19 results about "Demand driven" patented technology

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a demand-driven data processing method, device and equipment and a medium, and the method comprises the steps: obtaining demand information, and generating a structured demand analysis report through a demand analysis agent; generating an executable code by combining a strategy conversion agent with a zero code operation platform; generating a test case through the automatic test agent and executing an automatic test; when the test result is wrong, adjustment is carried out through the result feedback agent; when the test result is passed, executing the executable code to generate a processing result, and verifying the intelligent experience certificate by the accuracy; and storing the verified processing result, and performing multi-level data analysis through the data analysis agent to obtain an analysis result. By establishing a closed loop of demand analysis, rule conversion, test verification and data analysis, rapid conversion and accurate verification from the demand to the result are realized, the processing efficiency is improved, and the error risk is reduced.

The invention belongs to the technical field of intelligent manufacturing, and discloses a demand-driven material demand planning system based on deep reinforcement learning and an optimization method. The system comprises a demand module which is used for collecting, processing and outputting related demands and supplier environment data; the demand-driven material demand planning module is used for generating an inventory replenishment plan, a production plan and a material purchasing plan; the simulation module is used for constructing and operating a simulation model so as to output a simulation experiment statistical result; the deep reinforcement learning module interacts with the demand-driven material demand planning module and the simulation module, carries out training by utilizing a built-in algorithm library, and outputs an optimization parameter set of a demand-driven material demand plan; and the execution module is used for converting the plan information into an operation instruction and feeding back actual operation data and an execution result so as to make up for the deficiency of static parameter configuration of the traditional demand-driven material demand plan, realize collaborative optimization of inventory level and service rate and enhance the response capability of an enterprise to market demand change.

The invention discloses a resource optimization method and system based on demand driving, belongs to the technical field of software product development, and aims to solve the technical problems that resource allocation in software product life cycle management depends on artificial experience, is low in efficiency, subjective in allocation standard and difficult to dynamically adapt to project changes. Comprising the following steps: acquiring demand characteristics, and endowing the demand characteristics with weights; the method comprises the following steps: modeling available resources of a project to form a resource constraint model, defining attributes and constraint conditions of the resources through the resource constraint model, and collecting state information of the resources in real time; on the basis of the weights of the demand features, the state information of the resources and the attributes and constraint conditions of the resources, the resources are allocated through a multi-objective optimization algorithm, and an optimal resource allocation scheme is formed; issuing the resource allocation scheme to an execution end through tool chain integration; and optimizing the weight of the demand feature and the optimal resource allocation scheme based on a machine learning method.

The application discloses a demand-driven visual language model rule generation method and device, which comprises the following steps: receiving a natural language demand of a user, analyzing the natural language demand into a structured constraint template, converting the structured constraint template into an executable rule and binding a rollback point; executing the executable rule on a current sample and a same batch sample based on a visual language model, outputting a tabular report and a corresponding evidence package; rejudging suspicious samples in the tabular report, judging whether false positives or false negatives occur, updating the rule according to a rejudging result, and recording a version change log. The scheme significantly improves the accuracy and flexibility of rule generation.

An apparatus for implementing soft duplex operation of a communications network that transmits downstream signals from a service provider to a subscriber and upstream signals from the subscriber to the service provider. The apparatus may include a pair of opposed triplexers defining a first signal path through a first amplifier and a second signal path through a second amplifier. The apparatus may also include at least one switch that selectively alternates a mid0band signal between an upstream signal and a downstream signal.

The invention discloses a demand-driven reusable binary pointer analysis method, which is used for determining a pointing set and an alias of a given target pointer variable, and comprises the following steps of: S1, recovering a pointer type in a process through a use mode of the variable, and extracting an instruction related to pointer calculation; s2, on the basis of the pointer representation and an execution result of the modeling instruction, abstract interpretation is carried out in the process, a pointer representation set of all pointer variables is obtained, and the result is stored in an intermediate result library; s3, on the basis of an analysis result in the process, determining a to-be-analyzed function as required, and obtaining different pointer representations of the target pointer variable in different functions; and if a certain function is not analyzed, the in-process analysis of the step S1 and the step S2 is triggered for the function. According to the method, a context sensitive strategy and a flow sensitive strategy are realized, the balance of analysis efficiency and precision is realized, and inter-process on-demand pointer analysis can be efficiently carried out.

Systems and methods are directed toward managing demand, such as for manufacturing in complex supply and / or demand driven environments, including aerospace-industry products and systems, environments with a multitude of stakeholders, and other sophisticated organizations. A production request may be provided with a component identifier for a top-level module component to be produced. Data associated with the component identifier may be determined. The data may include one or more additional component identifiers for sub-components which are to be consumed to produce the top-level module component. Supply allocations for the top-level module component and the sub-components may be generated based at least in part on the data. One or more action signals may be provided to fulfill the production request for the top-level module component according to the supply allocations.

The invention relates to a key precise binding distribution method based on a demand-driven strategy, and belongs to the technical field of safety communication of a satellite communication system ground station access network. In order to solve the problems that a current satellite communication system ground access network generally adopts a standard VPX board card and cannot independently integrate a secrecy module for each channel board card, and key interaction between a group cipher machine and numerous baseband board cards is inconvenient, a precise binding and distribution model from a key to the baseband board card is constructed, and a demand driving strategy is adopted, so that a group cipher machine and the baseband board cards are accurately bound and distributed. And high-efficiency and safe distribution of the secret key is realized. The method comprises the steps of baseband board card registration and authentication, key demand request, key generation and distribution, key storage and update and the like, effectively solves the problems of complex key management and inconvenient interaction in the prior art, improves the security and reliability of the system, and is suitable for a multi-beam and multi-board card satellite communication system ground station access network environment.

This invention discloses a government service analysis and management system, belonging to the field of government service management technology. The system includes a user profile construction module, a demand prediction and proactive service module, a data control and permission adaptation module, a process monitoring and root cause tracing module, a policy compliance supervision module, an inclusive service adaptation module, and a central dispatch module. This system improves upon the limitations of existing government service systems' passive service architecture, which is centered on pre-set items, by constructing a user lifecycle profile and a causal inference logic chain for government service needs. It can accurately uncover the inherent causal relationship between user characteristics and government service items, effectively eliminating the interference of pseudo-correlation features on demand prediction, achieving accurate prediction and compliance verification of users' potential service needs. This realizes the transformation of government services from an item-driven "people looking for services" to a demand-driven "services finding people" model, reducing the time and communication costs for the public from the source and improving the government service experience.

The invention provides an inventory control method, an inventory control device, electronic equipment and a storage medium, and belongs to the technical field of inventory management. A decision tree is constructed according to historical demand driving characteristics and historical spare part demand quantity, and historical leaf nodes of the historical demand driving characteristics are determined through the decision tree; obtaining target demand driving characteristics of the nuclear power station in a target operation time period, generating spare part demand variables of the target operation time period, determining target leaf nodes of the target demand driving characteristics through a decision tree, and constructing estimated reference distribution of the spare part demand variables according to historical leaf nodes, the target leaf nodes, historical spare part demand quantities and the spare part demand variables; the method comprises the steps of estimating a spare part demand variable, constructing a distribution fuzzy set according to the estimated reference distribution, calculating a target inventory order quantity of the nuclear power station according to the spare part demand variable, the distribution fuzzy set and a preset expected inventory order quantity, and updating the expected inventory order quantity according to the target inventory order quantity, thereby improving the dynamic flexibility of inventory control.

The invention provides an ICD management method, system and device based on a model and a medium, and relates to the field of interface management, and the method comprises the steps: extracting and defining a function interface, a physical interface, a relation interface, an energy interface and a message interface based on a demand-driven RFLP architecture model; the method comprises the following steps: defining an airborne system modeling language ASML, integrating the ASML into a modeling tool, constructing a system architecture interface model, introducing meta-models into interfaces of different hierarchies as a core framework, and creating an interface definition template; based on the meta-model and a pre-constructed ICD data dictionary, defining an interface verification rule, and monitoring and verifying interface data; and performing version control on the model-based ICD management process, generating and updating a baseline version at a project milestone node, and outputting an ICD document in a standard format. According to the method, the standardization level, design efficiency and quality of airborne system ICD design are improved, and technical guarantee is provided for standardized design and management and control of complex system interfaces.

The application discloses a power system flexibility regulation method and device based on demand broadcast and resource matching, a medium and a product, relates to the technical field of power system dispatching operation and control, and comprises the following steps: calculating a flexibility gap representing the size and direction of system regulation demand by using power grid operation data; encapsulating the flexibility gap into a service order; broadcasting the service order to heterogeneous flexibility resources in a resource pool to replace point-to-point instructive scheduling; receiving declaration information of the heterogeneous flexibility resources; based on the technical label in the order and the received declaration information, sequentially performing compliance screening, economic sorting and safety constraint checking on the responding resources to form an executable winning combination; issuing an execution instruction to the resources in the winning combination and monitoring the execution process, and performing market settlement according to the actual contribution amount and the bid price monitored, so that the application can realize demand driving, price guiding and automatic calling of the flexibility resources of the power system.

An order fulfillment system for a warehouse according to the present invention comprises a control system (301), a memory (306), a modular inventory storage system (312) and a reconfigurable workstation (352). A control system (301) controls fulfillment activities of a warehouse (300), manages configuration of a workstation (352) for order fulfillment, inventory import, or order packaging, and records operational data (294) corresponding to the fulfillment activities in the warehouse (300). The control system (301) includes a plurality of workflows selected from a workflow library (304) stored in a memory (306). A memory (306) holds operational data (294). The selected workflow and the configuration of the modular inventory storage system (312) correspond to a current state of the warehouse (301) defined by the selected portion of the operational data (294) and the expected demand.

This invention belongs to the field of data element market allocation technology, and discloses a demand-driven dynamic valuation method and system for data assets. The system includes a user-end module and a dynamic valuation calculation center; a buyer sends a valuation request; a demand parsing module parses natural language demands into task vectors; a data-task matching module calculates the multi-dimensional matching degree between the dataset and the task vectors and filters candidate sets; a dynamic valuation engine automatically selects a valuation model based on the matching degree and accuracy to calculate the expected value; a value fusion module integrates quality, scarcity, and risk factors to obtain the final valuation; a price generation module generates dynamic prices based on market supply and demand; and a feedback update module updates the model online based on actual results. This invention achieves accurate dynamic matching of data value and buyer demand, and has advantages such as high automation, strong privacy, and traceability. It can be widely applied to data transactions and enterprise data assetization.

The invention discloses a demand-driven Turing Machine (NDTM) model method, which is used for a maritime affair remote sensing detection task, and is used for solving the limitation of a current deep learning system in the aspects of autonomy, generalization and interpretability. According to the method, symbolic reasoning and state transition based on reinforcement learning are combined, so that an intelligent agent can internally represent dynamic requirements, select a self-adaptive strategy and execute an interpretable decision-making process. In order to verify the effectiveness, the method is applied to a marine remote sensing image ship detection task: a proper YOLOv11 sub-model is dynamically selected through a lightweight reasoning module according to deduced internal requirements instead of being embedded into a fixed detection framework. Experimental results on a standard remote sensing ship detection data set show that the NDTM-guided framework not only improves the detection precision and consistency, but also enhances the interpretability of the decision process. The research provides a generalized and explainable framework for the intelligent agent, and lays a foundation for autonomous decision-making in maritime affair application.

The invention provides a passenger demand driven train operation adjustment method and system, and belongs to the technical field of train operation scheduling. A train operation adjustment model is constructed, and a micro train timetable is generated; generating a passenger path selection set by adopting a shortest path algorithm: constructing a passenger discrete selection model, obtaining passenger travel behavior change characteristics caused by train timetable changes, and describing distribution of passengers on train services; integrating the train operation adjustment model and the passenger discrete selection model into a mixed integer nonlinear model; and a transformation and linearization method is introduced to linearize nonlinear terms of the mixed integer nonlinear model, a mixed integer linear programming model is formed and solved, and a final adjusted train operation scheme is obtained. The method is used for adjusting the train operation plan under the interference condition, when the original train operation plan cannot be executed, the train operation plan influenced by interval blocking can be rapidly and automatically adjusted, and meanwhile the passenger satisfaction degree and the enterprise operation benefit can be maximized.

The present invention relates to a computer-implemented method for the demand-based provision of flood protection equipment. In the method, at least the parameters of the location data of a first equipment depot, the parameters of the inventory of flood protection equipment elements in the first equipment depot, the parameters of the region-specific forecast data, in particular meteorological forecast data and / or location-specific condition data, and the parameters of the inventory of flood protection equipment elements in at least one second equipment depot are first made available on a host server. Subsequently, a required selection of at least one flood protection equipment element for at least the first equipment depot is determined on at least one host server based on the location data and / or the region-specific forecast data, and the selection is compared with the inventory of the first equipment depot.If the investigation reveals that there is an additional need for at least one flood protection equipment element, a request for at least one flood protection equipment element will be made to at least one second equipment depot, in particular via an application programming interface.

This application relates to the field of project operation management technology, and in particular to a demand-driven project operation collaborative management system and method. The system uses a demand management module to perform structured parsing of user project requirements and generate demand data and user profiles; a project matching module matches project personnel qualifications, capabilities, and resources based on the demand data and user profiles, generating resource allocation results; a project collaborative execution module constructs a project workspace, records and tracks the project implementation process, forming execution trajectory data; and a project quality assessment module evaluates the project process and delivery results based on the execution trajectory data, outputting monitoring or alert information when anomalies or risks occur. This invention achieves closed-loop project operation management with precise allocation of project resources, traceable execution processes, and predictable risks, thereby significantly improving project implementation efficiency and delivery quality.

The application is a kind of key accurate binding distribution method based on demand-driven strategy, belonging to the security communication technical field of satellite communication system ground station access network. In view of the problems that the current satellite communication system ground access network generally adopts standard VPX board card and cannot independently integrate security module for each channel board card, and the group road cipher machine is inconvenient for key interaction with numerous baseband board cards, the application builds a key to baseband board card accurate binding and distribution model, adopts demand-driven strategy, and realizes efficient and safe distribution of keys. The method includes baseband board card registration and authentication, key demand request, key generation and distribution, key storage and update and other steps, effectively solves the problems of complex key management and inconvenient interaction in the prior art, improves the security and reliability of the system, and is suitable for multi-beam, multi-board card satellite communication system ground station access network environment.