9 results about "Business objectives" patented technology

This invention provides a control method and apparatus based on a lean manufacturing system, comprising: calculating the operational maturity value of a target lean manufacturing system to identify problems to be improved; constructing manufacturing strategic goals by comparing the target factory with business objectives based on pre-built quantitative indicators; streamlining the organizational structure based on pre-built lean processes, lean organizational structure, and lean departmental functions and responsibilities; constructing a multi-level key performance indicator system and a facilitating management meeting mechanism; and finally, constructing an implementation plan and controlling the target factory according to the implementation plan to achieve the optimization goals. This invention solves the problems of high deployment costs and poor application effects in existing technologies.

This invention discloses a multi-cluster data processing method and system based on a large-scale language model. The method collects multi-dimensional telemetry data from managed clusters; inputs the multi-dimensional telemetry data, business objectives, and dynamically generated prompts into a large-scale language model to obtain structured decisions; translates the structured decisions into configuration instructions for the target platform and executes the configuration instructions. This invention achieves global intelligent optimization and accurately proposes failover decisions, thereby improving data processing efficiency.

The invention discloses an AI native intelligent central operating system based on reinforcement learning, and relates to the technical field of reinforcement learning, and the AI native intelligent central operating system comprises the steps: determining a corresponding regulation action based on a preset business target and state representation; according to the invention, the plurality of sub-regulation items are determined based on the recognition of the regulation action, and the quantitative execution is carried out along each sub-regulation item, so that the change information of the regulated key performance indicator is predicted, and the accuracy of the change information of the regulated key performance indicator is improved. Determining a corresponding reward value according to the identification of the change information of the key performance indicator; determining to-be-optimized content according to reinforcement learning of the reward value; according to the method, each optimized sub-regulation item is determined according to the matching of the to-be-optimized content and each sub-regulation item, and the final operation content of the security industry AI native intelligent center is constructed in combination with the action constraint relationship of the security database, so that the accuracy of the final operation content of the security industry AI native intelligent center is improved.

This application discloses a self-organizing evolution method and system for knowledge graphs based on causal attribution, relating to the field of artificial intelligence technology, aiming to solve the problems of insufficient creativity in dialogue systems and the degradation of knowledge graph structures. The method includes: selecting high-level intents from a causal strategy knowledge graph in response to a dialogue state; extracting subgraphs or paths as semantic constraints and causal utility guides; generating response dialogue using the constraints and guides; performing causal attribution analysis on the dialogue trajectory containing the dialogue to determine the causal contribution of the dialogue to business objectives; and performing a self-organizing rewriting operation on the knowledge graph based on the causal contribution. The system is used to implement this method. This application, by constructing an intelligent closed loop, enables the knowledge graph to self-purify and iterate, realizing a transformation from "limited selection" to "autonomous generation" and from "incremental growth" to "self-organizing evolution," thereby improving the long-term performance of the system.

This invention relates to the field of big data analytics and intelligent decision-making technology, and discloses a multi-dimensional data collaboration method and system for operational data analysis. The method includes: real-time access and fusion of multi-source heterogeneous operational data to generate a standardized operational entity event sequence; construction and continuous updating of a dynamic causal network representing the causal relationships between business entities based on this sequence and a time-series causal discovery algorithm; real-time identification of abnormal patterns in the network; construction of virtual intervention strategies based on the abnormal patterns and business objectives; and multi-scenario simulation and deduction using the dynamic causal network to generate a strategy deduction and analysis report including a comparison of expected impact values. This invention, by constructing a dynamic causal network and conducting simulation and deduction based on it, solves the fundamental technical defects of traditional operational data analysis, such as data silos, weak correlation, disconnect between prediction and decision-making, and static and one-sided analysis results, achieving end-to-end collaborative analysis from multi-dimensional data fusion to intelligent and forward-looking decision support.

This invention discloses an enterprise multi-business interconnection system for data processing, relating to the field of enterprise business process optimization technology. It includes a value stream definition module, a process analysis module, a requirement backpropagation module, a business interconnection module, a value stream processing module, and a value verification module. Based on enterprise business objectives, this invention determines the end-to-end business value stream and decomposes processes to identify business nodes, states, and collaborative relationships. Then, based on optimization objectives, it deduces the minimum necessary data interconnection scope. Subsequently, it implements data interaction between heterogeneous businesses according to this scope and integrates and processes multi-source data to construct a business interaction view, generating operational performance indicators. Finally, the value verification module quantifies and displays the optimization effect. This invention achieves value-driven interconnection and optimization, effectively improving the targeting and measurability of cross-system business operations.

This invention discloses a method and system for optimizing labor organization based on an AI intelligent agent hub, comprising: constructing a labor resource mobilization library; obtaining project business objectives, logically decomposing the project business objectives based on a semantic parsing model to obtain a set of project sub-tasks, and performing digitizable evaluation on each sub-task in the project sub-task set to obtain a digitizable score; performing scheduling and matching based on the labor resource mobilization library, the project sub-task set, and the digitizable score to obtain the optimal labor force grouping; generating hybrid virtual work teams based on the optimal labor force grouping, and issuing work instructions to execute work based on the hybrid virtual work teams. Compared with existing technologies, this invention can significantly improve the overall coordination efficiency of heterogeneous labor, the accuracy of task adaptation, and the smoothness of human-machine collaboration, overcoming the technical shortcomings of fragmented resource profiles, lack of digitizable task evaluation, and low grouping matching accuracy.

The embodiment of the specification provides a method and device for displaying the correlation between a business target and business indicators. The method comprises: obtaining a target value sequence of the business target at each time point in a first time period and a plurality of indicator value sequences of the plurality of business indicators in the first time period; for each business indicator, performing correlation calculation on the target value sequence and the corresponding indicator value sequence of the business indicator to obtain a coefficient sequence composed of correlation coefficients between the business indicator and the business target at each time point; establishing a three-dimensional coordinate system, in which three axes represent time, target value and correlation coefficient respectively; displaying a target curve corresponding to the target value sequence and a graphical element corresponding to the coefficient sequence in the three-dimensional coordinate system; and the graphical element is used to determine a first cause indicator most relevant to the business target among the plurality of business indicators. The user can accurately, clearly, effectively and intuitively see the first cause indicator affecting the business target.