306 results about "Delivery efficiency" patented technology

The invention relates to the field of supply chain management and optimization, in particular to a crude oil supply chain management method and system, and the method comprises the steps: constructing a supply chain dynamic model through multi-modal data fusion and causal analysis; real-time data and prediction data are generated based on a digital twinning technology, and cross-node association scenes and extreme climate conditions are simulated; a transportation path, an inventory allocation strategy and a delivery sequence are dynamically optimized through a multi-objective optimization algorithm and a flexible emergency adjustment module; an optimization scheme is automatically executed by using an intelligent contract system, feedback adjustment data and improved scheme data are generated based on real-time feedback, and closed-loop optimization is realized. The dynamic adaptive capacity of the crude oil supply chain in a complex environment is effectively improved, the cost, the inventory turnover rate and the delivery efficiency are optimized, and meanwhile the robustness and the emergency response capacity of the system are enhanced.

The invention provides a railway engineering completion delivery data information extraction method based on digital twinning. Relates to the technical field of engineering data processing. The technical key point of the invention lies in how to construct a dynamic digital twinborn model by integrating various technologies, such as BIM, Internet of Things, big data, AI and the like, and in combination with technologies, such as real-time data monitoring, intelligent analysis, data sharing and the like, the quality control, operation optimization, decision support and completion delivery efficiency of a railway construction project is improved.

The invention relates to the field of order delivery, in particular to a delivery order intelligent management method and system. The method comprises the following steps: collecting a fresh food delivery order stream, and carrying out effective delivery time window calculation to obtain a dynamic effective time window of each order; identifying available deliverymen in the region, performing real-time delivery load evaluation, and generating a real-time delivery load index; performing intelligent order allocation according to the dynamic effective time window and the real-time delivery load index to obtain newly added order information; performing order priority dynamic evaluation based on the newly added order information to obtain an order delivery priority; and carrying out distribution sequence and path re-planning according to the order distribution priority, and generating a latest distribution planning scheme. The fresh food order delivery efficiency is improved, and the customer purchase experience is optimized.

The invention discloses an industrial ERP dynamic scheduling optimization method based on deep reinforcement learning, and the method comprises the following steps: S1, obtaining to-be-scheduled industrial ERP data, and carrying out the preprocessing of the to-be-scheduled industrial ERP data; s2, constructing a heterogeneous graph structure, and setting node types and edge weight parameters in the graph; s3, performing multi-layer graph feature extraction on the initial scheduling state graph based on a graph attention mechanism to generate a node feature vector; s4, constructing a distributed reinforcement learning environment, and setting an independent strategy sub-network for each type of scheduling sub-tasks; s5, performing joint decision-making on the scheduling action to generate a scheduling scheme as a current round scheduling result; s6, calculating a reward value and feeding back the reward value to the corresponding strategy sub-network; and S7, repeatedly executing the steps S1 to S6, and generating a new scheduling action by using the updated strategy sub-network. According to the method, adaptive optimization of industrial ERP scheduling under multi-source heterogeneous data is realized, and the resource utilization rate and the order delivery efficiency are remarkably improved.

The invention discloses a predictive order dispatching system based on digital twinning, and relates to the technical field of intelligent order dispatching, the predictive order dispatching system comprises four core modules: an urban transport capacity digital twinning construction module integrates order dispatching platform historical orders, real-time traffic flow and urban GIS data, constructs and updates a twinning model, and divides standard grid units; a short-term order demand prediction module obtains grid order, traffic and environment feature sequences based on the model, and predicts order quantity and thermodynamic diagrams in 15-30 minutes in the future; a transport capacity supply and demand gap early warning module analyzes the gap and generates early warning; the active intervention and optimization module generates an instruction according to a preset strategy, dispatches transport capacity through order pre-dispatching and the like, and then evaluates and optimizes the strategy according to feedback. The system realizes order pre-judgment, accurate transport capacity allocation, reduction of supply and demand imbalance, shortening of user waiting time, reduction of operation cost, and improvement of delivery efficiency and service quality.

The invention relates to a cold-chain food distribution analysis method and system based on big data, and the method comprises the steps: carrying out the dynamic feature extraction of multi-source monitoring data of a cold-chain food distribution vehicle, and obtaining and generating transportation state parameters; carrying out correlation matching on the transportation state parameters and real-time environment data of the cold-chain food distribution vehicle to obtain an environment influence evaluation result; carrying out distribution efficiency analysis on the vehicle path transportation data of the cold-chain food distribution vehicle based on the environmental influence evaluation result to form initial distribution efficiency data; road condition diagnosis is carried out on the route transportation data, route pre-judgment is carried out in combination with the environmental influence evaluation result, and a route prediction result is generated; and performing cross analysis on the initial delivery efficiency data and the path prediction result, and formulating a global delivery scheme of the cold-chain food delivery vehicle. According to the invention, logistics resource configuration can be optimized, and the overall operation efficiency of cold-chain logistics is improved.

The invention discloses a near space unmanned aerial vehicle launch trajectory optimization method, device and equipment and a storage medium, and the method comprises the steps: determining a take-off point and a target launch point of an unmanned aerial vehicle according to a launch task when the launch task is received; constructing a motion model of the unmanned aerial vehicle, and constructing a target function corresponding to the launching trajectory of the unmanned aerial vehicle and a plurality of constraint conditions based on the motion model of the unmanned aerial vehicle; constructing a putting trajectory planning problem model based on the objective function and a plurality of constraint conditions; based on the take-off point, the target delivery point and the delivery trajectory planning problem model, performing optimization solution on the delivery trajectory to obtain an optimal delivery trajectory; the unmanned aerial vehicle is controlled to be launched in the near space according to the optimal launch trajectory, and the optimal launch trajectory is optimized and solved under the target function corresponding to the launch trajectory of the unmanned aerial vehicle and multiple constraint conditions, so that efficient trajectory optimization of the unmanned aerial vehicle in the near space under the multiple constraint conditions is realized; and the launching efficiency of the unmanned aerial vehicle and the task execution success rate can be improved.

The invention discloses a resource creation method, device and equipment for model service and a medium, and relates to the technical field of computers, and the method comprises the steps: converting a model service deployment demand input by a user into a standardized service template; analyzing the standardized service template to obtain a model service resource scheduling instruction, the model service resource scheduling instruction being used for indicating a target resource pool; and determining a target driver corresponding to a target resource pool indicated by the model service resource scheduling instruction, so as to create cloud resources of the model service in the target resource pool by using the target driver, thereby realizing automatic resource creation of the model service, greatly shortening the deployment period through full-process automatic operation, reducing the labor cost, and improving the deployment efficiency. The heterogeneous resource management process is effectively integrated, the delivery efficiency is remarkably improved, and an enterprise can flexibly and efficiently deploy various AI model services on a private cloud platform and deal with quickly changing business requirements leisurely.

The invention provides an intelligent cooking supervision optimization system based on digital twinning and a construction method, and solves the problems of insufficient whole-process supervision of a traditional kitchen, lagging of real-time early warning and difficulty in operation standardization. The system constructs a virtual model through high-precision modeling (geometry, physics, behaviors and rules); the whole stir-frying link is uniformly coded by using an industrial internet identification analysis technology, so that data tracking and tracing are realized; a real-time data acquisition, transmission and analysis mechanism is established, and seamless virtual-real mapping between physical equipment and a digital platform is realized; and a visual control interface is constructed to support ordering and remote control. A scheduling rehearsal mechanism based on an improved ant colony algorithm is innovatively proposed, multi-task multi-pot dish distribution scheduling is optimized, trial and error cost is reduced, and meal delivery efficiency and system stability are improved. The system provides support for digital and intelligent transformation of the catering industry, and improves food safety supervision and kitchen operation efficiency.

The invention belongs to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle delivery method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the delivery task information of an unmanned aerial vehicle, controlling the unmanned aerial vehicle to fly to an air area to obtain the position information of a target identifier, and recognizing the motion state of the target identifier based on the position information, and when the target identifier is in a moving state, calculating to obtain a predicted moving track of the target identifier through a dynamic target prediction model, generating flight path information according to the environment information in combination with the position information or the predicted moving track, controlling the unmanned aerial vehicle to fly to a delivery position corresponding to the flight path information, and performing wind speed compensation based on the wind speed compensation information. Controlling the unmanned aerial vehicle to deliver the target material to a receiving area corresponding to the target identifier; and based on the environment information and the position information or the delivery position corresponding to the flight path information generated by the predicted movement track, the unmanned aerial vehicle is controlled to deliver, and the delivery efficiency of the unmanned aerial vehicle is improved.

The invention discloses an intelligent bidding method and device based on an Apple advertisement marketing interface, and relates to the technical field of advertisement putting, and the method comprises the steps: constructing a double-branch machine learning model comprising a long and short-term memory time sequence branch and a gradient boosting tree feature branch; training the model by using historical delivery data to obtain a target prediction model; collecting real-time delivery data through an Apple advertisement marketing interface, and generating a plurality of candidate bidding strategies according to a preset business rule; inputting the real-time data and the candidate strategy into a target prediction model to obtain a conversion probability prediction value and a cost distribution prediction value of the candidate bidding strategy; based on the predicted value, calculating a strategy score value through a score function, and screening out a high-score strategy combination; and integrating keywords, audiences, time periods and region adjustment parameters of the strategy combination, and generating an optimal bidding strategy package. According to the application, the Apple Ads advertisement bidding strategy can be efficiently and automatically optimized so as to improve the putting efficiency and the cost control.

The embodiment of the invention discloses a data space and a data interaction method. The data space comprises a plurality of modules, and an efficient intelligent data circulation system is constructed. The data market platform stores data resource description, and the data resource library is responsible for storing data governance information. And the AIAgent module converts query of a data demander into a structured request through a natural language processing technology, and performs data matching. And a matching result generates a data use protocol through the contract management module, so that the data use compliance is ensured. And the user interaction module is used for displaying and confirming protocol content and ensuring consensus of a data provider and a data demander. Once confirmed by the protocol, the data resource description will be delivered to the data demander through the AIAgent delivery engine. According to the invention, the data interaction and delivery efficiency is greatly improved, manual intervention is reduced, intelligent scheduling, development and utilization of data resources are realized, and data transaction circulation is effectively promoted.

The invention discloses an intelligent delivery targeted penetration decision-making method for precision marketing, particularly relates to the technical field of intelligent delivery targeted penetration decision-making, and comprehensively identifies potential anomalies through unified processing of a standardized index set and dynamic association construction of multi-level thresholds; by means of the constraint of a delivery strategy oscillation index on a delivery behavior, dynamic bidding, material optimization and flow distribution can be smoothly adjusted in a fluctuating environment, the controllability of budget consumption and the continuity of a delivery effect are ensured, and a multi-dimensional penetration strategy of competition, scenes, crowds and materials is combined, so that the delivery efficiency is improved. According to the method, high-value user groups are more accurately reached, the material matching degree is improved, the return on investment and the conversion rate are stably kept increased, oscillation and resource waste in the putting process are reduced, and the cross-platform collaborative optimization capability and the risk prevention and control level are improved.

The invention discloses an advertisement putting control method, an advertisement putting system, a storage medium and a program product, and the advertisement putting method comprises the steps: receiving a business district image uploaded by a user based on a user terminal node, and then determining a group portrait corresponding to the business district according to the business district image; and then one or more advertisements most adaptive to the group portrait are selected from the advertisement library according to the group portrait as target advertisements, and target advertisement putting device nodes in the business district are controlled to play the target advertisements, so that the purpose of accurately putting the advertisements is realized, and a plurality of decentralization processes are realized. In this way, the advertisement putting income in unit time is effectively improved, and advertisement putting is more accurate. Moreover, by implementing the above scheme based on the block chain, the purpose of decentration is better achieved, and the problem of low advertisement putting efficiency caused by artificial interference is effectively avoided.

The invention discloses a public transportation auxiliary unmanned aerial vehicle cooperative distribution method considering client point dynamic demands, introduces a public transportation auxiliary unmanned aerial vehicle with large service range coverage to carry out express distribution, and aims to reduce the terminal logistics distribution cost and improve the distribution timeliness. The method comprises the following steps: constructing a generation model which simulates a dynamic customer demand and considers a time window in combination with an actual scene, and establishing a bus auxiliary unmanned aerial vehicle cooperative distribution optimization model which considers the customer point dynamic demand based on a customer point generation mechanism and a bus unmanned aerial vehicle cooperative operation mechanism in the generation model; and aiming at the established model, designing a dynamic information processing strategy based on bus departure time, and fusing the dynamic information processing strategy into an adaptive large neighborhood search framework for solving, thereby obtaining a heuristic algorithm suitable for solving a bus-assisted unmanned aerial vehicle cooperative distribution problem considering the dynamic demand of a client point. The distribution path can be dynamically planned according to the demand points generated at any time, the logistics delivery efficiency is improved, and the distribution cost is reduced.

The invention discloses an intelligent logistics order scheduling method and system, and the method comprises the steps: obtaining a parameter set, the parameter set comprises solid state parameters and dynamic parameters, the solid state parameters are inherent attribute parameters of each order in a to-be-scheduled order queue, and the dynamic parameters are parameters determined according to the dynamic changes of the order queue and an external environment; obtaining a plurality of weight coefficients, wherein the weight coefficient is an importance degree value preset for each parameter; according to the parameter set and the weight coefficient of each parameter, calculating a scheduling priority weight value corresponding to each order through a preset weighting algorithm; ordering the orders in the order queue to be scheduled according to the calculated scheduling priority weight value; and allocating appropriate deliverymen to the orders according to the sequenced order and generating a scheduling instruction. According to the invention, the problems of single logistics order scheduling strategy and difficulty in adapting to real-time dynamic change scenes in the prior art are solved. The distribution efficiency and the resource utilization rate can be improved.

The invention relates to the technical field of resource management systems, in particular to a virtualized resource management platform which comprises an infrastructure layer, and the infrastructure layer converts scattered hardware equipment into a resource pool managed in a unified mode and is composed of a physical server cluster, network equipment and storage equipment. According to the virtualization resource management platform, accurate mapping from physical resources to business services is achieved through perception, decision making, execution and optimization of full-link automation, each link from bottom layer hardware perception to top layer business guarantee of the virtualization resource management platform comprises precise automatic control and is also provided with a flexible manual intervention interface, and the automation degree of the whole link is improved. Finally, double improvement of the resource utilization rate and the service quality is realized, the operation and maintenance cost is reduced, the resource delivery efficiency is improved, rapid business innovation is supported, the level-of-guarantee three-level compliance requirement is met, and the key operation can support audit tracing.

The invention discloses a marketing mobile terminal safety monitoring and dynamic response method and system, belongs to the technical field of information monitoring response, and aims to solve the problems of audience positioning fuzziness, data fragmentation, delivery strategy rigidity, safety risk control difficulty and the like in traditional information touch. The method comprises the steps that potential audience features are positioned, a target population feature system is constructed, and a terminal label is matched to delimit a delivery range; collecting terminal user behavior data in a delivery range, extracting features, dividing information categories, and constructing a multi-dimensional target information database; clustering features to generate a differentiated putting strategy, updating data and re-classifying, and dividing and subdividing a scene to construct a behavior baseline; removing abnormal terminals based on baseline recognition, constructing a category transfer path map, evaluating a strategy effect and judging whether putting is terminated or not according to a standard; according to the invention, the precision, safety and dynamic adaptation of information touch delivery are realized, and the delivery efficiency and effect are remarkably improved.

To improve delivery efficiency.SOLUTION: An information processing apparatus 20 includes: a communication unit 23 for performing communication with a terminal device 30 of delivery staff; and a control unit 21 for acquiring nameplate information concerning a delivery destination and sending the acquired nameplate information to the terminal device 30 via the communication unit 23.SELECTED DRAWING: Figure 1

The invention belongs to the field of intelligent traffic systems and green logistics energy management, and provides a method for optimizing an energy path of an electric vehicle logistics fleet under dynamic traffic, which comprises the following steps of: defining an energy path optimization problem of the electric vehicle logistics fleet under a dynamic traffic environment, the coupling influence of multiple factors such as traffic jam, energy consumption and charging is considered, and a corresponding mathematical model is constructed. And then, designing an optimization framework based on simulation DeepSeek style reasoning, and combining various advanced reasoning mechanisms, such as thinking tree, self-consistency and multi-agent dialogue, to realize dynamic collaborative optimization of charging and paths in the motorcade. And finally, a closed-loop optimization method is provided, and optimal allocation of energy and time is realized by simulating DeepSeek energy decision and later optimization refinement. According to the method, the energy consumption of the motorcade under dynamic traffic can be effectively reduced, and the distribution efficiency is improved.

The invention relates to the field of logistics transportation management, and particularly discloses a visual TMS logistics transportation management system and method, which takes deliverymen, clients and delivery points as transportation network nodes, constructs a dynamic topology based on predicted driving time among the nodes, and provides a visual TMS logistics transportation management system. Deep context association perception is carried out on attribute information such as geographic coordinates and time windows of all transportation network nodes by using a graph convolutional neural network, so that the optimal path connection probability between every two nodes is predicted on the basis, and an adjacent probability matrix between the nodes is generated; and based on a maximum adjacency probability selection principle and an access logic verification mechanism of first delivery and second delivery, determining a transportation route planning result according with business logic, and performing visual display. According to the method, rigid constraints of actual business rules and operation processes can be met, effective delivery decision support is provided for managers and deliverymen, and the intelligent level and delivery efficiency of logistics transportation are remarkably improved.

The invention relates to the technical field of bearing sales, in particular to an MES-based bearing sales management system, which comprises a sales management module, a warehouse management module, a stock management module, a statistical report module and a building and repairing cooperation module, and is characterized in that a real-time linkage mechanism is established, and the delivery efficiency is improved; the core problem of order and inventory disjunction is solved, on-demand, accurate and automatic stock-up instruction generation is realized, the repair and manufacturing precision of bearing overhaul and the product consistency are effectively improved, and the operation safety of client key components is guaranteed.

The invention discloses an application version release time consumption prediction method and apparatus, a device and a storage medium. The method comprises the steps of obtaining version information of a target application version; for each release link, determining a plurality of time consumption influence factors based on a target time consumption prediction model corresponding to the release link; based on the version information, determining factor values respectively corresponding to the plurality of time consumption influence factors; through a target time consumption prediction model, the release time consumption is predicted based on the factor value, and the release time consumption represents the manual time consumption for releasing the application version; the target time consumption prediction model is obtained based on the historical version release time consumption of the plurality of application versions in the release link and the plurality of time consumption influence factors through fitting. According to the embodiment of the invention, quantitative traceability of time consumption influence corresponding to a plurality of links can be realized, the accuracy of predicting release time consumption is improved, the actual optimization of an application version release process is guided, the delivery quality and the delivery efficiency of the application version are improved, and the optimal control of the operation cost is realized.

The present invention provides a multi-door access linkage method, system and storage medium based on takeaway orders. When creating a takeaway order based on a household, a temporary access permission QR code information is selected for creation; the access address of the door lock management platform associated with the household's delivery address is obtained, and a temporary request is sent to the access address of the door lock management platform; the door lock management platform creates temporary access permission QR code information according to the temporary request; according to the temporary access permission QR code information, it is determined that the current QR code type is the takeaway access control type; and a verification message is generated; the door lock management platform verifies according to the verification message and feeds back to the access control management platform to determine whether to open the current access control. Compared with the prior art, when a household conducts a takeaway transaction, a temporary access permission is automatically generated and provided to the delivery person, solving the authorization problem of the access control in the last link of takeaway delivery and improving the takeaway delivery efficiency.

The application provides a reservation type belt warehouse system, which comprises a warehouse device for storing a cargo carrier, a warehousing device for conveying and hanging the cargo carrier into the warehouse device, a delivery device for outputting the cargo carrier stored in the warehouse device, and a warehouse adjusting device for transferring and adjusting the cargo carrier stored in the warehouse device; the warehouse device has a storage type warehouse device and a reservation type warehouse device, the warehouse adjusting device has a cross-warehouse adjusting device for transporting the cargo carrier between the storage type warehouse device and the reservation type warehouse device, and the delivery device is arranged on the reservation type warehouse device. According to the reservation type belt warehouse system, the user can transfer and adjust the recently needed cargo from the storage type warehouse device to the reservation type warehouse device in advance through the warehouse adjusting device, so that the cargo is close to the delivery device, and the delivery efficiency is greatly improved.

Disclosed in the present application are a group-buy data processing method and apparatus, and an electronic device. The group-buy data processing method comprises: displaying group-buy objects having selectable delivery modes; in response to a first user initiating a target group buy for a target object among the group-buy objects, requesting stock keeping unit information of the target object from a service terminal, displaying the selectable delivery modes of the target object, and determining data of an order to be placed of the first user; in response to a target delivery mode among the selectable delivery modes being selected, updating, on the basis of the target delivery mode, a stock keeping unit of the data of the order to be placed; and in response to an order confirmation instruction for the data of the order to be placed, triggering the generation, based on the updated stock keeping unit, of an order of the first user as a first order of the target group buy, the first order comprising information of the target delivery mode. The method solves the problem of how to improve the delivery efficiency of existing group-buy solutions.

The invention discloses a method and a system for publishing and distributing information service, which realize full-process automatic management of application from developer submission and auditing to access party online through unified application uploading, mirror image construction, isolation environment auditing and multi-dimensional automatic verification. The system supports multi-tenant isolated deployment, and a built-in review rule engine completes compatibility, safety and functional verification; realizing cross-environment adaptation based on the standardized container mirror image and the reusable application assets; and dynamic resource scheduling and alarm rollback are supported through a multi-level elastic capacity expansion and contraction and abnormal instance processing mechanism. According to the method and the system, application version multiplexing and operation state visual monitoring can be realized, the delivery efficiency is improved, the operation and maintenance cost is reduced, and the cluster resource utilization rate and the system stability are improved.

The invention provides a request processing method and device, and the method comprises the steps: responding to a received current code merging request associated with a target branch, and obtaining the states of a plurality of code merging entrance guards associated with the current code merging request; on the basis of the weight and the state corresponding to each code merging entrance guard, determining a merging readiness score of the current code merging request; in response to the fact that the merging readiness score is smaller than a set score threshold value, determining a target access control with the maximum weight from at least one unpassed code merging access control; according to the access control failure log associated with the target access control and the first incremental code difference between the source branch and the target branch associated with the current code merging request, merging blocking information is generated and visually displayed, and therefore the automation and intelligence level of the code merging process is improved, and the code merging efficiency is improved. And the problem repairing period is shortened, so that the stability and delivery efficiency of the target branch are improved.

The application discloses a kind of risk data management systems for cross-border supply chain, belong to risk data management technical field, including raw material procurement management module, product warehousing management module, international logistics transportation management module, domestic warehousing management module, domestic distribution management module, comprehensive data management module.The multiple management modules of the present application are set, the information in cross-border supply chain can be managed in a hierarchical comprehensive, the security of information is guaranteed;And by presetting frequency identification graphics on the outer packaging of product, the product's shipment priority level information can be obtained through subsequent identification, and a more reasonable cargo cell unit is determined according to the product's shipment priority level information to store the product, which greatly reduces the delivery time when delivering, improves the delivery efficiency, to some extent, also reduces the warehousing cost, and also improves the user experience.

The invention provides a take-out order scheduling method and system, a storage medium and a program product, and relates to the field of personnel or project management, and the method comprises the steps: generating a path network according to the coordinates of a pickup point and a delivery point of a new order; determining a group of geographic grid indexes covering the path network based on a preset grid cell size to obtain a new order path index set; calculating an intersection index set of the new order path index set and the future path index total set of the candidate rider; and when the number of the unique identifiers of the geographic grid indexes in the intersection index set exceeds a preset path matching threshold value, adding the new order into the order sequence of the target candidate rider with the highest comprehensive score, and adjusting the planned path corresponding to the target candidate rider to complete the scheduling of the new order. By implementing the method, the problem of misjudgment of the smoothness caused by path simplification can be relieved, and the matching accuracy of the order and the rider is improved, so that the overall delivery efficiency is improved.