458 results about "Order management" patented technology

The invention relates to the technical field of order management, and discloses a supply chain-oriented intelligent order management method, which comprises the steps of obtaining corresponding multi-modal data through an order demand flow, a production equipment state, logistics sensor dynamic information and an inventory topological graph; analyzing relevance between orders and equipment based on a space-time diagram convolutional network, and generating a capacity allocation scheme; calculating a logistics path planning scheme, predicting a stock stockout risk and generating a replenishment suggestion; if the high-priority order exists, inserting a productivity plan and adjusting an equipment process chain; if resource conflicts occur, dynamically allocating resources; if the path risk value exceeds the threshold value, standby path switching is triggered; adjusting weighting parameters through an adaptive federation algorithm, generating a global strategy and issuing the global strategy to the client; the client dynamically adjusts local configuration and uploads execution effect data in real time; and if abnormity is detected, triggering global strategy regeneration and updating the model through federated learning increment. According to the invention, efficient management of supply chain orders can be realized.

The invention belongs to the technical field of logistics management, and discloses a logistics order management optimization method and device, equipment and a storage medium. The method comprises the following steps: collecting multi-source logistics data in real time through a multi-source heterogeneous sensor; performing space-time dimension feature extraction and correlation analysis on the multi-source logistics data based on a space-time diagram neural network to generate a feature tensor; performing multi-objective optimization by adopting an improved hybrid swarm intelligence optimization algorithm in combination with the feature tensor to generate a plurality of initial optimization schemes for logistics order management; screening out a target optimization scheme from the initial optimization schemes by using a virtual logistics network constructed by a digital twinning technology; in the delivery process, the order execution state is monitored in real time through the Internet of Things equipment, and when an abnormal condition is detected, secondary optimization is performed on the target optimization scheme, so that heterogeneous data streams can be synchronously processed, the optimization time consumption is reduced, secondary optimization can be performed on the optimization scheme for an emergent abnormal condition, and the optimization efficiency is improved. And the logistics order management efficiency is improved.

The invention relates to the technical field of maintenance work order management, in particular to an intelligent management system for after-sales maintenance work orders, which realizes equipment clustering based on a K-means algorithm, considers different user habits and use environment differences, and improves the fault diagnosis precision. A fault propagation network is constructed in combination with association rule mining and a graph convolutional network, and a fault influence path between hardware is described, so that accurate identification of target fault hardware is realized, alternative hardware is intelligently determined in combination with recent maintenance records, and misjudgment and repeated maintenance are avoided. And the intelligent order dispatching module is used for preferentially dispatching the nearby maintenance personnel with the required spare parts by matching the position information of the maintenance personnel with the real-time spare part inventory, so that the maintenance response efficiency is improved. And the model error correction module continuously monitors the operation state of the equipment after maintenance is completed, automatically adjusts node features and edge weight parameters if a prediction result does not accord with actual maintenance, updates a graph convolution model through an incremental learning mode, and improves the self-adaption and evolution capability of the model.

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 discloses an overseas warehouse operation intelligent wave order management method and system, and the method comprises the steps: constructing a commodity incidence matrix, mining a frequent item set, determining the commodity correlation degree, carrying out the centralized picking of high-correlation commodities, reducing the round-trip times, shortening the walking distance, improving the picking efficiency, planning a picking path in combination with the warehouse layout and inventory information, and achieving the intelligent wave order management of the overseas warehouse operation. The method comprises the following steps: preferentially selecting short-distance commodities in the same area, further reducing the picking time, allocating priorities according to order emergency degrees and customer levels, ensuring that important orders are processed in time, improving customer satisfaction, dynamically adjusting the sequence in the picking process, avoiding invalid walking caused by stockout, enhancing path flexibility and adaptability, and collecting warehouse-in and warehouse-out information in real time. Inventory is updated immediately, data are ensured to be accurate and timely, labor intensity and operation time of picking personnel are reduced, labor cost is reduced, and storage equipment loss and maintenance cost are reduced.

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 an intelligent order management method for a cross-border e-commerce platform, and the method comprises the steps: obtaining the order data of cross-border e-commerce platform merchants in a set time period, and extracting good comment orders; extracting a target order according to the signing time, the receiving confirmation time and the evaluation time of the well-commented order; and determining whether the target order is abnormal according to the evaluation text content of the target order, the commodity browsing duration and the commodity browsing frequency, and when the ratio of the number of the abnormal orders to the total number of the orders reaches a second threshold value, marking that the cross-border e-commerce platform merchant is abnormal. Whether the order is abnormal or not is comprehensively evaluated from the aspects of the good reputation number, signing time, good reputation time, evaluation text and the like of the order of the e-commerce platform, then whether the merchant to which the order belongs carries out the click farming behavior or not can be evaluated, meanwhile, the buyer can be evaluated according to the buyer data of the abnormal order, the abnormal order is recognized from multiple aspects, and the user experience is improved. The order abnormity identification accuracy of the e-commerce platform is improved, and the order management range is expanded.

The invention discloses a community work order intelligent management method and device, and relates to the technical field of community service management.The community work order intelligent management method comprises the steps that user work order data containing texts, voices and images are received through a multi-mode interface, and the user work order data are cached to a preprocessing queue; based on a semantic segmentation model, performing multi-dimensional analysis on the user work order data in the preprocessing queue, generating a structured work order comprising an equipment identifier, a fault feature and a geographic position, and associating a problem type label for the structured work order; according to the equipment identifier, the fault feature, the geographic position, the problem type label and an order division decision model, obtaining an assignment instruction of the structured order; and allocating the structured chemical worksheet to a corresponding processing terminal according to the allocation instruction, and updating the processing state of the structured chemical worksheet. According to the invention, the efficiency and response speed of community work order management are greatly improved.

The invention relates to a goods transaction management platform based on a goods counting code and an intelligent verification technology, and the platform comprises a goods counting code generation module, a goods tracking module, an intelligent verification module, a transaction integration module, an intelligent contract module, and an analysis module. The block chain technology is combined to record cargo circulation information, so that full-process tracing is realized; the cargo tracking module collects data such as position and environment in real time through Internet of Things equipment, and provides dynamic monitoring and abnormal early warning for environment-sensitive cargos. The intelligent verification module is combined with the Internet of Things technology to ensure the authenticity of goods information; the transaction integration module supports order management, payment confirmation, refund processing and logistics synchronous sharing; the intelligent contract module automatically executes contract terms based on a block chain technology, so that the transaction efficiency and reliability are improved; and the analysis module carries out risk prediction through a time sequence analysis and anomaly scoring method.

The invention belongs to the technical field of order management, and discloses an order management method based on cloud computing service. The method comprises the steps that the cloud platform receives a passenger position sent by a passenger terminal; acquiring real-time traffic data, defining a screening radius, and generating an order dispatching area for passenger positions; driver positions sent by all driver ends in the order sending area are received; road traffic information is obtained, the road traffic information, the passenger position and all driver positions are fused, the shortest driving time from each driver position to the passenger position is calculated, and a time sorting table is generated; the order is sent to the driver end with the shortest receiving time, and if the driver end does not receive the order, the order is sent to the driver end in sequence according to the time sorting table; according to the invention, cloud computing and big data analysis technologies are fully utilized, intelligent optimization and dynamic adjustment of order distribution are realized, the waiting time of passengers and the unloaded driving rate of drivers can be effectively reduced, the user experience is effectively improved, and the overall operation efficiency is 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 belongs to the technical field of industrial production control, and particularly relates to a diamond roller machining workshop production line process control system which comprises an order management unit, a workshop production line supervision unit and an information visualization unit. The workshop production line supervision unit comprises a real-time data acquisition and processing module, a process parameter intelligent optimization module, an automatic cooperative control execution module and an online closed-loop feedback module; according to the invention, the real-time data acquisition and processing module acquires data and generates a standardized data stream, the process parameter intelligent optimization module dynamically generates optimal process parameters, and the automatic cooperative control execution module performs corresponding control operation on a processing workshop production line. The online closed-loop feedback module conducts online detection on the finished diamond roller and feeds back the detection result to the intelligent technological parameter optimization module, efficient, accurate and intelligent diamond roller machining is achieved, intelligent control over the whole diamond roller machining process is facilitated, and the production efficiency and the product quality are remarkably improved.

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.

The invention discloses an artificial intelligence-based operation and maintenance work order management method and system, and relates to the technical field of artificial intelligence and operation and maintenance management, and the method comprises the steps: constructing a CNN model, optimizing a strategy network and a value network through a PPO algorithm, optimizing model parameters through multi-task learning and gradient updating, outputting an equipment fault probability and a recommendation action, and generating a JSON work order. Based on a classic GBDT framework, a quantum decision tree is used for performing split gain calculation, a loss function is optimized through a quantum Monte Carlo method, the quantum decision tree is iteratively constructed, and a candidate scheduling scheme is output. According to the method, the CNN model is combined with the PPO algorithm to optimize the generation of the work order, the accuracy and timeliness of fault prediction and action recommendation are enhanced, quantum machine learning is introduced into work order scheduling modeling, and the multi-target adaptive capacity of scheduling is improved through a quantum decision tree and a quantum Monte Carlo optimization mechanism.

The invention discloses a clock after-sales service automatic management system, which comprises a user side and a service layer, and is characterized in that the user side has a self-service function of carrying out repair application, inquiring the maintenance progress and submitting service evaluation through a client self-service platform; the service layer is used for intelligently diagnosing the maintenance requirements of clients, automatically managing the processes of all maintenance services, analyzing multi-dimensional data such as historical maintenance data, user portraits and regional culture, and establishing a user-clock association model, so that the system can provide personalized maintenance suggestions according to regional culture differences, use habits and the like of the users, and the user experience is improved. The cultural adaptability of the service enhances the satisfaction and loyalty of the user, and the management mode based on data driving greatly improves the accuracy and adaptability of the after-sales service; by means of intelligent diagnosis and automatic chemical order management, manual intervention is reduced, the labor cost is saved, and the accuracy and timeliness of maintenance service are improved.

The invention relates to the technical field of computer application, in particular to an intelligent management assistant system and method based on a large model, and the system comprises a user interaction module, a large model core processing module, a task analysis module, a function execution module and a knowledge base module. The method has the beneficial effects that an intelligent assistant system integrated with multiple management functions is constructed, and the powerful natural language understanding and processing capability of a large model is utilized, so that accurate analysis and efficient processing of a user instruction are realized; one-stop services such as weather query, schedule management, work order management, answer based on a knowledge base and answer based on networking search results can be provided for the user, the management efficiency and experience of the user are improved, and the requirements of the user for intelligent and convenient management are met.

The invention belongs to the technical field of order management, and particularly relates to a production order supply planning management system based on data analysis, and the system comprises an order data collection module which is used for collecting customer order data, and the customer order data comprises historical order data and current order data; the order data analysis module is used for calculating the demand quantity of product orders in M periods in the future based on the obtained historical order data; the supply chain data collection module is used for collecting data of each production line in a supply chain; the supply chain data analysis module is used for calculating the actual order demand quantity of the product in the M periods in the future based on the product order demand quantity and the data of the production line in the supply chain; and based on the data of the production line in the supply chain and the actual demand of the product, the delivery time index of the order product required by the current customer is calculated.

The invention provides a government affair hotline work order management method, system and device based on a large model and a medium, and belongs to the technical field of large model application. The method comprises the following steps: recording an incoming call of a government affair hotline, and converting the incoming call into a dialogue text; generating cue words by using the cue word template, and inputting the cue words into the large model to generate a work order abstract; extracting keywords based on the dialogue text, generating an index in combination with a work order abstract, retrieving business knowledge in a government affair hotline business knowledge base, recording the business knowledge in a knowledge list, and retrieving similar work orders in a historical work order knowledge base; according to the knowledge list and the similar work orders, whether work order assignment is carried out or not is judged; if the work order needs to be dispatched, retrieving the department knowledge base and the historical work order knowledge base in sequence according to the work order abstract and the knowledge list, generating a work order distribution suggestion, executing a work order element extraction process, and generating and inputting a work order; and if the work order does not need to be allocated, executing a work order element extraction process, and generating and inputting the work order.

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 virtual reality wine product sales platform system with personalized wine list customization, which relates to the technical field of wine product sales and comprises a user management module, a virtual reality display module, an information acquisition module, a demand analysis module, a dynamic wine list generation module, a cost benefit analysis module, an order management module and an inventory management module. Compared with a traditional personalized wine list customization service, the virtual reality wine product sales platform system with personalized wine list customization can perform personalized wine list customization and adjust customization parameters in real time while a user freely explores and selects wine products in a VR environment without depending on a preset template or option, so that the user experience is improved, and the user experience is improved. Therefore, a completely personalized customization body is provided, the highly personalized customization service meets the pursuit of consumers for personalization and exclusiveness, and the purchase experience and satisfaction of the users are improved.

The invention relates to the technical field of digital management, and particularly discloses a publishing house full-process digital management system based on big data analysis, which comprises a publishing house topic selection planning module, a topic selection content determination module, a publishing house order management module, a book inventory monitoring module, a book quality evaluation module and a book copyright management module. According to the method, a topic selection feasibility evaluation model is established through book multi-source data fusion, topic selection accuracy is improved, production and printing management is intelligently planned through a paper format optimization algorithm, a book inventory prediction model is established through fusion of sales and inventory data, inventory allocation management is realized, and the production and printing efficiency is improved. The printing quality problem is automatically identified through standardized deviation analysis, copyright key links are subjected to uplink evidence storage, a press is promoted to transform from experience driving to data driving through a big data analysis technology, and scientization of topic selection decision, refinement of production management, standardization of quality management and control and full chain of copyright protection are achieved.

The invention provides a supplier management system, method and device and a medium, and belongs to the technical field of enterprise supply chain digital management, and the system comprises a multi-role collaborative management module which carries out the user role authority control management of suppliers, service providers, internal inspection departments, internal purchase operation departments and system administrators; the contract and order management module is used for receiving signed electronic contracts and generating hardware and software orders; the order acceptance module is used for receiving quality inspection results of hardware and software by an internal inspection department and outputting acceptance data; the dynamic evaluation module calculates scores of suppliers and service providers according to the acceptance data and historical acceptance data; the automatic payment module is used for paying the payment amount according to the scoring results of the suppliers and the service providers and the content of the electronic contract and updating the state of the contract; and the risk control list module is used for freezing the suppliers and the service providers which exceed the set times of low-score risk early warning. The supplier management process is optimized, the efficiency is improved, and the risk is reduced.

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.