98 results about "Market place" patented technology

The application discloses a customer demand response prediction method and system based on double-model multi-source information fusion. The application integrates customer historical purchase, product price and regional market supply and demand multi-source data to construct a three-dimensional time series data set. Based on a sliding window, a customer daily sample sequence is generated to construct a survival analysis prediction framework. The core is to construct a double-model parallel prediction architecture. The first model is a survival analysis model based on an attention mechanism, which is used to predict the conditional risk sequence of customer future daily purchase. The second model is a double-head neural factor decomposition machine model, which is used to calculate the interest score of the customer for each product. The two are fused to generate the customer's daily purchase demand risk prediction results in the future multiple prediction days, and then the customers with purchase intention and their predicted purchase days are screened out. The application combines time dynamics and product preferences, and improves the accuracy and interpretability of demand prediction.

The application discloses a power market electricity price mechanism coordinated evolution implementation method, and particularly relates to the technical field of power market operation and regulation; based on a multi-dimensional power market scene set, evolution track characteristic parameter sets of the electricity price mechanism are extracted; a similarity clustering algorithm is used to divide the electricity price mechanism into coupled mechanism clusters, and a coupling degree coefficient matrix is constructed; a coordinated evolution function group is constructed based on the coupling degree to represent the linkage response relationship between the mechanisms; a disturbance factor is introduced to optimize the robustness of the model, forming a robust evolution model; the optimized model is applied to the current operating state of the target area, and the electricity price mechanism state prediction result of the next period is output; the electricity price tearing point and the mechanism conflict point in the prediction result are further identified, and the high-risk regulation interval is marked; the application can realize dynamic linkage modeling and stability early warning between multiple mechanisms, and improve the adaptability and regulation precision of the electricity price mechanism under high uncertainty scenarios.

An electronic trading system utilizes a Match Engine that receives orders, stores them internally, calculates tradable combinations and advertises the availability of real and implied orders in the form of market data. New tradable items defined as combinations of other tradable items may be included in the calculation of tradable combinations. A technique is disclosed for suppression of the calculation and / or subsequent listing of an implied order when the order is either undesired or unnecessary in the market therefore.

Provide a system. 【Solution means】 An information collection means for automatically obtaining market data and competitive information from a communication network or a recording medium, An analysis means for predicting market trends and organizational needs based on the obtained information, A hypothesis generation means for automatically generating a proposed hypothesis according to the analysis result, A document creation means for automatically generating a proposal and documents based on the proposed hypothesis, A progress monitoring means for monitoring the progress of work based on the proposal, A warning means for detecting problems during work and presenting solutions, Means for a user to collect the latest information in a specific area and reflect it in the proposal for improving work efficiency, A system including the above.

This invention discloses a modeling method based on a multi-product electricity market clearing and settlement mechanism. The method includes identifying key concepts in the electricity market, including homogeneous products, heterogeneous products, product groups, and product conversion; determining data based on a bidding function; determining data based on a true function; constructing a general model for centralized bidding market bidding and settlement; and constructing a general model for bidding market clearing. The mathematical model established by this invention can better express the relationships between various factors in the electricity market.

The application discloses a data product pricing method and device based on reinforcement learning, and a medium. The method comprises the following steps: obtaining the cumulative total cost and the total number of calls of a target data product, and calculating a break-even bottom price of the target product; determining a value adjustment coefficient through a preset parameter mapping relationship according to multi-dimensional value evaluation parameters, and adjusting the break-even bottom price to obtain a benchmark price; calculating a price deviation value between the benchmark price and a market median price; when the price deviation value exceeds a preset threshold, generating an expected selling price based on the current operating state parameters of the market through a reinforcement learning agent; performing a gray-scale test on the expected selling price to determine a full-amount effective state; and based on the effective expected selling price, performing the verification and cancellation of the number of calls through a blockchain in response to the number of calls paid by a buyer. The cost and value are anchored, the reinforcement learning dynamic pricing and delivery feedback closed loop are linked, and the pricing can be adjusted according to market and quality changes.

A method and system for multi-market collaborative optimization of independent energy storage in the electricity market is proposed. This method acquires the statistical distribution characteristics, peak-valley structure characteristics, and extreme event characteristics of daily historical electricity price sequences, and clusters them to obtain typical days. Each typical day is divided into normal days and risk days. At the bottom layer, based on the operational data of each energy storage unit on risk days, the constraints of intraday decision parameters are adjusted to meet the constraints of safe energy storage operation. At the top layer, using the operational data of each energy storage unit on normal days, and aiming at the optimal market economic objective, the baseline values ​​of intraday decision parameters for each energy storage unit are determined under the constraints of the adjusted intraday decision parameters. At the bottom layer, based on the operational data of each energy storage unit on normal days and the baseline values ​​of intraday decision parameters, the baseline values ​​of intraday decision parameters for each energy storage unit are optimized to maximize energy storage operating efficiency and minimize energy loss, thereby obtaining a profit-maximizing control strategy under multi-market collaboration to achieve executable monthly and annual scheduling for the project.

Provide a system. 【Solution means】 Means for performing multilingual processing, Means for collecting and analyzing market data, Means for obtaining regulatory and cultural information, Means for selecting business partners, Means for providing information to users, Means for providing regulations and cultural backgrounds related to electronic payment services, Means for proposing business partners for providing electronic payment means, A system including means for constructing an optimal service provision strategy including consideration of market culture and regulations.

A method and system for multi-market collaborative optimization of independent energy storage in the electricity market is proposed. This method acquires the statistical distribution characteristics, peak-valley structure characteristics, and extreme event characteristics of daily historical electricity price sequences, and clusters them to obtain typical days. Each typical day is divided into normal days and risk days. At the bottom layer, based on the operational data of each energy storage unit on risk days, the constraints of intraday decision parameters are adjusted to meet the constraints of safe energy storage operation. At the top layer, using the operational data of each energy storage unit on normal days, and aiming at the optimal market economic objective, the baseline values ​​of intraday decision parameters for each energy storage unit are determined under the constraints of the adjusted intraday decision parameters. At the bottom layer, based on the operational data of each energy storage unit on normal days and the baseline values ​​of intraday decision parameters, the baseline values ​​of intraday decision parameters for each energy storage unit are optimized to maximize energy storage operating efficiency and minimize energy loss, thereby obtaining a profit-maximizing control strategy under multi-market collaboration to achieve executable monthly and annual scheduling for the project.

A bid optimization apparatus and method are provided. The method comprises the following steps: collecting data on current bid amounts, auction outcomes, and performance metrics; assessing market volatility and estimating a win probability for various bid levels based on the collected data and assessed market volatility; determining a bid suggestion based on the win probability, a specified budget and a risk tolerance level; and generating suggested bid change percentages for an initial bid value in the online auction bid system based on a highest bid change return on investment estimation of the bid suggestion.

A secure, compliant trading platform for securities exchange using the open outcry methodology within a secure electronic exchange environment that reduces or eliminates unfairness and opportunities for fraud within the marketplace. Enhancements to the system include the addition of an exchange blockchain for recording all trade events, smart contracts that allow the use of digital currencies for monetary transactions associated with trades, and an intelligent exchange assistant that monitors the exchange member's activity and offers contextual notifications and makes recommendations in real-time to assist the exchange member. The system assures that private information is retained private and the blockchain records immutable data that is used for compliance checking and performance analytics.

We provide the system. [Solution] A means for analyzing data on user characteristics, interests, experiences, and skills acquired from an information processing device, Methods for analyzing industrial market data imported from external databases, A means for generating suitable occupations and career paths for users based on the aforementioned analysis and results, A means of presenting generated occupations and career paths to users, A means of acquiring information in conjunction with home automation devices and enabling interaction with users, A system that includes this.

We provide the system. [Solution] In order to suggest the most suitable items based on the user's preferences, characteristics, budget, and lifestyle, a means of collecting purchase history, browsing history, and social networking data to generate user characteristics, A means for selecting and proposing the most suitable items for the user using artificial intelligence processing based on the user's characteristics, A means of virtually trying out or placing selected items in a user's characteristics or environment using augmented reality technology, A means of comparing market values, obtaining the most economical purchasing options and available discount information, and presenting them to the user. A means of interpreting user inquiries using natural language processing and providing relevant information, A means of providing a more intuitive purchasing experience through virtual try-ons of items that users are interested in, A system that includes this.

The application discloses an intelligent settlement system and method for short-term electricity transaction of a power spot market, and the method comprises the following steps: step one, data acquisition and preprocessing; step two, prediction analysis and output of a prediction result; step three, generation of a dynamic adjustment factor; step four, acquisition of an optimal settlement strategy and automatic settlement; and step five, generation of a settlement report and notification of both transaction parties. The long short-term memory network algorithm is adopted to predict power load and price fluctuation in a short term, data support is provided for short-term market trend prediction, and the method is favorable for assisting in formulating an economically reasonable settlement scheme. Through the introduction of the dynamic adjustment factor, the load change rate, the output fluctuation coefficient and the subsidy change amount are comprehensively considered, so that the settlement process can be flexibly adapted to complex and changeable market conditions. Through the self-learning and dynamic adjustment capability of the settlement system, the optimal settlement strategy can be adopted according to real-time market feedback in a short-term transaction scene, so that the settlement result is ensured to be closely matched with the actual market condition.

The application discloses a kind of devices and methods for assisting individual power users to participate in power market quotation, device includes data input module: the type of power market that individual power user participates in is input, the transaction period under the type of participation, the power that each transaction period participates in;Data storage module is arranged by device operator, in networked state, daily update operator issued market information and user information by each device;Data analysis module: for the certain power market of certain time scale of individual power user, carry out the analysis of suggested quotation based on the historical transaction information of power market and the analysis of suggested quotation based on the historical transaction result of individual power user;Data output module: the result obtained by data analysis module, the visualized suggested quotation output for user reference, weaken the hindrance of individual power user participating in power market, promote its enthusiasm of participating in power market transaction, promote demand side resource to participate in power market, guarantee the safe and stable operation of power system.

We provide the system. [Solution] Means of obtaining market information, A means of analyzing acquired market information to predict price fluctuations, Based on the analysis results, a means to automate the buying and selling of assets, A means of generating personalized suggestions through interaction with the user, A means of regularly reporting on the user's investment performance, A means of proposing ways to optimize consumer behavior based on feedback on investment results, A system that includes this.

Methods, apparatus, and systems to determine a niche market of items or services, the first phase of which identifies a gap between demand and supply for a set of items. Session logs may be evaluated to compare transactions involving a specific item to those of a larger group of items. The resultant information identifies areas of high demand, but with low availability. The niche market information may be provided as direct merchandising items for sellers. In one example, the method generates niche market item web pages in specific categories. Additional methods, apparatus, and systems are disclosed.

This application provides a method, device, storage medium, and program product for determining the exchange resources for goods. It acquires attribute information of the item to be exchanged, and based on this, retrieves target similar items from an item pool that meet similarity requirements, accurately obtaining target similar items that are meaningful for determining the exchange resource value of the item to be exchanged. Based on the exchange resource value of the target similar items, a preliminary range of exchange resource values ​​for the item to be exchanged is defined to avoid deviations caused by fluctuations in a single reference value. Then, considering the actual exchange situation of the target similar items within a preset time period, the target exchange resource value for the item to be exchanged is selected from the exchange resource range. By introducing similar items and historical exchange data, the determined exchange resource value is more in line with market conditions, significantly improving the market adaptability of the exchange resource value and promoting the circulation efficiency of goods. The automated process reduces the subjectivity and cost of manual intervention, improving the efficiency of item exchange.

The application discloses a kind of based on digitalization's commodity data display method, it is related to data processing technical field, and the specific steps of the method are as follows: commodity data is collected from multiple data sources, and commodity data is stored in central storage node, the data source includes commodity sales platform, supplier database, market research agency, the commodity data includes price change, sales data fluctuation, product upgrade iteration node information, based on digitalization's commodity data display method of the application by creating the time axis backtracking function of commodity data, user can in-depth understand the complete development history of commodity since listing, can judge its price stability according to price change history, predict future price trend, for merchant, can comprehensively analyze the market performance of self product, the correlation of sales data fluctuation and product upgrading in different time periods, to accurately locate the advantages and disadvantages of product, timely adjust marketing strategy.

We provide the system. [Solution] A means of collecting and storing users' payment history in a database, A method for analyzing payment history collected using machine learning algorithms and extracting user purchasing patterns, A means for generating product recommendations based on user-specific purchasing patterns, A means of collecting the latest market activity information and making the best possible proposals to users, A means of analyzing natural language input from users and providing appropriate information, A means of selecting and notifying market activity information when arriving at a specific facility using location information, A system that includes this.

We provide the system. [Solution] A device that collects consumer data and analyzes consumer intentions, emotions, and trends using natural language processing technology, A device that proposes optimal advertising transmission and budget management based on past advertising activity data, A device that monitors the actions of competing companies and predicts market changes, A device that generates customized messages for each customer, A device that analyzes purchasing trends based on sales history and provides personalized product recommendations, A device for evaluating the effectiveness of a marketing strategy and suggesting the next strategy, A system that includes this.

To provide a novel display system and a novel display method capable of performing meaningful analysis and classification to the trading data and displaying the result to the user in a more intuitive manner so as to allow the user to use the result to provide estimation referring thereto.SOLUTION: A classified display method of centralized market activity comprises: acquiring transaction data; determining a current bid-ask price status; labeling a trading attribute for the trading data based on the bid-ask price status; deciding a displaying position of the trading data based on the trading attribute; identifying a trader identity based on a trading volume of the trading data; deciding a displaying pattern based on the trader identity; updating displaying data of an actual activity graph; and, updating a displaying figure of the actual activity graph.SELECTED DRAWING: Figure 5

This application provides a method for training an intelligent agent model for the electricity market, applicable to the field of artificial intelligence. The method includes: the intelligent agent model is a reinforcement learning model built on an actor-commentator network framework; the actions output by the intelligent agent model are input into an electricity market environment model to obtain the market environment state; wherein the actions are the declared electricity price and declared power, and the market environment state is the node price and winning bid power at the electricity market clearing point; the actor network of the reinforcement learning model is trained using a first loss function; wherein the function value of the first loss function is determined based on the values ​​of the main loss term and the regularization term; the main loss term represents the negative value of the Q-value corresponding to the action, and the regularization term represents the difference between the actual market electricity price and the declared electricity price; the Q-value corresponding to the action is determined by the commentator network in the reinforcement learning model based on the market environment state and the action.

The application provides a marketing strategy dynamic simulation optimization system data processing method and device, and relates to the field of data processing. The method comprises the following steps: establishing an industry market demand prediction model with a specified period based on industry characteristic data; establishing a market competition situation and market influence model based on historical market data, and determining the competition type of each market participant in the market competition structure in the target industry through the market competition situation and market influence model; establishing a production capacity and energy storage model based on the production process characteristic data, the upper limit of production capacity data and the inventory turnover level data of the target industry; constructing a market dynamic twin engine based on the production capacity and energy storage model, the market competition situation and market influence model and the industry market demand prediction model; and dynamically simulating the marketing strategies corresponding to different competition types through the market dynamic twin engine to obtain optimal marketing strategy data with a specified period.

This application relates to the field of information technology and discloses a method and apparatus for product selection and advertising in cross-border e-commerce based on regional popularity analysis. The method integrates multi-channel data on regions, products, and users to construct a multi-granularity regional market knowledge graph and extract regional popularity vectors for candidate products. It mines user characteristics and calculates geographical distance weights to quantify the compatibility of products with regional culture, mines product association strength, and calculates dynamic recommendation scores. A decision-making system is built to generate regional product selection lists and personalized recommendation lists, and strategies are dynamically adjusted through anomaly detection. This method abandons subjective experience and the limitations of single data sources, accurately captures differences in regional market popularity, achieves deep matching between product selection and regional needs and user preferences, solves the problem of supply and demand imbalance, ensures accurate and flexible product selection, helps enterprises improve capital turnover efficiency and market competitiveness, and promotes the large-scale and refined operation of cross-border e-commerce.

Systems and methods for transforming an electronic portfolio. A system includes an electronic crossing platform that receives data defining trade orders of the electronic portfolio during an initial time period; compares portions of the data to determine an imbalance of the trade orders remaining after the initial time period and receives, during a final time period, a final trade order from a fund agent device to offset the remaining imbalance. The platform receives, after the final time period, a benchmark value of the electronic portfolio from a fund device; compares the final trade order with the remaining imbalance to determine an adjustment value; converts the benchmark value to a final value by applying the adjustment value to the benchmark value; and transforms the electronic portfolio into the transformed portfolio by creating paired buy and sell orders among the trade orders received during the initial time period at the final value.

The present application relates to a wall-mounted air purifier with intelligent advertisement projection, which combines air purification and intelligent advertisement projection functions, saves installation space, reduces procurement and maintenance costs, and facilitates efficient management without the need to install and purchase two types of equipment separately. The flat panel display machine is matched with the U-shaped ring seat in the rectangular accommodating groove through left and right rotating shafts and can be flipped around any rotating shaft under the driving of the driving mechanism. Users can flexibly adjust the display angle to ensure clear viewing of advertisements or information acquisition from different positions and angles, improving the advertisement dissemination effect and information acquisition efficiency. The device has rich and diverse functions, expands application scenarios, and is suitable for families, offices, and commercial places such as shopping malls and hotels. The combination of adjustable angle and detachable structure improves practicality and user experience, enhances market competitiveness, and facilitates product popularization and dissemination.

This invention relates to a hybrid game-theoretic optimization scheduling method for an integrated electricity-heat energy system considering energy sharing across multiple industrial parks, belonging to the technical field of integrated energy system scheduling and energy market trading. The method includes: establishing an integrated electricity-heat energy system comprising multiple industrial parks, and constructing a cooperative game model for energy sharing among the parks and a master-slave game model between park operators and park users; transforming the master-slave game model into a single-layer mixed-integer linear programming model, constructing an overall optimization model for the integrated electricity-heat interactive energy system based on hybrid game theory, introducing Nash negotiation theory to decompose the cooperative game problem into two sub-problems, and using the alternating multiplier method for solving them, so as to realize the distribution of cooperative benefits based on the solution results. It aims to solve the technical problems existing in the collaborative operation of multiple industrial parks, such as imperfect energy sharing mechanisms, insufficient multi-entity pricing and scheduling coordination, and difficulty in coordinating the interests between parks and users.