27 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 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 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.

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 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 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.

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.

The present invention relates to a system and method capable of counting, classifying, and evaluating repeated biomechanical activities in real time. The basic configuration of the system consists of one or more devices, wearable and / or embedded, each consisting of a microcontroller, an IMU, and an LED, capable of processing inertial data, providing feedback on counting, and sending it to the computing node that classifies and evaluates motion through machine learning algorithms and data fusion techniques. The cloud service enables optimal management of training datasets and user profile information. The graphical user interface allows the user to interact with the system by accessing evaluation histories and customizing it based on their own goals. The method ology presented involves a central use of mathematical modelling, ensuring specialized biomechanical assessments and the construction of robust training datasets. This invention finds further application as monitoring aimed at controlling robotic limbs.

The invention provides a programming practical training intelligent feedback system based on a large model and an optimization management method, and belongs to the technical field of optimization management, and the method specifically comprises the steps: according to the association condition of a programming practical training instance and an identification risk defect type, combining the distribution data of the identification risk defect type in different students, and obtaining an identification result of the identification risk defect type; according to the method, the push processing scheme of the programming practical training instance is determined, the practical training course is pushed based on the push processing scheme, and the feedback management method of the model is determined by using the change data of the code defect portrait of the student, so that the recognition processing efficiency of the large model when the code defect type has the recognition defect is improved.

This invention discloses a method for optimizing and managing airside cargo flow at air ports based on RFID and big data, belonging to the field of air logistics information technology. The method includes the following steps: collecting reading records of the same RFID tag within a continuous time window in the apron area; sorting the reading records according to a unified time scale to construct a reading time sequence; and marking densely read segments that appear consecutively within a preset time span and whose reading frequency meets a preset density condition within the reading time sequence. This invention constructs a reading time sequence and performs time difference compression analysis and displacement process calculation. Combined with the time range required for normal apron movement, it constrains and corrects abnormal jump behaviors to avoid misjudging real displacement as multiple jumps. Simultaneously, by associating electromagnetic fluctuation records and dynamically adjusting the judgment window, it achieves rhythm rearrangement during interference and post-incident recovery, ensuring continuous and stable cargo flow.

The invention provides a drainage resource management method and system based on machine learning, and relates to the technical field of drainage resource management. The method comprises the following steps: collecting multi-source heterogeneous data; constructing a multi-source heterogeneous data fusion knowledge base; constructing a drainage resource comprehensive prediction model through a machine learning algorithm; inputting multi-source heterogeneous data in the operation process at the current moment in a multi-source heterogeneous data fusion knowledge base into the drainage resource comprehensive prediction model, and obtaining a predicted value at the current moment; judging whether the flow of each pump station at the current moment needs to be optimized or not; if the flow of each pump station needs to be optimized, obtaining water volume data stored in a pipe network; determining the optimized flow of each pump station according to the drainage resource comprehensive prediction model and the pipe network storage water volume data; and outputting the optimal management instruction. According to the method and the system, the pump station flow can be optimized according to the conditions of energy consumption, maintenance cost and emission standard-reaching rate, the long-term operation and maintenance cost of the system is reduced, and the management intelligence level is improved.

The invention belongs to the technical field of livestock breeding management, and discloses a livestock breeding management system and management method based on a machine learning algorithm, and the management method comprises the steps: S1, constructing and training an output value prediction model based on the machine learning algorithm; s2, collecting target current air environment data of the target livestock farm; s3, obtaining target attribute features of the target livestock farm; s4, taking the target current air environment data and the target attribute features as input of the output value prediction model, identifying a target feature extraction strategy according to the target attribute features, extracting target features from the target current air environment data according to the target feature extraction strategy, and outputting the target features to the output value prediction model. Predicting a target predicted output value of the target livestock farm based on the target characteristics; and S5, screening and outputting an optimal management strategy which can be applied to the target livestock farm according to the target predicted output value.

A system is provided.SOLUTION: A system for supporting an operation of a Neighborhood Association, comprising: means for collecting operation information provided from the Neighborhood Association using a generation and AI engine and accumulating the operation information in a database; means for generating an optimal operation proposal based on the operation information accumulated in the database; and means for notifying members of the Neighborhood Association of the generated operation proposal.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to optimally manage the user's financial assets and provide advice on savings and investments. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a provision unit, and an operation unit. The collection unit collects the user's financial asset data. The analysis unit analyzes the data collected by the collection unit and classifies and analyzes the user's spending. The provision unit provides savings and investment advice based on the analysis results obtained by the analysis unit. The operation unit automatically manages assets based on the advice provided by the provision unit.

The invention discloses a sports equipment maintenance period optimization method based on big data analysis. The method comprises the following steps: S1, collecting and processing sports equipment use data, environment data and maintenance record data; s2, dividing the data according to factor categories; s3, constructing a multi-branch echo state network, wherein the multi-branch echo state network comprises a use intensity dynamic pool branch, an environment factor dynamic pool branch and a maintenance record dynamic pool branch; s4, the state fusion module generates a global dynamic state vector; s5, the output layer generates a sports equipment maintenance period prediction result and a corresponding risk scoring result; s6, calculating a prediction error, and when prediction error information exceeds a preset threshold value, updating a post-maintenance period prediction result and a risk scoring result; and S7, generating a sports equipment dynamic maintenance plan and outputting the sports equipment dynamic maintenance plan to an operation and maintenance scheduling system. According to the method, the multi-branch echo state network is adopted, and optimal management of sports equipment maintenance period prediction and dynamic maintenance plan generation is realized.