327 results about "Order management" patented technology

The invention provides a supply chain order placing management method and system based on big data analysis, and relates to the technical field of supply chain management. The method comprises the following steps: respectively carrying out qualification hierarchical auditing on a purchaser and a supplier to obtain a comprehensive auditing result; the purchaser multi-source data and the supplier multi-source data are integrated, and a dynamic demand-supply cooperation plan is generated; according to a purchaser order, based on a compliance audit result, automatically matching a compliance and adaptive supplier list; a multi-level supply chain bidirectional view is constructed, and cross-level commodity rapid positioning and inventory synchronization are realized through cascade screening; supplier performance data, purchaser demand change data and environment data are monitored in real time, and dynamic risks actually occurring in the performance process are identified; and according to the dynamic risk linkage access risk file, triggering graded early warning and dynamically adjusting the operation authority, thereby effectively solving the problems existing in the traditional supply chain order placing management method, and improving the transparency, flexibility and risk management capability of the supply chain.

The invention provides an internet right product agent management system, and relates to the technical field of product agent management. The system comprises a product management module, an order management module, an agent management module, a database and a data analysis module. The system processes on-off and stock of products through the product management module, the order management module calculates commission, and the agent management module achieves credit evaluation. The data analysis module predicts requirements through a multi-layer architecture; a data input layer integrates internal and external data; the analysis engine layer adopts feature coding and a time attention mechanism to model space-time correlation, and outputs a demand prediction formula; and the decision output layer generates an agent personalized report through inventory calibration, credit grading and regional weighting strategies, recommends products and early warns risks. The system realizes intelligent acquisition and sales decision making, and improves the operation capability and market influence of the system.

The invention relates to the technical field of network operation and maintenance, and relates to an intelligent management and control method and device for an operation and maintenance work order, a computer program product and electronic equipment. The method comprises the steps of performing intention recognition on demand description information in an operation and maintenance work order based on a work order management and control agent, and determining a work order type and a work order task of the operation and maintenance work order according to an intention recognition result; according to the work order type and the work order task, generating an operation and maintenance guidance scheme of the operation and maintenance work order based on the operation and maintenance corpus knowledge base through the work order management and control agent; determining a target operation and maintenance worker based on the work order type, a work order adaptation model and a work order intelligent scheduling strategy through a work order management and control agent, wherein the work order adaptation model is a model representing the adaptation degree of the operation and maintenance worker and the operation and maintenance work order; and automatically distributing the operation and maintenance work order and the operation and maintenance guidance scheme to the target operation and maintenance personnel, and performing automatic order staring management and control on the operation and maintenance work order through the work order management and control agent so as to complete the disposal of the operation and maintenance work order. The management and control processing efficiency and quality of the operation and maintenance work order can be improved.

The invention discloses a dynamic order distribution optimization system based on deep learning, and relates to the technical field of order management, and the system comprises a multi-dimensional dynamic data collection module which is used for obtaining the multi-dimensional dynamic data of each service item in real time; the project emergency feature calculation module generates a project emergency feature value reflecting the resource allocation priority; the resource reachability feature extraction module outputs a resource reachability feature value reflecting the task assignment difficulty level; the composite dispatch risk feature fusion and optimization model module performs dynamic weighted fusion on the two types of feature values to generate a composite dispatch risk feature vector, inputs the composite dispatch risk feature vector into an asynchronous parallel genetic optimization model to perform dispatch path search, and introduces a convergence premature recognition mechanism to prevent the algorithm from falling into local optimum; and the dispatching strategy dynamic adjustment and feedback optimization module continuously optimizes model parameters through feedback of an actual service execution result to realize closed-loop iteration update of a dispatching scheme.

A method, system, and program product includes an integrated artificial intelligent system for generating a work order by including processes configured to execute demand forecasting, tailored pricing, service provider matching, and dynamic job order management. An example leverages data analytics to forecast demand, determine tailored prices, match users with nearby service professionals, teams, and offers via a marketplace network, and manage job orders using a dynamic work order management tool. The system provides service delivery and enhances customer satisfaction. Generating the work order may include performing a task selected from a list that includes at least one of: demand forecasting, tailored pricing, service provider matching, and dynamic job order management. Based on the performed task, the system may match a user with nearby service professionals via a marketplace network to generate a job order and manage the job order.

The invention discloses an electronic ticket ordering and payment application system based on a block chain, relates to the technical field of block chains, and is used for ticket business whole-process digital management, and a user interaction module supports multi-terminal operation and information management; the block chain order management module is responsible for order chaining and state updating; the multi-mode payment module supports double-track payment and encrypted transmission; the comprehensive matching module is linked with the block chain order management module and comprises a meal subsystem, a tourism subsystem, a hotel reservation subsystem and the like, and the passenger ticket verification module realizes multi-mode verification; the data storage module stores key data; and the intelligent contract scheduling module automatically executes the pre-deployed contract. The problems that an existing system is poor in data safety, low in efficiency and insufficient in adaptability are solved, ticket transaction safety and process automation are improved, data synchronization is guaranteed, multiple languages and multiple currencies are supported, user privacy is protected, multiple scenes are adapted, and travel and supervision requirements are met.

The invention relates to the field of computer science and technology, and discloses an intelligent operation management platform for multi-scene application aggregation, which realizes full-life-cycle management and accurate association of commodity labels in a label management module, realizes full-process management and control and dynamic optimization of coupons in a coupon management module, and realizes full-process management and control and dynamic optimization of the coupons. Full-link fine management of commodities from classification, attributes to information is realized in the commodity management module, standardized processing and risk monitoring of multi-source and multi-state orders are realized in the order management module, and platform management and control of supplier classification, qualification and association logic are realized in the supplier management module. Accurate configuration and multi-terminal adaptation of advertisement resources are realized in the advertisement management module, authority hierarchical management and control are realized in the platform role management module, and cross-platform user information unification and life cycle management are realized in the platform user management module. And finally, the problems of function fragmentation, response lag, poor industry adaptability and weak risk prevention and control of a traditional platform are solved.

The invention discloses a digital power equipment management system which comprises an equipment automatic management module, a network topology visualization module, an intelligent alarm strategy engine, an automatic inspection execution module, a work order closed-loop management module, a multi-dimensional safety management and control module, an asset full-life-cycle data center and an AI fault prediction module. According to the invention, automatic discovery and full-life-cycle intelligent management of equipment can be realized, network topology dynamic visualization and fault rapid positioning capabilities are improved, a false alarm rate and operation and maintenance cost are reduced through triple verification intelligent alarm and adaptive routing inspection, a standardized operation and maintenance system is constructed in combination with a work order closed-loop process and multi-dimensional safety management and control, and the operation and maintenance efficiency is improved. And potential faults are warned in advance by using an AI prediction technology, so that the intelligent level and the operation reliability of power equipment management are comprehensively improved.

A system for receiving a product dataset associated with a product comprising one or more subproducts, a first corresponding product dataset associated with a first corresponding product, and a second corresponding product dataset associated with a second corresponding product. A system may determine a product model output corresponding to the product, wherein the product model output is a single, value-weighted indicator of the product. A system may determine a first variability index corresponding to the first corresponding product based at least on the product model output and the first corresponding product dataset, and a second variability index corresponding to the second corresponding product based at least on the product model output and the second corresponding product dataset. A system may display a visual indicator on a graphical user interface the first variability index and the second variability index.

The invention relates to the technical field of hotel reservation systems, and particularly discloses a hotel reservation system and a bidding method for hotel reservation, and the hotel reservation system comprises a customer end module, a merchant end module, an order management module and a transaction execution module. The customer end module is used for receiving room use demand information input by a user, generating an order request and sending the order request to the order management module; the merchant end module is used for receiving the order request broadcasted by the order management module and feeding back an order receiving willingness according to the current empty room rate and a preset strategy; the order management module broadcasts orders to merchants meeting conditions according to the order requests and receives order receiving responses of the merchant end module; and the transaction execution module is used for generating a transaction contract after the merchant receives an order and broadcasting the transaction contract to the customer end module, and after the user agrees with the transaction contract and pays successfully, the transaction execution module deducts platform commission from the payment amount of the user and transfers the remaining amount to the merchant account.

The invention discloses a new energy automobile rental order-charging collaborative energy consumption optimization system and method, and aims to solve the problems of high operation cost, poor user experience and difficult power grid adaptation in the new energy automobile rental industry. The system adopts a layered architecture of a hardware layer, a data layer, a business logic layer and an application layer, the hardware layer collects data of vehicles, charging piles and the like, the business logic layer realizes collaborative management and control through order management, charging scheduling, energy consumption prediction and a strategy optimization module, and the application layer serves enterprises, users and a power grid. According to the method, through data acquisition, order processing, energy consumption prediction, charging plan optimization and dynamic adjustment, peak-valley charging cost reduction, efficient charging pile utilization and power grid load balance are realized. According to the scheme, the enterprise operation cost can be reduced, the user satisfaction degree is improved, the power grid stability is guaranteed, the industry intelligent development is promoted, and remarkable economic and social benefits are achieved.

The invention discloses a supply chain automatic performance method and system based on order state triggering, and relates to the technical field of supply chain management, a purchaser terminal communicates with an order management server to create an order, order detail data and associated contract data are input, and the order management server detects the validity of the order; and if the associated supplier terminal confirms that the order is accepted, the order state is modified into a to-be-delivered order state, the to-be-delivered order state information is interacted with the order management server, and the order management server pushes the to-be-delivered order state to the order associated party terminal. According to the invention, order state change is taken as a core trigger point, and automatic circulation of the whole process from order creation, supplier confirmation, delivery, transportation to sign-in is realized. Each link automatically verifies data and pushes information through the system, traditional modes of manual receipt transmission, telephone communication and the like are replaced, the performance period is remarkably shortened, the manual operation cost is reduced, and the system is particularly suitable for enterprises with weak informatization basis to quickly improve the management efficiency.

Provided in the present application are a computing power scheduling platform and a computing power leasing system comprising same. The computing power scheduling platform comprises: an order management unit, which is configured to receive at least one computing task from each platform user; a storage space allocation unit, which is configured to allocate to the platform user a data storage space having a target capacity; a computing power allocation unit, which is configured to allocate, on the basis of computing power requirements of the computing task, a corresponding computing node to the computing task; and a cost calculation unit, which is configured to record the computing resource usage of the computing task and generate corresponding cost information. The computing task is packaged in an independent container, and the container is started on the computing node allocated by the computing power allocation unit, such that the computing task is executed. The embodiments of the present invention realize unified scheduling and management of computing power resources by means of containers and virtualization technology, effectively increase the utilization rate of computing power and reduce usage costs, and prevent unnecessary waste of computing power.

The invention discloses a rule engine and low-code dual-drive power grid digital graph fusion treatment platform and method. The platform comprises an infrastructure layer, a data layer, an algorithm engine layer and a business application layer. And the data layer is used for accessing and managing multi-source power grid data. And the algorithm engine layer comprises a rule engine module for configuring and executing data verification, digital graph association and exception handling rules, a data quality diagnosis algorithm module for performing data quality diagnosis to identify exceptions, and a digital graph fusion driving engine module for realizing bidirectional linkage between data and graphs. And the business application layer comprises a low-code arrangement platform for customizing a governance scene page and a work order process, a digital graph integrated display module for displaying multi-source power grid data on the same screen, and a closed-loop work order management module for automatically generating and distributing governance work orders. The method constructs a depth digital graph fusion system, improves the anomaly positioning and treatment efficiency, achieves automatic management and control and whole-course tracing, does not need a large amount of code development, and shortens the response period of a new business scene.

The invention belongs to the related technical field of vehicle control and scheduling, and particularly relates to an unmanned vehicle scheduling system and method based on strategy driving, and the system employs a three-layer architecture, and comprises a framework layer which comprises a visual human-computer interaction interface, a scheduling service system and an automatic driving system, data management, work order management, scheduling task execution and unmanned vehicle state feedback functions are provided, and the layer is kept unchanged when a service scene is newly added; the strategy layer supports three elements of dynamic configuration and strategy management and provides a customized interface of scheduling rules and parameters, and the three elements of the strategy comprise a scheduling algorithm plug-in program, a parameter configuration page and a new work order page; and the scheduling layer is used for instantiating and operating scheduling logic, associating a specific strategy, calling the function of the framework layer and the scheduling capability defined by the strategy layer to command the unmanned vehicle to complete scheduling operation, and realizing business work order fulfillment. The system and the method have the advantages of rapid scene adaptation, high system compatibility, low development cost, flexible service configuration and the like.

The present invention relates to the related field of information technology. Disclosed are a product process tracking method and system for physical commodity order management. The method comprises: uploading customer project activity information to a data center; sending a physical commodity list to the data center; a supply side responding to a physical commodity purchasing request and obtaining physical commodity information; importing physical commodity outbound and inbound receipts; taking the physical commodity list as an initial process tracking node, setting a continuous process tracking vector, and generating a product process tracking chain; and after responding to the physical commodity purchasing request, the supply side uploading the customer project activity information and the physical commodity list, and a client refreshing the physical commodity information in real time. The technical problems of low data accuracy and reliability, untimely information updating, insufficient process transparency, and low management efficiency in existing physical commodity order management are solved, and the technical effects of ensuring data accuracy and reliability, realizing real-time order information updating, synchronously performing process tracking, and improving management efficiency are achieved.

The invention relates to the technical field of logistics management, and particularly discloses a modern medicine logistics management operation system. The method is used for solving the problems of high cost, low utilization rate and difficulty in achieving SLA caused by separation of a box and a path, imperceptible and non-quantifiable temperature control risk, slow border-crossing disposal, insufficient loading stability and difficulty in balancing cost and carbon emission in medicine cold chain distribution. Comprising a customer order management module, a vehicle-mounted monitoring module, a boxing path optimization module, an execution scheduling module, an accounting module and a tracing alarm module. According to the method, an encasement-path integrated optimization system is driven by an equivalent stability index generated by multi-source monitoring, path feasibility and loading feasibility are unified through early warning trigger constraint injection and local recalculation, dynamic rescheduling and linkage accounting, meanwhile, carbon emission, time window, stability and compliance event monetization are merged into a target function, and the load performance is improved. The cooperation of a temperature control early warning closed loop and an encasement path is realized, the cost and carbon emission are reduced, and the SLA achievement rate and the transportation efficiency are improved.

Systems and methods are disclosed for order management. One or more processors may receive a first data object containing text data related to user interactions. The processors may input the first data object into a machine-learning model configured to identify intents associated with the data. The processors may receive an identified intent from the model and generate a second data object based on the intent, including the intents, a prompt selected based on the intents, and a function selected based on the intents. The processors may input the second data object into another machine-learning model configured to identify item classifications. The processors may receive an item classification data object from the second model and perform actions related to the function based on the item classification data object.

The invention relates to the technical field of computers and financial science and technology, and discloses a transaction order management method and device based on a state machine pool, a medium and equipment, and the method comprises the steps: generating various types of state machine instances, and adding the generated state machine instances into the state machine pool; and for any newly generated transaction order, acquiring a matched state machine instance from the state machine pool according to the type of the transaction order, so that the acquired state machine instance monitors the transaction order based on a preset life cycle rule, and when monitoring that the transaction order needs to add a processing state, sending the processing state to the state machine instance. And automatically adding a processing state to the transaction order and executing a processing operation of the transaction order in the processing state until the processing operation of all processing nodes in the preset life cycle rule corresponding to the transaction order is completed. Compared with a traditional method, the method has the advantages that the state machine pool is constructed, the order is monitored by the state machine instance, the to-be-processed state is automatically inquired and added according to the rule, management is more flexible, and manual intervention is less.

The invention discloses an enterprise-level intelligent point inspection identification and analysis system based on a graph neural network, and the system comprises a point inspection standard management module which is used for building a point inspection standard library and a unified coding system, and generating a point inspection route; the inspection task generation and execution module is used for generating a periodic point inspection task set; the data uploading and analyzing module is used for uploading the inspection data to a server through an enterprise network to form a trend sequence; the graph structure construction module is used for constructing an inspection network graph and forming an inspection feature set; the graph neural network analysis module is used for calculating an equipment health score and an abnormal confidence coefficient by improving a MixHop model; the abnormity identification and work order management module is used for triggering early warning notification and assessment index updating according to a preset rule; and the data synchronization and report generation module is used for generating a statistical report and an audit log, so that standardized, networked and intelligent management of enterprise-level polling is realized.

The invention relates to an intelligent community charging pile management method and device, equipment and a medium, and the method comprises the steps: obtaining the real-time power utilization state data of a community, determining a corresponding effective charging power interval based on the power utilization state data, building a multi-level charging strategy according to the effective charging power interval, and carrying out the management of the charging pile of the intelligent community. A corresponding charging strategy is matched and issued to the target charging pile, operation data of the target charging pile are dynamically monitored, and the charging power of the target charging pile is adjusted in real time to not exceed a safety load limiting threshold value contained in a preset power grid bearing threshold value; generating and pushing a corresponding exclusive charging mode according to pre-acquired historical use behavior data of the user; based on an intelligent regulation and control mechanism of a cell-level load state and user multi-dimensional information, dynamic perception and hierarchical control of a charging process are realized, the load prediction capability is enhanced, and efficient scheduling and ordered management of charging behaviors in an intelligent cell are realized.

The invention provides an electric power repair work order management method and system based on big data analysis, and the method comprises the steps: calculating a compression control factor through a disaster grade, an influence area and historical work order density when a disaster event is triggered; based on the compression control factor and an original fault work order set, constructing a work order graph, setting a graph division threshold according to the compression control factor, performing iterative aggregation, and generating a compression work order unit set; calculating a comprehensive score for each compressed work order unit; calculating a matching score of each compressed work order and a first-aid repair team based on the comprehensive score and the state of the first-aid repair team, and generating a matching scheme of the work order and the team through a maximum weighted matching strategy; converting the matching scheme into a structured task instruction, including path planning, task abstract, equipment list and the like; for the communication interruption risk area, generating a redundancy instruction and sending the redundancy instruction to a standby first-aid repair team; and an instruction confirmation state is monitored, and a backup mechanism is triggered.

The invention relates to an electric power accounting clearing optimization system based on multi-channel payment. The electric power accounting clearing optimization system comprises a channel access layer, an accounting processing layer, a clearing charging engine, an account checking adjustment layer and a service display and interface layer. The channel access layer is in butt joint with payment channels, comprises WeChat, Alipay, UnionPay, bank outlet counter, self-service terminal and enterprise APP, and collects orders and payment flow; the accounting processing layer is used for order management, payment or refund interface and accounting data formatting standardization; the clearing and charging engine is responsible for collecting funds of each channel and carrying out multi-dimensional clearing according to a settlement rule and a service charge allocation strategy; the reconciliation adjustment layer performs automatic reconciliation, abnormity identification and reconciliation processing, and supports post manual reconciliation; the business display and interface layer is in butt joint with an ERP, a financial system and a cashier system and outputs an accounting report and a clearing result. According to the invention, the power accounting clearing efficiency and accuracy are effectively improved.

The invention discloses a power failure risk marketing and distribution co-processing system based on RPA, and relates to the technical field of power system automation and intelligent operation and maintenance. The system comprises a data preprocessing module, a risk influence factor analysis module and an RPA co-processing flow construction module, original data can be cleaned and standardized, power failure risk factors can be identified and analyzed, an efficient co-processing flow is automatically constructed based on the RPA technology, real-time monitoring and updating of power failure risk equipment and a sensitive customer list are achieved, and the real-time monitoring and updating of the power failure risk equipment and the sensitive customer list are achieved. And marketing and distribution collaboration is enhanced through closed-loop management and control on double-active I-line and single-line. In practical application, risk identification efficiency and repair efficiency can be greatly improved, power failure time and complaint amount are reduced, an automatic and intelligent solution is provided for power failure risk management, and power supply reliability and customer satisfaction are effectively improved.

The invention discloses a campus take-out order data management system based on location-based service, and belongs to the technical field of order management. The system comprises a positioning data acquisition module, an environment adaptive modeling module, a distance correction module and a confidence evaluation module. The method comprises the following steps: triggering a code scanning action of a rider, and synchronously obtaining GPS coordinates and Bluetooth signal intensity; establishing an adaptive signal attenuation model based on historical data of the meal taking cabinet, and calculating a high-precision correction distance; and finally, carrying out spatial vector consistency verification by fusing the GPS position and the correction distance, and generating an arrival confidence score, thereby accurately triggering order delivery confirmation, enhancing the discrimination capability of a false arrival behavior, remarkably improving the accuracy of order state updating, and improving the user experience. The problem of false delivery misjudgment of a rider caused by inaccurate positioning of the GPS in a complex environment in the prior art is solved.

The invention provides an intelligent work order automatic classification system, and relates to the technical field of work order management. According to the system, work order texts are analyzed through an LLM technology, core business phenomena are identified, auxiliary descriptions are eliminated, and an initial phenomenon mark set is generated. And further establishing a cross-sentence association analysis mechanism, dynamically inserting context associators with directivity between discrete phenomena based on syntactic dependency and semantic role labeling, and implementing dynamic weight assignment based on context proximity. The system generates a causal rule set with version identification, and a multi-decision trigger unit processes weighted phenomenon marks in parallel to generate a differentiated candidate root cause set. And the decision conflict quantization unit calculates rule matching degree distribution, and activates rule backtracking verification to ensure decision stability. And finally outputting a root cause classification work order entity with a rule version traceability identifier, thereby realizing automatic work order classification with high accuracy and stability.

A method for safeguarding data in dynamic relational order management involves receiving a data feed and a dynamic order with various order attributes, including a protected dataset and an unprotected dataset. The protected dataset, containing a request type and a reserve execution threshold, is obfuscated from display on a respondent system. Instructions are transmitted to the respondent system to present a proposal request dataset for executing the dynamic order, comprising the unprotected dataset and the data feed. A proposal response dataset is received from the respondent system, including first and second execution values. Adjusted values are generated based on the received data, and an execution action is performed when the adjusted execution values meet the adjusted reserve execution threshold.

The invention relates to a client work order management method and system based on intelligent template dynamic configuration, and the method comprises the following steps: S1, obtaining a business demand document, historical work order data and a field rule library, extracting all business scene universal fields, and storing the universal fields in the field rule library; s2, constructing template metadata according to the field rule base; s3, dynamically generating a work order instance; s4, after the work order is generated, the whole work order processing cycle is driven according to the flow rule, and each work order node and operation action are dynamically executed according to the template flow chart configuration; and S5, regularly and automatically counting the field utilization rate, common process bottlenecks and high-frequency branches through data analysis, generating template optimization suggestions in combination with user feedback and user satisfaction survey data, automatically classifying new problem descriptions by the system according to a pre-trained machine learning model, recommending the most suitable template, and finally, carrying out data analysis on the new problem descriptions. And a work order dispatching strategy is optimized in combination with historical efficiency data. According to the invention, high flexibility and intelligence of work order management are realized.

Various versions of a customer-friendly smart dining table are disclosed for streamlining all processes and meeting customer needs and interests from food ordering to delivery directly on the table. The table may comprise an interactive interface capable of receiving touch-based inputs, voice-based inputs, or both from patron(s) and displaying output(s) respectively. The interface may comprise a feedback module to provide automated assistance to the patron(s) in food selection and customization of the menu, an order management module to allow the patron(s) to place food orders, a payment module to enable the patron(s) to complete payments directly from the table, a power management module to manage power usage and ambient lighting, and a leisure module to interact with various entertainment options. The interface may be capable of concurrently processing inputs from a plurality of patrons seated at the table.

The invention relates to the technical field of computers, in particular to an internet fresh agricultural product distribution management system which comprises an order management module, a logistics management module, an inventory management module and a data analysis module. The order management module is used for processing customer orders, including order receiving, processing, tracking and state updating, so as to ensure efficient processing of the orders; the logistics management module is used for monitoring the temperature and humidity of the fresh agricultural products in the transportation process and planning a distribution route so as to ensure that the fresh agricultural products are delivered to customers in the shortest time; the inventory management module is used for monitoring the inventory level of the fresh agricultural products so as to ensure that enough inventory meets the order requirements; and the data analysis module is used for optimizing a purchasing strategy through data analysis. According to the invention, optimization of the fresh agricultural product distribution process is facilitated.