12 results about "Real time pricing" patented technology

The invention provides a real-time pricing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining real-time user data for pricing; performing feature extraction on the real-time user data to obtain processed user features; inputting the processed user features into a pre-constructed target model to obtain a result, and determining a specified pricing strategy corresponding to the real-time user data; and under the condition that the specified pricing strategy meets a preset validity requirement, determining the specified pricing strategy as a target pricing strategy for implementation. According to the invention, the problem that the pricing is seriously lagged in the prior art is solved.

The invention discloses a short insurance dynamic pricing method based on an AI large model, and the method comprises the steps: S1, constructing a multi-modal risk dynamic perception architecture, and outputting a unified dynamic risk vector with a fixed length; s2, establishing a real-time risk pricing adaptive mechanism based on the unified dynamic risk vector with the fixed length output in S1, and realizing a real-time pricing decision across insurance types; s3, designing an intelligent strategy generation and conflict resolution system, optimizing the real-time pricing decision across insurance types in the S2, and ensuring that the pricing decision achieves the optimal balance between market competitiveness and profit targets on the premise of meeting actuarial constraints and supervision requirements; and S4, constructing a complete decision tracing mechanism by adopting a multi-mode interpretable artificial intelligence technology, and generating an attribution report based on the data output from S1 to S3 so as to realize the conversion of the pricing decision from a black box to a white box. According to the patent technology, through innovative application of an AI large model, a new-generation intelligent pricing solution is provided for short-term insurance services.

Systems and methods are described that enable dealers to manage their end user traffic in an own traffic environment on a distribution platform. The system includes a server configured to provide a single window user interface (SPoG UI) and a real-time data grid (RTDM) module for ingestion and standardization of data from multiple sources. An advanced analysis and machine learning (AAML) model analyzes the data to provide predictive analysis, anomaly detection, and personalized recommendations. The SPoG UI presents real-time data and insights through interactive visualization, enabling dealers to perform operations such as creating offers, issuing orders, and managing customer accounts. The system supports real-time pricing negotiation, compliance management, and integration with external systems via an API. The method and system generates an end-to-end real-time view of the provider's interaction with the end-customer.

The invention relates to the technical field of intelligent retail technologies, in particular to a vending machine real-time pricing method and system based on a multi-dimensional factor, and the method comprises the steps: obtaining the information of a commodity needing to be priced, and the commodity information comprises coordinate information, a commodity name and batch information; based on the commodity information, factor data influencing pricing is collected in real time, and the factor data comprises an inventory factor, a time and environment factor and a commodity attribute factor; based on the commodity information and the factor data, a final price is calculated through a weighted adjustment model; based on the coordinate information, the final price is issued to the vending machine to be updated, transaction data are recorded, and the transaction record comprises the transaction price and the sales quantity corresponding to the transaction price. The method has the effect of capturing the demand change in real time in combination with multiple factors so as to carry out intelligent price adjustment.

A method, apparatus and computer program product are provided for a compiled standardized measure representative of a subset of prescription transactions associated with a controlled substance. The compiled standardized measures may be used in the prescription domain to notify prescribers of a patient's morphine milligram equivalent (MME) to reduce risks related to drug overdose, abuse, and the like. Historical prescription transactions may be accessed to identify prescriptions classified as an opioid or other controlled substance, and that may likely still be in a patient's possession based upon days supply, such that a daily MME may be calculated. Messaging is provided to the prescriber if the amount exceeds a maximum threshold, and the prescription can be changed accordingly.

The invention relates to a queuing reservation system based on dynamic pricing and a scheduling method thereof. The system comprises a user interaction module used for receiving a queuing reservation request of each user; wherein the queuing appointment request comprises user information and an appointment time period; the dynamic pricing engine is used for calculating real-time pricing data based on the spatio-temporal characteristic information; the resource management module is used for acquiring equipment state information of each terminal and maintaining a time resource pool and an equipment resource pool according to the equipment state information; performing resource allocation in a time resource pool and an equipment resource pool according to the reservation time period and the real-time pricing data of each user, and constructing a three-dimensional resource matrix comprising three dimensions of reservation time period-equipment resource-real-time pricing; the intelligent scheduling module is used for generating a queuing queue according to the three-dimensional resource matrix, performing closed-loop scheduling on the queuing queue, and allocating each terminal according to the queuing queue; according to the technical scheme, the queue circulation efficiency can be improved, and the user payment conversion rate is improved.

The invention belongs to the technical field of data processing, and discloses a business sales method, device and equipment based on an invitation code and a storage medium, and the business sales method comprises the steps: generating a digital signature invitation code bound with a user group, and returning the digital signature invitation code to the user group; receiving a target digital signature invitation code submitted by a target user; verifying the digital signature to generate first verification information; verifying the digital signature invitation code to generate second verification information; after the verification is passed, analyzing a group identifier corresponding to the target user; inputting a pricing feature vector obtained by fusing the static rate corresponding to the group identifier and the real-time pricing factor into a pricing rule model, and outputting a final business quotation; and marking the target digital signature invitation code as a used state. The method can be applied to business management systems of financial science and technology, medical health and the like, and solves the technical problems that errors are easy to occur and the efficiency is relatively low when preferential quotation is carried out on group customers in the prior art.

The invention particularly relates to an e-commerce real-time pricing method and system based on multi-modal federal learning. According to the e-commerce real-time pricing system based on multi-modal federated learning, heterogeneous multi-modal data of each participant is aggregated, and commodity demand and user preference joint features are extracted from the heterogeneous multi-modal data; fusing the multi-modal features by adopting a hierarchical attention mechanism, and generating a commodity demand elastic coefficient and a user intention confidence coefficient; on the basis of local encrypted data, a pricing model is trained in a cross-domain cooperative manner through a parameter aggregation mechanism so as to guarantee data privacy; and on the basis of incremental learning and stream-oriented calculation, combining real-time market real-time data streams, and generating an optimal pricing strategy in a second level. According to the e-commerce real-time pricing method and system based on multi-modal federated learning, high-precision and low-delay dynamic pricing is realized, the platform income and conversion rate are improved, a data island is broken, the privacy compliance requirement is strictly met, and a credible technical basis is provided for cross-platform commercial collaboration.

The disclosed system provides a new platform that allows users to access installation target templates, powerful design software, and automated pre-production processes and enables them to create their own production-ready designs. Once a design is complete, the system directly connects the consumer to nearby service providers with the capabilities to complete the work. Importantly, the disclosed systems provide complete real-time pricing transparency. As a user manipulates a design or scrolls through service providers, they are presented with dynamic pricing. The disclosed system represents a novel end to end fully transactional consumer experience.

A method, apparatus and computer program product are provided for providing real-time pricing information to a patient. A patient may submit a prescription inquiry. In response to the prescription inquiry, a cash price inquiry, a prescription benefit inquiry, and a formulary alternative inquiry are generated by a service provider computer accordingly. The various inquiries may be executed by a service provider computer and / or associated systems. Responses may be further processed, such that cash price information, a patient pay amount under a benefit plan, and formulary alternatives and associated costs are included in a prescription inquiry response for provision to a patient or user.

The present application relates to the technical field of intelligent parking, and more particularly to a macroscopic road network parking dynamic modeling and pricing optimization method, which establishes a macroscopic parking dynamic model to quantify and evaluate the influence of parking cruising based on the expected cruising time of vehicles in the region; a feedback real-time pricing strategy based on fuzzy PID is proposed to control the on-street and off-street parking prices in two regions, and under the driving of parking occupancy, the parking prices change, the parking demand in the region is affected by the parking prices and the expected cruising time and thus changes, and by setting a target function to minimize the regional vehicle cruising time, the parking demand of the two regions is balanced; the present application more accurately describes the parking cruising behavior, formulates a real-time pricing strategy more suitable for rapidly changing parking conditions, optimizes the regional vehicle cruising time, balances the parking demand, relieves the parking pressure, and improves the parking resource allocation efficiency.

System and methods are provided for automated SKU management. Embodiments include a user interface for receiving diverse catalog files, a Catalog Transformation module, a Real-Time Data Mesh (RTDM) module, a Master Data Governance (MDG) module, a Global Data Repository (GDR), and a Search Platform. The Catalog Transformation module, through iterative learning, transforms catalog files to a standard format and predicts categorization and attribute mapping. The RTDM module is configured to perform real-time data exchange. The MDG module validates the transformed catalogs. The GDR stores validated catalogs. Embodiments can include a Dynamic SKU Creation module and a Global Pricing Engine for real-time pricing. Embodiments improve data accuracy and SKU management, facilitating integrated order processing and fulfillment. 20 26 20 53 12 06 J ul 2 02 6 2 0 2 6 2 0 5 3 1 2 0 6 J u l 2 0 2 6