14 results about "Management indicators" patented technology

The application provides a smart question and index management engine and system based on dynamic reward optimization, relates to the technical field of data learning, and is used for enterprise index analysis, attribution diagnosis and decision support. The system sets an index management layer to uniformly manage index caliber, calculation logic, blood relationship, credibility score and version information by means of a dynamic knowledge graph, uniformly implements semantic constraints on a multi-agent analysis process, and guarantees index consistency and traceability. The system also establishes a cause-effect cognition module, generates and corrects a business index cause-effect directed acyclic graph based on time series data and in combination with expert priori, realizes root cause positioning and counterfactual simulation, and answers "why change" and "what if intervention". A multi-agent collaborative analysis core is responsible for natural language intention analysis, index compliance verification, automatic data acquisition, cause-effect inference, narrative generation and chart presentation, and calculates a multi-target compound reward value based on user feedback and interaction behavior, and adaptively adjusts output; user correction write-back forms a closed-loop learning.

The invention discloses a medicine supply analysis management system and method based on big data, and relates to the technical field of data processing, historical data is acquired and decomposed into basic data units, a first analysis rule and a second analysis rule are configured for each basic data unit and management indexes respectively, a corresponding rule base is generated, and the corresponding rule base is stored; storing the corresponding rule libraries into corresponding rule spaces respectively, decomposing to-be-analyzed medicine supply data into data elements, matching the data elements with the basic data unit to obtain a first analysis rule, inputting parameters for the data elements, generating a third analysis rule and a fourth analysis rule, and storing the third analysis rule and the fourth analysis rule in the corresponding rule spaces; to-be-analyzed data and the corresponding third analysis rule and fourth analysis rule are stored in an analysis execution space, supply trend prediction and supply strategy suggestions are generated, through data unit decomposition, multivariate rule configuration and dynamic scene rule generation, the defects of a traditional method are overcome, refined analysis and scientific management of data are achieved, and the supply trend prediction and supply strategy suggestions are obtained. And the medicine supply chain management efficiency is improved.

The invention provides a financial data multi-dimensional processing method, device and equipment based on artificial intelligence, and relates to multiple technical fields of artificial intelligence, data science and financial engineering. The method comprises the following steps: acquiring financial data; performing three-level index stratified analysis processing on the financial data according to a preset stratified analysis mode to generate first data under a first-level decision index, second data under a second-level management index and third data under a third-level execution index; wherein the first data is macroscopic financial core index monitoring analysis data under a preset first authority, the second data is analysis monitoring data under a preset second authority, and the third data is monitoring analysis data under a preset third authority. And performing vectorization processing on the first data, the second data and the third data according to a preset intelligent question-answering system and a double-encoder model, and generating and outputting financial report information. Therefore, the technical problem that the processing accuracy of the financial data is poor is solved.

The invention relates to the technical field of big data and data visualization, and discloses a cognitive decision-making system fusing BI and AI capabilities, and the system comprises a data access and management module which accesses multi-modal data, carries out the preprocessing of the multi-modal data, and further carries out the full-life-cycle management; the index interaction and analysis module is used for performing index caliber unification processing on the data to obtain standardized index data; a data interaction panel is constructed, and an analysis result is visually displayed; the decision deduction module is used for performing cognitive calculation and dynamic deduction on the standardized index data and generating and outputting decision suggestions; executing a decision behavior to obtain actual effect data, and feeding back the actual effect data to a cognitive calculation process to realize continuous optimization of the module; and the authority workbench module is used for configuring a personalized Web interface according to role authority and integrating multiple functions so as to realize differentiated data access and operation.

The invention provides a property management index visualization method and device, equipment and a medium. The method comprises the steps that a target external system, display demand information and index demand information are determined on an index management interface; identifying a target style template from the display demand information through an NLP model; traversing codes of the target external system through the target API to determine a plurality of candidate index modules; determining a plurality of target index modules and target index data based on the candidate index modules and an NLP model; and constructing a target chart based on the multiple pieces of target index data and the target style template, and displaying the target chart in the visual area. According to the technical scheme provided by the embodiment of the invention, the target style template can be flexibly determined according to the display demand information, and the target index data can be obtained by traversing the code of the target external system according to the index demand information, so that the template of the target chart and the self-definition of the data source are realized, and the flexibility and the management efficiency of index monitoring are improved.

The present application provides an indicator system construction method, device, electronic device and storage medium. By obtaining multiple preset meta-indicators and cloud indicator identifiers of each preset meta-indicator, at least two preset meta-indicators are processed to obtain at least one derivative indicator, and a derivative indicator identifier is set for each derivative indicator, the indicator identifier to be managed and the indicator management content are obtained, the indicator to be managed is determined according to the indicator identifier to be managed, the cloud indicator identifier and the derivative indicator identifier, the indicator to be managed is deleted or modified, and each indicator to be labeled in the indicator set to be labeled is labeled with a smart car cloud application business label, and an indicator system for smart car cloud application business is constructed based on the smart car cloud application business label of each indicator to be labeled. A method for modifying and managing indicators is provided, and then an indicator system is generated according to at least a part of the indicators after management. The adjustment of the indicator system is more flexible and can meet the needs of business development.

To enable even a non-expert to easily grasp index values ​​relating to management. [Solution] The financial analysis system 100 includes an acquisition unit 3 that acquires financial information of multiple business entities, a processing unit 4 that adds up the financial information of the multiple business entities acquired by the acquisition unit 3, and an output unit 5 that outputs the result of the addition by the processing unit 4.

The invention provides a task optimization management method and system based on artificial intelligence, and relates to the technical field of task management, and the method comprises the steps: determining a plan start moment, a plan end moment, execution condition information and execution result information of a sub-task, determining a task graph structure, generating task execution information after a target task starts, and storing the task execution information in the task graph structure; and when the task execution cycle is finished, acquiring actual task execution condition information, and updating the task graph structure. And after the target task is completed, determining a target task performance management index. According to the method and the device, the task graph structure can be automatically obtained based on the Gantt chart of the target task, so that the optimal flow of task execution is obtained, the task execution efficiency is improved, the task execution information can be automatically generated, a clear task execution target can be formulated, and the execution efficiency is favorably improved. The task execution efficiency can be improved through continuous adjustment and optimization, and the target task performance management index can be determined, so that the task execution is effectively supervised.

The invention discloses an electronic product manufacturing workshop index system management system, a construction method, a device and a product, relates to the field of production and manufacturing management, and is used for improving the fusion degree of an index system and an electronic product manufacturing service from macroscopic to microscopic. The method comprises the steps that at least one main dimension of an index system is constructed, at least one sub-dimension is constructed under each main dimension, components of each sub-dimension are constructed, cross combination is carried out on the components of each sub-dimension under each main dimension for each main dimension, a management node set is constructed, and the management node set is used for managing the index system. And respectively constructing a management index for each main dimension and each management node. According to the method, the comprehensive fusion of the index system and the production business and the comprehensive coverage of the production business from macroscopic to microscopic are ensured, and the development speed of the index system of the industry is obviously improved.

To provide a system for quickly and accurately supporting the decision of a management index and the formulation of a financial strategy.SOLUTION: A system includes a conversation reception part, an index determination support part, and a financial strategy proposal part. The conversation reception unit receives a question of a president. The index determination support unit proposes a management index based on the question received by the conversation reception unit. The financial strategy proposal unit proposes a financial strategy for maximizing the management index proposed by the index determination support unit.SELECTED DRAWING: Figure 1

The invention discloses a die-casting machine output performance index evaluation method and system based on edge calculation, and relates to the technical field of industrial production management, and the method comprises the steps: obtaining monitoring data and electric energy data of a die-casting machine, and carrying out the evaluation of the output performance index of the die-casting machine according to a time sequence from front to back based on a cold die pressure change threshold value; and pressure value data in the monitoring data of the die casting machine are analyzed, and injection cycle data are obtained. The pressure data in the working process of the die-casting machine are monitored in real time, the key parameters describing the die-casting production process and the equipment performance are accurately calculated, the pressure threshold value of the injection period is set through historical data of the die-casting machine, accurate recognition of the injection period is ensured, different production process requirements can be met, and the production efficiency is improved. The key management data and the management indexes are accurately calculated through few data (such as the pressure value and the electric energy data of the die-casting equipment), the output evaluation efficiency of the die-casting machine is improved, and the production and management level of a factory is further improved.

This invention proposes a method, device, equipment, and medium for visualizing property management indicators. The method includes: identifying a target external system, displaying requirement information, and indicator requirement information on an indicator management interface; identifying a target style template from the displayed requirement information using an NLP model; determining multiple candidate indicator modules by traversing the code of the target external system through the target API; determining multiple target indicator modules and target indicator data based on the candidate indicator modules and the NLP model; constructing a target chart based on the multiple target indicator data and the target style template; and displaying the target chart in a visualization area. According to the technical solution of this invention, the target style template can be flexibly determined based on the display requirement information, and the target indicator data can be obtained by traversing the code of the target external system based on the indicator requirement information, enabling customization of the target chart template and data source, thus improving the flexibility and management efficiency of indicator monitoring.

The invention relates to the technical field of artificial intelligence, in particular to an automatic test management method and device, equipment and a medium. The method is applied to the field of finance, determines real-time test coefficients of testers, dynamically allocates test sub-tasks to corresponding testers according to the real-time test coefficients and task complexity, and flexibly matches test sub-task requirements and tester capabilities in real time, so as to balance the workload among the testers and improve the test efficiency. And the efficiency, quality and cooperation level of the test team can be obviously improved. And determining a demand document of each sub-task, and performing text analysis on the demand document to generate a corresponding test case. By performing text analysis on the demand document and generating the corresponding test case, the team can be helped to more efficiently understand the demand, the communication cost is reduced, and the project delivery quality is improved. Based on the test case, the management index is detected, the detection result is obtained, intelligent detection is carried out, the detection accuracy can be improved, and therefore the quality of automatic testing is improved.

This application discloses a management method and system for improving the accuracy of pig farm production data. The method includes: acquiring sow production records; constructing individual digital twin objects of sows based on standard events; and establishing state transition rules corresponding to the sow's production stages; aggregating standard events according to standard sow identifiers; generating a candidate event set and a candidate event chain diagram based on the state transition rules; performing path solving on the candidate event chain diagram to obtain the sow's main event chain; identifying state gaps between adjacent events based on the sow's main event chain and generating corresponding inferred events; updating the individual digital twin objects of sows based on the sow's main event chain and inferred events; and outputting the corrected business timeline and management indicator calculation results based on the updated individual digital twin objects of sows. This invention is applicable to the consistent processing of multi-source production data in sow farms.