223 results about "Purchasing" patented technology

An autonomous futures contract orchestration platform includes a set of processors programmed with a set of non-transitory computer-readable instructions. The instructions include receiving, from a data source, an indication associated with a product that relates to an entity that purchases or sells the product. The instructions include predicting a baseline cost of purchasing or selling the product at a future point in time based on the indication. The instructions include retrieving a futures cost, at a current point in time, of a futures contract for an obligation to the purchasing or selling the product for delivery or performance of the product at the future point in time. The instructions include executing a smart contract for the futures contract based on the baseline cost and the futures cost. The instructions include orchestrating the delivery or performance of the product at the future point in time.

Systems and methods for purchasing (typically under a factoring model but other models are still possible), on a selected basis, declined payment transactions; receive, for assessment, the failed payment transaction via API; enrich the data received for the failed transaction with external and internal data; define, via one or more predictive models, the expected cause of payment failure; define, via the one or more predictive models the probability of successfully process in the following days the transactions successfully, calculating the associated cost of risk; interact in real-time with the customer where needed; confirm to the party invoking the service, for each transaction sent for assessment, the purchase or not of the failed payment transaction.

A method for constructing an intelligent bid-invitation purchasing customer service system based on a retrieval enhancement generation technology comprises the following steps: constructing a multi-source knowledge base, and integrating and processing customer service work orders, bid-invitation files and laws, regulations and policies; non-sensitive metadata information is extracted through entity recognition to construct a knowledge graph, and a block chain is used for evidence storage; classified navigation is provided during user consultation, and metadata is complemented through brief interactive questions and answers; performing fusion retrieval through a dual-channel RAG architecture to generate answers; and continuously supplementing data and optimizing training. According to the method, the data security is guaranteed, the semantic comprehension capability is improved, the agile response to information change is realized, and the compliance and controllability of the system are enhanced.

The invention relates to an application that utilizes artificial intelligence to enhance project management in construction and repair industries. The system includes a user computing device, an application server, and a database server. The application server processes project data, including blueprints, to generate materials lists, integrates with online marketplaces to facilitate purchasing, and employs machine learning for product recommendations. The system also uses predictive analytics to forecast project deliveries and prevent backorders, while optimizing resource allocation through efficient supplier and material selection. The software application features an AI-powered chat, job planner, marketplace, and cart, providing a comprehensive platform for real-time collaboration among contractors, suppliers, and manufacturers. This innovation streamlines project workflows, reduces errors, and improves overall efficiency in managing construction and repair projects.

A fashion show matchmaking virtual incubator system based on metaverse, and a method thereof are disclosed. A matchmaking database host stores a fashion show item and a matchmaking message, and a server-end device performs a virtual incubator platform. When a user logs in a platform, the server-end device drives a display device to display the 3D virtual fashion display space and the fashion show item. When detecting that the user selects the show item and corresponding matchmaking message, the server-end device generates a design commission request for the user to edit, transmits the design commission request to an order taking device. After the order taking device transmits back a design result, the server-end device displays the design result. After the user confirms, the server-end device displays the purchasing message and generates an order message to perform purchase, thereby improving convenience and efficiency of matchmaking transactions.

The invention discloses an electricity purchase strategy risk assessment method based on multiple market types, and belongs to the technical field of electricity market transaction risk management. Medium and long term, in-province spot goods and inter-province spot goods are brought into a unified risk assessment framework, and collaborative optimization of three markets is realized; three-dimensional risk measurement is introduced, risk identification is more comprehensive, and global optimum can be obtained between cost and risk based on combined risk measurement and scene optimization of CVaR; and through Hash calculation and block chain evidence storage, the integrity of the transaction data is protected, and the non-tampering and transparency of the transaction data are ensured. According to the electricity purchase strategy risk assessment method based on the multiple market types, quantitative risk assessment is provided for traders, the assessment provides more practical data support for transaction decisions, the traders are helped to better understand potential risks and opportunities, and therefore the transaction strategies of the traders are optimized. According to the method, the problem of risk dynamic balance under multi-market collaboration is solved, and auditable and traceable decision support is provided for power grid enterprises.

The invention discloses a shared energy storage fine scheduling method considering multi-scene uncertainty and hierarchical decision, and the method comprises the steps: building system power-energy constraint modeling based on a typical scene set; modeling is carried out based on a typical scene set and system power-energy constraint, electricity purchasing and selling, energy storage efficiency and life degradation cost are comprehensively counted in multiple scenes, a multi-target scheduling model is formed, and opportunity constraint is introduced to ensure supply and demand reliability; based on a multi-target scheduling model, constructing a hierarchical decision-making model which takes a shared energy storage operator as a main part and takes a plurality of micro-grids / communities as an auxiliary part, and establishing a coupling constraint and power balance relation of energy storage charging and discharging-energy state-capacity leasing price; an energy storage dynamic rental price, capacity distribution and a time-sharing charging and discharging plan are obtained by adopting distributed iteration solution, and income allocation can be carried out in combination with an improved Shapley mechanism. According to the invention, the optimal decision of consumption improvement, energy consumption cost reduction and multi-agent coordinated operation under the condition of high-proportion access of new energy can be realized.

A system and method for closed-loop tracking of advertising events through offer redemption with artificial intelligence feedback. A session identifier links device, pass, content, and contextual data throughout a content playback session. Advertisements dynamically inserted into the content stream inherit the session identifier. An offer platform generates offers linked to the session identifier and pass identifier, enabling tracking through distinct lifecycle states from push to redemption. A database captures timestamped and geo-referenced data for each event. An artificial intelligence engine uses redemption and avail events as verified ground-truth outcomes for training machine learning models, enabling supervised learning that establishes causal relationships between ad exposure and purchasing activity. An inventory gateway receives merchant product inventory data. An optimization engine employs demand forecasting and reinforcement learning to generate inventory-driven triggers and offer recommendations. A merchant interface presents analytics for inventory optimization.

The invention discloses an intelligent group meal inventory management and replenishment method, and belongs to the technical field of inventory management, and the method comprises the steps: carrying out the data training through employing a machine learning algorithm based on the preprocessed historical multi-source data, and constructing a group meal demand prediction model; then collecting real-time multi-source data related to group meal inventory, and analyzing the real-time multi-source data by adopting a group meal demand prediction model to determine the group meal demand; dish information in the group meal inventory is acquired, and the replenishment amount of the group meal inventory is identified according to the dish information and the group meal demand amount; and finally, making a replenishment plan of dishes to be replenished by adopting an intelligent optimization algorithm on the basis of the group meal inventory replenishment amount, and sending the replenishment plan to a purchasing department or supplier for automatic purchasing and delivery, so that inventory consumption prediction can be realized, food extrusion or shortage is avoided, and the purchase efficiency is improved. And the inventory management and replenishment efficiency is improved.

The present invention relates to an AI-driven platform for automatically generating an international market entry strategy for Fast-Moving Consumer Goods (FMCG) products. The platform comprises multiple integrated modules including a data ingestion module for acquiring and normalizing data from diverse sources, a demand forecasting module that leverages machine learning to predict market-specific demand and a pricing optimization module that computes retail prices based on landed cost, competitive pricing and consumer purchasing power. Additionally, the platform includes a distribution recommendation module, a benchmarking module for strategy validation against historical patterns and an output module that compiles the final strategy report. The invention provides a scalable and automated solution for companies seeking data-driven expansion into new markets, reducing time, effort and subjectivity in decision-making. The scope extends across industries seeking automated, intelligent tools for global market entry planning.

The invention relates to the field of comprehensive energy system optimization, in particular to a multi-park collaborative comprehensive energy system optimization method considering stepped carbon transactions. The method comprises the following steps: firstly, acquiring multi-source data including energy prices, carbon transaction rules, equipment parameters and park interaction limits; constructing a target function with the purpose of minimizing the total operation cost of the system, wherein the target function covers the energy purchasing cost, the stepped carbon transaction cost and the energy abandoning punishment cost; designing composite constraint conditions of energy balance, node constraint, multi-energy conversion, energy storage dynamics, carbon emission segmented pricing and inter-park energy interaction; and finally, solving and generating a multi-park cooperative operation scheme through a state optimization algorithm. According to the invention, through integration of a stepped carbon transaction mechanism and multi-park dynamic energy flow allocation, the problems of extensive carbon cost accounting and insufficient consideration of an inter-park energy complementation strategy in an existing method are solved, and collaborative optimization of economical efficiency and low-carbon performance is realized.

Multi-layer security permissions and multi-layer security functionality is provided for a purchasing system. A purchasing risk assessment is determined for both a merchant and a purchaser and verified in real-time as a purchaser makes a purchase with a merchant at a merchant site including a physical location or online. Summary identification, verification, tracking and location information and comprehensive identification, verification and location information is provided in real-time for both the purchaser and merchant. Feedback and adaptive learning with artificial intelligence (AI) and using blockchains and other methods provide comprehensive identification, tracking and verification information, adaptable across various different situations and circumstances for purchasers and merchants at merchant sites.

The invention discloses a medicine collection and sale account checking method and system based on identification matching and comparison, belongs to the technical field of computers, and can dynamically integrate historical evidence chains in medicine collection and sale business and predict future business influence by constructing a tense knowledge graph and combining a bidirectional graph reasoning mechanism. Therefore, a comprehensive beforehand risk pre-judgment capability is provided before settlement execution. The quantized settlement credibility score is fused with multi-dimensional information, and the reliability and objectivity of the decision basis are effectively improved. Therefore, the limitation of a traditional reconciliation method in the aspects of time sequence tracing, risk pre-judgment and decision credibility is overcome, the intelligence and automation of the medical collection and sales reconciliation process are realized, and the efficiency and risk control level of a supply chain are improved.

The invention provides an intelligent food material purchasing method and system based on deep learning, and relates to the technical field of data processing, and the method comprises the steps: employing a multi-strategy training algorithm to train a deep learning model through multi-dimensional historical data and food material consumption corresponding to the multi-dimensional historical data, obtaining a food material consumption prediction model, and obtaining a food material consumption prediction model; then, a food material consumption prediction model is dispatched to recognize the multi-dimensional real-time data, the food material consumption prediction amount can be more accurately obtained, the powerful feature extraction and nonlinear fitting capacity of the deep learning model is utilized, the complex mode and influence factors of food material consumption can be more accurately captured, and the food material consumption prediction amount can be more accurately obtained. Compared with a traditional method, the prediction precision is remarkably improved, finally, an intelligent food material purchasing plan is generated in combination with food material inventory data and food material consumption, the intelligent food material purchasing plan audited by workers is obtained, the intelligent food material purchasing plan is automatically generated, the workload of artificial experience judgment is reduced, and the efficiency is improved. And the purchasing process is more efficient and more scientific.

The invention provides a carbon emission intelligent calculation method and device, equipment and a medium, and the method comprises the steps: obtaining the raw material purchasing information of a target supplier, covering the material classification, subclass identification and purchasing measurement, querying a predefined rule base based on the material classification information, determining the carbon emission weight calculation type corresponding to each material, and calculating the carbon emission weight according to the carbon emission weight calculation type. Querying a historical carbon emission intensity record of the target supplier, if no record exists, generating a historical reference coefficient by adopting the reference value of the same-industry and same-scale enterprise, inputting the weight calculation type and the historical reference coefficient into a preset machine learning model, and outputting an emission coefficient and confidence; and finally, carrying out correlation calculation on the emission coefficient of which the confidence exceeds a preset threshold and purchase measurement to obtain the carbon emission of the target commodity. According to the method, through combination of the emission coefficient and the machine learning model, intelligent and differentiated accounting of the carbon emission is realized, the method is suitable for multi-scene supply chain carbon footprint management, and the accounting efficiency and accuracy are significantly improved.

The invention relates to the technical field of virtual power plant optimal scheduling methods, in particular to a multi-user virtual power plant scheduling method integrating risk seeking preference or disgust preference, which comprises the following steps of: establishing a virtual power plant operator model in a deterministic scene; establishing a virtual power plant operator economic dispatching model containing the optimal value and the conditional value-at-risk; establishing a heating ventilation air conditioner user economic dispatching model; based on the game theory, establishing a non-cooperative game economic dispatching model of a virtual power plant operator-multiple heating, ventilation and air conditioning users; and based on an ADMM algorithm, carrying out distributed solution on the non-cooperative game economic dispatching model of the virtual power plant operator-multiple heating ventilation air conditioner users. According to the method, a new thought is provided for the scheduling operation decision of the virtual power plant operator under the influence of multiple uncertainties, and a method is also provided for the energy transaction optimization of the virtual power plant operator and the energy purchasing user.

The invention discloses a door lock continuous entrusting purchase method and system, and the method comprises the steps: building an entrusting relation between the door locks of a client and a client according to the entrusting requests initiated by a plurality of clients on respective intelligent door locks and the confirmation operation of the client on the door lock, and synchronizing a shopping list to the door lock of the client; according to an identity verification result after the delegated person arrives at the unmanned supermarket, generating a collection payment request message containing shopping information of multiple delegated persons, and sending the collection payment request message to a door lock of the delegated person; automatically forwarding a message to a next consignor door lock according to the collection payment request message received by the consignor door lock; and the supermarket system updates a payment state according to a processing result that the door locks of all the consignors complete payment. By using the embodiment of the invention, the efficiency of buying on behalf and the payment security can be improved, and the operation burden of the delegated person can be reduced.

An object of the system according to the embodiment is to effectively analyze the preferences and trends of consumers and reflect them in the development of new products.SOLUTION: A system includes an analysis part, an idea generation part, and a process optimization part. The analysis unit analyzes purchase data of consumers, posts on social media, and evaluations on review sites. The idea generation unit generates an idea of the new product based on a result of the analysis by the analysis unit. The process optimization unit optimizes the product development process based on the idea of the new product generated by the idea generation unit.SELECTED DRAWING: Figure 1

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.

A product release system, method and device that enables product controllers to generate product listings for one or more products as well as one or more customized prepurchase events for each of the products. The product release system, method and device then executes the prepurchase events according to one or more pricing, timing and permission conditions specified for each of the prepurchase events, facilitates the purchasing of the products during the prepurchase events and notifies the product controllers of the results of the prepurchase events.

This invention provides a user profiling and adaptive transaction permission control method for duty-free e-commerce. It belongs to the fields of big data processing and artificial intelligence technology. The invention includes: collecting user status and operation data, generating a fusion feature matrix through feature fusion; injecting this matrix into heterogeneous graph nodes to construct a dynamic graph, and mining hidden group topological features through a graph attention mechanism; inputting the topological features into a large model to deeply mine the intent of proxy purchasing, and outputting a comprehensive user risk confidence score; constructing an environment-aware threshold adjustment center to dynamically adjust risk control thresholds; matching the comprehensive risk confidence score with the dynamic thresholds to execute tiered permission control. This invention achieves the synergy of big data and a large model, enabling accurate identification of hidden proxy purchasing, reducing false positives while ensuring risk control, balancing security and revenue, and realizing user risk identification and permission control in duty-free e-commerce.

An object of a system according to an embodiment is to analyze lead data and existing customer data and optimize sales activities.SOLUTION: A system includes a data collection unit, a preprocessing unit, an analysis unit, a scoring unit, and a presentation unit. The data collection unit collects lead data or existing customer data. The preprocessing part preprocesses the data collected by the data collection part. The analysis unit analyzes the data pre-processed by the pre-processing unit and predicts purchase intention or demand of the customer. The scoring unit performs scoring of the read based on the result predicted by the analysis unit. The presentation unit presents the priority of the lead scored by the scoring unit to the salesperson.SELECTED DRAWING: Figure 1

A log purchasing system comprises a plurality of containers 1a suitable for carrying wooden logs; each container having a unique identity code (13, figure 3). The system includes a plurality of points

We provide the system. [Solution] A means of collecting product data from multiple commercial facilities, A method for predicting demand using machine learning techniques, A means for optimally allocating goods among multiple commercial facilities based on predicted demand, A means of monitoring and updating information on changes in product inventory in real time, A means of analyzing user purchasing behavior and formulating sales strategies, A means of providing information on product inventory status within commercial facilities via a smartphone app, A system that includes means for instructing commercial facilities to replenish their stock based on demand forecasts that take weather information and event information into account.

The invention relates to the technical field of enterprise supply chain management, in particular to a supplier intelligent matching collaboration method for enterprise purchase data. A supplier intelligent matching cooperation method for enterprise purchase data comprises the following steps that S1, enterprise emergency purchase demand data, enterprise historical purchase data and current market data are collected, and the emergency purchase demand data comprise emergency material types, emergency material quantity, delivery time and emergency quality standard data; s2, supplier information is acquired according to the historical purchasing data of the enterprise, stock material data of the supplier information is collected, and the supplier information meeting the preliminary requirements is divided as a first-level supplier group; according to the invention, by integrating the enterprise emergency purchase demand, the historical purchase data and the market dynamic information, an intelligent supplier screening and online bidding mechanism is constructed, and the supplier matching efficiency and accuracy are significantly improved.

We provide the system. [Solution] A means for collecting flyer information from online retail stores, A means of receiving inventory information inside the refrigerator, A means of obtaining food ingredient purchase information based on logistics lead time, A means of receiving weather forecast information, Means of obtaining information on family structure and event dates, A system that analyzes this information and provides optimal recipe and ingredient purchasing advice.

The invention relates to a subway riding commodity purchasing and outbound self-pick-up data control system, and discloses a subway riding commodity purchasing and outbound self-pick-up data control system which realizes line binding and code scanning entrance through a subway handle device, performs commodity display through a sales exhibition and festival operation module, and completes locking and self-pick-up through a remote cancel-after-verification and pick-up module. The data control system is convenient for passengers to select and purchase goods in the process of taking the goods and take the goods conveniently when the passengers leave the station. The system is characterized by comprising a subway handle device, a local propaganda module, a sales exhibition module, a festival operation module, an extraction module and a background operation safety module, the sales exhibition module establishes information interaction with the festival operation module and the background operation safety module, and the sales exhibition module establishes information interaction with the extraction module. Information interaction is established between the extraction module and the background operation security module, and information interaction is established between the background operation security module and the local propaganda module and the festival operation module.

This application discloses a method and system for trading film-grade real-world scene assets, relating to the field of film and television production technology. The method includes: acquiring a virtual scene model; generating an asset identifier using blockchain and storing the asset identifier and the virtual scene model together; acquiring script content input by a purchasing user, querying matching virtual scene models in an asset database to form a matching ranking list; generating a transaction order after the purchasing user selects a virtual scene model, and sending the selected virtual scene model to the purchasing user after payment; acquiring shooting data, generating adjustment instructions, adjusting the virtual scene model according to the instructions to form a new model; determining the adjustment range of the new model, determining the profit-sharing ratio when the purchasing user sells the new model; and listing the new model for sale. This application breaks down asset barriers by establishing a unified virtual scene asset trading platform, allowing enterprises and individuals to upload their own models and participate in transactions, thus transforming idle assets into profitable resources.

Systems and methods for progressive training, heartbeat validation, and error minimization in intelligent agent systems for predictive purchasing and behavior mimicry are disclosed. The system discloses progressive training providing a hierarchy of intelligence, from basic list compilation to advanced predictive models based on user behavior, collaborative device input, social preferences, and budget considerations. The system further discloses heartbeat validation addresses evolving user preferences by intermittently seeking human input, comparing it to responses generated by the intelligent agents, and triggering re-training if deviations surpass a defined threshold. The system further discloses error minimization training which focuses on replicating user intent accurately, employing prompts, satisfaction assessments, and input from other agents. When decision-making involves multiple agents, a comprehensive training approach ensures consistent performance.

A system is provided.SOLUTION: A system comprising: means for receiving purchase information; means for storing an inventory of ingredients in a database based on the purchase information; means for generating an optimal recipe based on the inventory of ingredients and a purchase record; means for transmitting the generated recipe to a user device; means for providing a voice guide and a video guide for supporting cooking by a user in real time; means for receiving a picture of a completed dish and generating a caption for posting to an SNS; and means for displaying a AI screen for posting the generated caption and picture to the SNS on the user device. AI.SELECTED DRAWING: Figure 1