; real-time amplitude-change pole performance data are collected and combined, the manufacturing error prediction and the performance offset are combined, an individual final performance value is generated through Bayesian weighted fusion, and an individual performance label of each individual amplitude-change pole is constructed; the tissue electrical impedance, the cutter head temperature and the ultrasonic echo signal are collected in real time in the operation, the driving voltage of the transducer is dynamically adjusted by combining the individual performance label, and closed-loop control over the amplitude is carried out. According to the invention, a safer and more intelligent energy output scheme is provided for a high-complexity operation scene.

We provide the system. [Solution] A means including multiple artificial intelligences that collect data related to urban management and perform analyses on energy, transportation, and the environment based on said data, A means for conducting virtual meetings among multiple artificial intelligences, integrating urban management information, and generating an optimal management plan, A means for automatically executing urgent management instructions based on the generated management plan, A means of notifying the user of the results of the execution and enabling them to make further decisions, A system that includes this.

The invention relates to a construction management system and method for a complex construction scene, and relates to the technical field of construction management, and the system comprises a monitoring module which obtains the construction progress and construction monitoring information of the construction scene in real time, and a digital twinborn model recognition module which builds a three-dimensional digital twinborn model and determines the risk recognition result of equipment and personnel; the decision module determines a plurality of initial management strategies based on the risk identification result and a pre-constructed construction safety knowledge graph; and based on the construction progress, the construction plan, the environment information and a preset multi-objective optimization algorithm, optimizing the plurality of initial management strategies, determining an optimal management strategy, and sending the optimal management strategy to a corresponding management terminal in the optimal management strategy. The method has the effects of effectively identifying the construction risk, optimizing the management strategy, guaranteeing the construction safety and improving the construction efficiency.

This invention discloses an intelligent management system for distribution network diagram and model data, belonging to the field of distribution network diagram and model data management technology. It includes an application analysis module, an optimization analysis module, and an optimization management module. The application analysis module performs application analysis on the diagram and model data to determine optimization items, which are data items requiring optimization of diagram and model data transmission. The optimization analysis module performs optimization analysis on the optimization items, obtains diagram and model flow association data for each optimization item, generates a diagram and model flow information diagram for each optimization item based on the association data, identifies the transmission items present in each optimization item based on the flow information diagram, determines the baseline optimization method for each transmission item, determines the evaluation order of each transmission item based on the baseline optimization method, performs optimization analysis based on the evaluation order, and forms an optimization combination curve. The optimization management module manages the optimization items for each diagram and model.

The invention discloses a distributed power supply grid-connected optimization management system and a control method thereof, and belongs to the technical field of distributed power supply grid-connected management, and the control method comprises the steps: judging the operation state of distributed power supply equipment according to natural microenvironment data and operation state data in real time, and when the distributed power supply equipment is judged to be abnormal, executing the operation of the distributed power supply equipment; and issuing a control instruction of equipment shutdown to the distributed interface equipment in the region, predicting the output state of each region based on the operation state judgment result of the distributed power supply equipment in the region, and comprehensively considering the power market transaction and power selling market conditions. And the output state of the distributed power supply equipment in each region is coordinated and distributed based on the overall optimization target, so that the whole distributed power supply grid-connected optimization management system achieves optimal scheduling. According to the method, the comprehensive effect of multiple influence factors can be comprehensively considered, the operation state of the equipment can be accurately judged in a complex operation environment, and then the optimal management strategy is formulated according to different conditions.

This invention provides a distributed energy optimization management method and system for rapidly deploying mobile makeshift hospitals. In this embodiment, the invention dynamically adjusts energy allocation by constructing a multi-layered virtual energy network model for the mobile makeshift hospital; it uses time series forecasting technology to predict energy consumption demand and power generation potential, generating an energy supply and demand balance plan; it introduces a multi-objective optimization algorithm to intelligently schedule the charging and discharging process of the energy storage system, obtaining the optimal charging and discharging plan; it collects and analyzes the operating data of the distributed energy system at preset time nodes, uses a machine learning model to predict fault risks from the operating data, and optimizes the optimal energy allocation strategy and multi-objective optimization algorithm based on the results, forming an adaptive and self-learning energy closed-loop management system. The technical solution provided by this invention enables dynamic optimization management of energy in mobile makeshift hospitals, ensuring efficient, flexible, and adaptive energy allocation and scheduling, and improving the overall performance and reliability of the system.

The invention discloses a BIM-based building construction management method, and relates to the technical field of BIM, and the method comprises the steps: obtaining a BIM model of a target building, carrying out the key region extraction, and obtaining a plurality of key region integration levels; extracting BIM parameters of each key area, and performing construction error analysis to obtain a plurality of construction error parameters; sorting the key region set, and performing error conduction analysis to obtain a first conduction error parameter; according to the first conduction error parameter and the first key area integration level, management standard optimization of the first key area is carried out, a first optimal management standard is obtained, multiple optimal management standards of the multiple key areas are obtained through processing, and construction management is carried out. The problem that existing building construction management is lack of accuracy and high efficiency is solved.

We provide the system. [Solution] A means of analyzing past information and automatically generating the optimal document, A means of providing immediate solutions based on past cases of troubleshooting, A means to visualize the technology and knowledge within an organization and automatically identify the appropriate consultant, A means of improving operational efficiency in facility management by analyzing past management cases and proposing the optimal management strategy, A system that includes this.

The invention discloses an optimal management method for combined hydraulic reclamation construction of a ship group. The method comprises the following steps: acquiring resource configuration parameters of combined construction of multiple types of ships and sea condition grades in a planned construction period; constructing an objective function and a joint scheduling constraint expression for maximizing the hydraulic reclamation efficiency in unit time under the ideal sea condition; calculating the maximum theoretical construction efficiency and the construction management coefficient of the construction site; constructing an objective function for maximizing the construction efficiency under the adverse sea condition and a sea condition change combined constraint expression; determining the maximum expected construction efficiency and a construction management coefficient based on the estimated probability of occurrence of different levels of sea conditions; and pre-evaluating the construction scheme, and formulating and optimizing a dynamic adjustment strategy of the construction management coefficient. The invention provides the optimal management method for combined hydraulic reclamation construction of the ship group, so that the construction efficiency is greatly improved, the operation cost and time waste caused by improper management are reduced, and the high-efficiency, controllable and high-quality completion of a project on schedule is ensured.

The application discloses a fuzzy hierarchical simulation-optimization-evaluation method for optimal management measures of non-point source pollution. The method builds a double-level intelligent algorithm model containing environmental and economic targets and corresponding constraint conditions, and couples with a hydrological model to form a hierarchical simulation-optimization algorithm. In the optimization calculation, the fuzzy expected value and fuzzy reliability are used to handle uncertainty, and the hierarchical iteration linkage optimization of sub-basins and whole basins is executed to obtain the Pareto optimal solution of the optimal management measure space configuration scheme. Then, the scheme attribute value is extracted to build a fuzzy decision matrix, the weight is calculated by combining the fuzzy maximum deviation method, and the relative closeness of each scheme is calculated by the fuzzy TOPSIS, and the optimal configuration scheme is output. The application solves the problems of long time consumption of dynamic link formed by existing effect simulation and spatial optimization of optimal management measures, and the problems of insufficient uncertainty processing, and improves the efficiency and comprehensive benefits of scientific control of basin non-point source pollution.

The present invention belongs to the technical field of motor management, and discloses a motor control and management system; the present invention comprises: collecting historical motor comprehensive data, pre-processing the historical motor comprehensive data, and obtaining fused feature data; clustering and grouping the motors based on the fused feature data, and obtaining n motor groups; establishing a grid model of the motors, updating the states of the motors in each motor group according to the grid model, and simulating and obtaining the aging curve and failure rate of the corresponding motors within a preset time; determining the optimal management path for each motor group based on the aging curve and failure rate of the motors within the preset time using a path planning algorithm, and executing the optimal management path to perform patrol management on the motors in each motor group; the optimal management path can be planned, so that management resources are reasonably allocated and utilized, ensuring timely maintenance, thereby extending the service life of the motors and reducing operation and maintenance costs.

The invention relates to the technical field of medical cosmetology, in particular to an optimal management system and method for facial anti-aging. The method comprises the following steps: acquiring a facial three-dimensional model and a dynamic expression video, extracting a strain field and identifying high and low dynamic strain areas; after the face finite element mechanical model is established, an initial filling scheme is generated through topological optimization with the maximum supporting rigidity and the limitation of the total amount of materials as constraints; implanting the scheme into the model, performing dynamic mechanical simulation, and iteratively correcting the mechanical constraint according to a simulation result until the dynamic state is natural; and finally, receiving an adjustment instruction through a human-computer interaction interface, converting the adjustment instruction into an optimization parameter, and guiding to generate a final injection plan. According to the technical scheme, collaborative optimization and fixed-point and fixed-position layered design of the skin phase, the meat phase and the bone phase are achieved, the problems that the face is loose, vertical, fat and concave are comprehensively solved, the treatment has the three-dimensional supporting effect and the dynamic natural effect, the minimally invasive biotechnology concept is met, treatment without the recovery period can be achieved, the effects of wrinkle removing, aging resisting, tightening and lifting are finally achieved, and a user is assisted to achieve the young face state.

This application proposes a method, system, device, and medium for processing energy optimization management models, relating to the field of power system automation technology. The method includes: obtaining an initial energy optimization management model of a microgrid cluster; determining dual variables based on decision variables, with the dual variables used for transmission between sub-microgrids; performing distributed processing on the initial energy optimization management model based on the dual variables to obtain a distributed energy optimization management model; obtaining consistency constraints during the iterative calculation process; obtaining data communication volume between sub-microgrids; applying communication constraints to the dual variables based on the data communication volume to obtain communication conditions for the dual variables; and iteratively calculating the distributed energy optimization management model based on the consistency constraints and the communication conditions for the dual variables to obtain a target optimization management strategy. This application can solve the energy optimization management model of a microgrid cluster and reduce the external communication of internal characteristic information of sub-microgrids.

The application discloses a kind of hospital multidimensional value drive integral performance management methods, comprising the following steps: constructing multidimensional value index system including labor value, technical value, disease value, economic value, management value and social value;According to hospital strategic goal and DRG / DIP payment policy requirement, dynamically allocate the weight of each dimension through analytic hierarchy process;Through hospital information system, outpatient visits, operation volume, disease risk grade, medical cost, patient satisfaction data are automatically collected, and classified mapping to corresponding value dimension.The hospital multidimensional value drive integral performance management method of the application is in line with hospital strategy and enhances the adaptability to DRG / DIP policy, optimizes management system;For medical staff, construct multiple incentive system and individualized career development guidance, improve work enthusiasm and professional accomplishment.

The invention provides a bridge bearing capacity monitoring method and system based on digital twinning, and the method comprises the steps: constructing a digital twinning finite element model, and identifying the parameters of a time-varying material constitutive model; continuously updating the model to obtain a synchronous twin model; calculating a theoretical load effect on a vehicle prediction path, and identifying a temporary load condition data packet; outputting a virtual future load scene by using a multi-level probability model and an extreme value generator; injecting the temporary load condition data packet and the virtual future load scene into a synchronous twin model to obtain structural response statistical distribution; and calculating a safety evaluation index, and performing decision optimization by utilizing reinforcement learning to obtain an optimal management and maintenance intervention scheme. According to the method, the digital model and the physical entity can be synchronously evolved in real time, the probabilistic risk of the structure under the future random load can be predicted and evaluated, intelligent decision support is provided, and dynamic, online and predictive evaluation of the bridge bearing capacity is achieved.

The invention provides an optimal management method and system based on network resource scheduling. The resource reservation method comprises the following steps: firstly, determining a target resource reservation strategy according to historical service data of user equipment; secondly, analyzing to obtain a slice migration rule according to the network slice information; the slice migration rule and the resource reservation strategy of the corresponding service type are associated and integrated to form a joint scheduling strategy; when a new service request of the user equipment is received, performing adaptive correction on the initial resource reservation parameter based on the corresponding service attribute information and the reflected slice migration state to obtain a target resource reservation parameter; and finally, according to the target resource reservation parameter, executing resource allocation and service migration for the new service request on the target network slice. According to the technical scheme provided by the invention, the dynamic resource scheduling is carried out by fusing the historical service characteristics and the user mobility rule, so that the service continuity and the service quality are effectively guaranteed while the network resource utilization rate is improved.

The invention discloses a medication data supervision and evaluation system based on artificial intelligence, and belongs to the technical field of medication data supervision. The method and the device are used for solving the technical problems of poor active supervision reliability and poor active optimization iteration effect of drug administration data supervision evaluation in an existing scheme. Credible label values in the standardized matrix can provide clear input for subsequent risk assessment; through weighted integration of multi-dimensional factors of dosage, solvent and pathology, quantitative processing of medication risks is realized, a matching degree algorithm based on historical optimal prescriptions and real-time guide update enables a system to dynamically adapt to clinical changes, and through construction of a three-dimensional evaluation tensor, complex data can be converted into visual scores, so that the accuracy of evaluation is improved. Unnecessary intervention of low-risk prescriptions is reduced; the credible label value, the medication risk index and the rule adaptation degree are subjected to conjoint analysis and judgment, and a hierarchical optimization mechanism is dynamically triggered according to a judgment result, so that active optimization management on implementation of an existing supervision and evaluation scheme is realized.

This invention discloses an intelligent decision support system based on big data, belonging to the field of decision support system technology. Based on historical planting scenarios, it generates limiting factors and uses a random generation tool to generate several parameter spaces according to a preset number of spaces. The loss value of each parameter space is calculated using an information function. The loss values ​​of all parameter spaces are then substituted into a dynamic filtering algorithm. After filtering out some parameter spaces, the remaining parameter spaces undergo content randomization. A space set is established for all randomized parameter spaces, outputting multiple space sets. The loss values ​​of these multiple space sets are compared, and the parameter space with the lowest loss value is selected as the management solution for the enterprise's current planting scenario. This support system, through dynamic solution generation and filtering, can globally select the optimal management solution to adapt to the enterprise's current planting scenario, exhibiting strong adaptability and improving decision-making efficiency.

The invention relates to the technical field of management, in particular to an optimal management method for performance indexes. Obtaining a target performance index of the target employee based on the business level index, the customer reputation index and the economic benefit index, and comparing the target performance index with the actual performance index to obtain the performance completion degree of the target employee; according to the performance completion degree of the target employee, when the target completion degree is lower than a preset completion degree threshold value, starting a management program; obtaining the character type of the target employee, and calling a management strategy recommendation device based on the character type of the target employee, the target performance index, the actual performance index and the performance completion degree to obtain a recommendation management strategy; and managing the target employee according to the recommended management strategy, evaluating the management effect to obtain a management effect evaluation index, feeding back the management effect to the management strategy recommendation device, and performing iterative optimization on the management strategy recommendation device. According to the invention, an effect of dynamic, accurate and personalized management of employee performance can be realized.

This invention proposes an optimization management method and system for ultrasonic amplitude transformers. The method includes: receiving a set of performance target parameters set during system initialization; dividing the amplitude transformer into an input segment, an intermediate transition segment, and an output segment to construct a structural design model, and then optimizing the structural design model inversely through a performance prediction module to generate a corresponding parameter set; collecting SLM process parameters, and inputting the parameter set into a pre-constructed error prediction module to generate a manufacturing error prediction; collecting and combining real-time amplitude transformer performance data with the manufacturing error prediction and performance offset, and generating an individual final performance value through Bayesian weighted fusion, and constructing an individual performance label for each individual amplitude transformer; and collecting tissue impedance, probe temperature, and ultrasonic echo signals in real-time during surgery, and dynamically adjusting the transducer drive voltage based on the individual performance label to perform closed-loop amplitude control. This invention provides a safer and more intelligent energy output solution for highly complex surgical scenarios.

The invention discloses an AI-based intelligent supply chain optimization management method and system, and relates to the technical field of supply chain optimization management, and the method comprises the following steps: 1, building a data collection model, carrying out the collection of data, and carrying out the all-around processing of the data after the collection, and 2, formulating a transportation scheme, carrying out the design of a transportation mode in advance, and carrying out the optimization of the transportation mode. The method comprises the following steps: step 1, formulating a demand scheme, formulating an inventory management model, and managing inventory positions in a transportation process, and step 2, formulating a scheme optimization and adjustment model to optimize a supply chain, and formulating a bidirectional problem collection scheme in an implementation process to collect problems generated during implementation of the demand scheme and the scheme optimization and adjustment model. According to the method, in the process of optimizing the supply chain, the demand is predicted, the demand scheme is formulated after prediction is completed, stage processing is carried out in the formulating process, and the most real demand can be accurately predicted.