64 results about "Transaction price" patented technology

The invention relates to an interval value carbon price prediction method based on multi-source data fusion and deep learning integration, and the method comprises the following steps: obtaining the actual historical transaction data of a carbon market, collecting the maximum price and the minimum price of the daily actual transaction of the carbon market, and determining an interval value carbon price sequence; key external driving factors influencing the carbon transaction price are screened through feature importance analysis, and data alignment is conducted on the key external driving factors of different market transaction days through a cubic spline interpolation method; cEEMDAN-VMD dual decomposition is adopted, and higher-precision multi-scale characterization of an original interval value carbon price sequence is achieved; and by taking the decomposition result and the determined external key driving factor as input and the carbon price prediction interval as output, constructing a carbon price interval prediction model, and finally outputting to obtain the carbon price prediction interval containing upper and lower boundary values. The method can effectively cope with the non-stationary and non-linear characteristics of the carbon valence sequence, and is good in expansibility and adaptability.

The invention discloses a power transaction auxiliary decision processing method and system based on extreme weather, and relates to the technical field of power transaction decision, and the method comprises the steps: obtaining an extreme weather early warning message to form an original weather early warning data set; performing space-time reference alignment on the data set to generate a grid chart containing a meteorological intensity matrix and a power generation facility distribution index; mapping the meteorological intensity matrix to obtain a meteorological sensitivity coefficient matrix, and carrying out topological association on power generation facility distribution indexes to obtain a power generation side asset vulnerability association table; inputting the two into a risk conduction calculation engine for coupling deduction to generate a power supply-demand imbalance risk thermodynamic diagram; constructing a transaction price elasticity prediction model based on the thermodynamic diagram, and forming a transaction strategy reference matrix; quotation interval suggestions are generated through matching of the decision rule base and are converted into standardized declaration instruction streams to be pushed to the transaction interface end. According to the method, the extreme weather information and the power transaction decision can be accurately joined, and the accuracy and the normalization of the transaction decision are improved.

A real estate transaction system that facilitates integrated real estate transactions by enabling a seller to list a property at a specified price with negotiation parameters, and allowing a buyer to submit offers for those properties. The system supports direct online negotiations where buyers and sellers can place offers and counteroffers in real time. A matching module optimally matches buyers and sellers with real estate agents based on property information, user preferences, agent performance ratings, and geographic location. The system includes a user interface module providing a graphical interface for users to interact with the transaction and matching modules. A data analysis module accesses and analyzes real estate transaction price data from government sources to generate price trend analyses that assist in accurate pricing.

The invention discloses a source-load two-way interactive transaction method and system based on electricity-carbon real-time coupling, and belongs to the field of data processing and energy management. The method comprises the steps of real-time carbon flow accounting and account management, source-load matching, electricity-carbon coupling bargaining, dynamic contract generation, performance accounting and real-time settlement adjustment. The method comprises the following steps: firstly, acquiring real-time marginal carbon emission factors and electric energy metering data, and calculating and updating real-time carbon flow values and accounts of participants; and constructing an electricity-carbon coupling bargaining model for the source-load transaction pair, negotiating to generate an electricity-carbon coupling transaction price, and generating a dynamic contract comprising a price-response function and a carbon flow-penalty reward function according to the electricity-carbon coupling transaction price. And after the contract is executed, settlement is carried out according to the actual carbon flow deviation. According to the method, a dual Nash bargaining mechanism and a dynamic interoperation contract are adopted, real-time carbon flow contribution is taken as core excitation, multi-subject interest conflict and transaction uncertainty can be effectively solved, and low carbon, efficiency and performance robustness of source-load interactive transaction are remarkably improved.

The invention discloses a virtual item transaction data processing method and device. Information texts related to historical virtual article transactions are collected, and historical valuation reference information and historical user related information of historical transaction users are extracted from the information texts through a large language model; when the transaction of the current virtual article is detected, determining current evaluation reference information related to the current virtual article from the historical evaluation reference information, and determining an estimated transaction price of the current virtual article according to the current evaluation reference information; determining current user related information of two current transaction parties of the current virtual article transaction from the historical user related information; and verifying the current virtual article transaction according to the estimated transaction price, the to-be-transacted price of the current virtual article transaction and the current user related information, and outputting an obtained verification result. According to the scheme, the problem that the transaction judgment result is affected due to the fact that the evaluation accuracy is not high in existing virtual article transaction verification can be solved.

The invention relates to the technical field of power systems and automation thereof, and particularly discloses an energy scheduling and decentralized transaction management system based on a battery energy storage system. The method comprises the following steps: collecting battery multi-mode health data through a sensor, and calculating and updating the health state of each battery module by using a Bayesian algorithm; system-level virtual charge state equalization is realized based on a chemical neutral virtual battery abstraction layer; predicting energy surplus or deficit of each node through a causal state space model; for deficit nodes, calculating an optimal energy supply path by a multi-hop energy balance controller; and in combination with a battery health state, an operation condition and the like, a transaction price is generated through a personalized energy token pricing engine, and finally, automatic settlement is performed through a block chain smart contract. According to the invention, the health and chemical characteristics of the heterogeneous battery can be deeply perceived, the asset life and the system safety are improved, and the economy and reliability of the distributed energy storage network are enhanced.

This invention discloses a pricing method and system for distributed electricity transactions in industrial parks that considers the bounded rationality game theory of prosumers and consumers, relating to the field of distributed transaction technology. The method includes: designing a distributed transaction structure for industrial parks, clarifying the transaction identities of prosumers and consumers and the roles of operators; constructing a prosumer payoff model based on prospect theory, deriving the payoff prospect value function, and calculating risk preference parameters through questionnaires and maximum likelihood estimation; constructing a non-cooperative game theory model of prosumers and consumers; and designing a distributed transaction pricing algorithm for industrial parks to maximize the total electricity transaction volume by iteratively updating transaction prices. This invention can capture the bounded rationality characteristics of prosumers and consumers, promote low-price and efficient electricity consumption, improve transaction stability and economy, and provide an effective solution for distributed transaction pricing in industrial parks.

The invention discloses an optimal scheduling method and platform for distributed collaborative mutual aid of multiple virtual power plants, relates to the technical field of intelligent scheduling of power systems, and is used for solving the problems of limited data privacy, slow optimization convergence and opaque transaction execution among the existing multiple virtual power plants. The method comprises the following steps: firstly, calculating power generation cost increments under different output levels according to wind power and photovoltaic output prediction and load demand prediction data of each virtual power plant, and generating a quotation curve reflecting transaction willingness; then, each virtual power plant quotation curve is used as an input, a distribution network topology parameter and a line capacity constraint are combined, a distributed collaborative optimization model based on Lagrangian relaxation is constructed, and parallel solving of local power optimization and coordination layer dual updating is realized; in the iteration process, a penalty factor is adaptively adjusted through the ratio of an original residual error to a dual residual error, and the stability and convergence efficiency of the algorithm are improved; after optimization convergence, the mutual aid power and the transaction price are written into a block chain intelligent contract, settlement and deviation punishment are automatically executed based on metering data on the chain, and a closed-loop scheduling system from distributed optimization to trusted execution is constructed.

According to one embodiment, the commodity sales data processing device provides a registration unit, a price calculation unit, a reception unit, a first application unit, and a second application unit. The registration unit registers items being purchased in a sales transaction. The price calculation unit calculates a transaction price to be paid for the registered items. The reception unit receives information of coupons to be used in the sales transaction. When a received coupon is a first-type coupon, the first application unit applies a coupon benefit associated with the first-type coupon to a registered item. When the received coupon is a second-type coupon, the second application unit applies a coupon benefit associated the second-type coupon to the transaction price after a preliminary transaction price is calculated. The preliminary price reflects coupon benefits associated with any applied first-type coupons.

The invention belongs to the technical field of settlement, and particularly relates to a peer-to-peer power transaction settlement method and system based on an alliance chain, and the method comprises the following steps: S1, obtaining to-be-settled power transaction data at least comprising two transaction parties, the key levels of the two transaction parties, the transaction electric quantity, the transaction price and the transaction time; s2, according to the historical transaction verification reliability and the power grid role identity of each consensus node, calculating to obtain a consensus weight of each consensus node; and calculating the whole-network consensus health degree according to the whole-network distribution of the consensus weight, and taking the whole-network consensus health degree as a regulatory factor. According to the method, false or wrong transactions which do not accord with rules can be filtered out before the data is linked, the authenticity and reliability of the on-chain power transaction data are guaranteed from the source, and the potential operation risk of a power grid is avoided.

The invention relates to the technical field of engineering cost management, in particular to a digital building engineering project cost management system. The system comprises a data acquisition layer, an intelligent analysis layer and a decision output layer, the data acquisition layer is used for sequentially and continuously acquiring physical quantity data, BIM component-level engineering quantity data, market price data and carbon emission activity data of a construction site; the intelligent analysis layer integrates a learning cost prediction model, a BIM-cost mapping engine, a cost deviation traceability knowledge graph and a reinforcement learning simulation module; the decision output layer deploys a dynamic budget adjustment mechanism of block chain evidence storage and executes a carbon cost measurement model; according to the dynamic budget adjustment mechanism of the block chain evidence storage, each budget adjustment is submitted to a permissible block chain network in a smart contract form, and a budget change voucher which cannot be tampered is generated after consensus of multiple nodes; and executing the carbon cost measurement model for calculating the marginal carbon cost in real time and dynamically injecting the carbon quota transaction price into the cost prediction model.

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.

This invention provides a real estate price appraisal system, method, and program that enable real estate agents to easily and accurately determine the fair transaction price of real estate. [Solution] The real estate price appraisal system 1 includes an information acquisition unit 610 that acquires environmental data of the target floor and the target building having the target floor, and a calculation unit 630 that uses a trained model LM that has learned to output the rent and sales price of the target floor and the sales price of the target building from the environmental data.

To provide a game with improved amusement for a player.SOLUTION: The program includes screen display means for displaying a home screen, a deck assembly screen, and a store screen of a game, provision control means for providing a first type of game element and a second type of game element used in a transaction in the game, transaction control means for performing control such that the first type of game element is preferentially consumed and then the second type of game element is consumed in the transaction, and option display means for displaying a total number of the first type of game element and the second type of game element, a breakdown screen option, and a provision screen option on a screen. The first type of game element is given according to a predetermined condition. The second type of game element is provided in exchange for a fee. When the total amount of the exchanged charges exceeds an upper limit amount within a prescribed period, the application control means notifies the user of it. The option displayer displays the breakdown screen by selection of the breakdown screen option and displays the provision screen for providing the second type of game element by selection of the provision screen option.SELECTED DRAWING: Figure 8

To provide a transaction real estate estimation system, a transaction real estate estimation method and a program for estimating which real estate transaction price data managed by a real estate information library indicates the transaction price of which real estate.SOLUTION: A transaction real estate data acquisition part 30 acquires transaction real estate data including transaction price data showing a transaction price, location data showing a location character string common to a plurality of real estates, and transaction period data showing a transaction period. The registered real estate estimation unit 34 is related to the registration application of the divided building, and estimates the divided building which is the target of the registration application indicated by the registration application information in which the character string including the location character string indicated by the location data is indicated as the character string of the location, the purpose of the registration is the ownership transfer trade, and the reception date is within the search period determined based on the transaction time data, as the divided building whose transaction price is indicated in the transaction real estate data.SELECTED DRAWING: Figure 1

The invention discloses a reinforcement learning-based house resource dynamic market valuation prediction optimization system, which comprises a data processing module for collecting real estate transaction, geographic information, economic indicators and policy event data and generating a house resource state vector; the expert data module is used for constructing a weighted expert track set according to expert valuation records and transaction prices; the state recognition module is used for executing point change detection and determining market state identification; the confrontation signal module is used for generating a hetero-variance weighted confrontation reward signal based on the improved GAIL model; the risk constraint module introduces conditional value risk constraints based on quantile regression to generate risk weighted signals; the strategy optimization module is used for updating valuation strategy parameters by the risk weighting signals and distilling the valuation strategy parameters into a lightweight reasoning model; and the deployment updating module is used for executing incremental training and parameter updating based on the newly added data. According to the invention, robust optimization and risk adaptive adjustment of the valuation strategy are realized.

The invention discloses a causal inference-based interpretable real-time bidding reference price prediction method. The method comprises the steps of receiving a bidding request of an advertisement transaction platform, constructing a structured causal model, inputting a historical bidding feature matrix into the structured causal model, and obtaining a causal graph among variables influencing a transaction price through learning by the structured causal model; performing reference price prediction on the bidding request by using a dual-stage dual machine learning method; based on a prediction result of the dual machine learning model and uncertainty quantization, generating a price prediction interval taking an estimated value as a center; generating three-level interpretable information including a node level, a path level and a global level; and returning a bid response containing the reference price prediction and the prediction interval and / or interpretable information thereof to the advertisement transaction platform. According to the invention, high-precision causal inference, interpretable analysis and low-delay online inference of price prediction in real-time bidding are realized.

The present invention relates to a system for estimating a floor area ratio and a business sales revenue on the basis of AI. According to the present invention, a system for estimating a floor area ratio and a business sales revenue on the basis of AI comprises: a land information input unit for receiving, from a user terminal, a location and a development purpose of a target lot subject to development; a floor area ratio prediction unit for predicting a floor area ratio of the target lot on the basis of the location and land information of the target lot; a presale price prediction unit for predicting a presale price per pyeong (3.3058 m²) of the target lot by applying, to an artificial intelligence-based prediction model, siting environment data of the target lot and actual transaction price data of surrounding buildings selected in consideration of the location and the development purpose of the target lot; a sales revenue estimation unit for calculating an expected sales revenue of the target lot by using the predicted floor area ratio and the presale price per pyeong; and an analysis result output unit for outputting an analysis result including the expected sales revenue for the target lot.

The invention relates to the field of real estate transactions, in particular to a real estate transaction system, which promotes integrated real estate transactions by enabling a seller to list objects according to specified prices and bargaining parameters and enabling a buyer to submit bids to the objects. The system supports direct online negotiation, and the buyer and the seller can bid and return prices in real time. A pairing module optimally pairs buyers and sellers to real estate intermediaries using performance scores of the intermediaries, geographic locations, and user preferences based on object and user preferences. The system comprises a user interface module for providing a graphic interface, so that a user interacts with a transaction module and a pairing module. A data analysis module accesses and analyzes real estate transaction price data from a government source, generating a price trend analysis to assist in precise pricing.

The invention is suitable for the technical field of active power distribution network operation optimization, and provides an ADN distributed optimization method and system based on enhanced price update P2P transaction, and the method comprises the following steps: constructing a double-layer distributed optimization model comprising a producer and consumer P2P transaction layer and a physical optimization operation layer; the method comprises the following steps: iteratively optimizing an electric energy transaction price and a transaction volume between adjacent consumer consumers and / or between a consumer consumer and a superior main network based on an enhanced price updating mechanism by taking minimization of the operating cost of the consumer consumers as a target, and outputting an optimized active power transaction plan; on the basis of the optimized active power transaction plan, node voltage is calculated, and reactive power output of the producer and the consumer is optimized; judging whether all node voltages meet safe operation constraints or not; if yes, outputting a final optimization result; and if not, adjusting the active power transaction upper limit of each producer, and returning to the P2P transaction layer of the producer to carry out iterative optimization again.

The invention relates to the technical field of power systems, and particularly discloses a wind power heat storage bilateral transaction method considering peak regulation, and the method comprises the steps: dividing a heat storage device into an independent type and a coupled type; aiming at the independent heat storage device, taking the maximum revenue of the heat storage device and the maximum revenue of a wind power enterprise as a target, and constructing a bilateral transaction model for the independent heat storage device to participate in power grid peak regulation; according to the bilateral transaction model, a heat storage device is adopted to declare consumption of transaction electric quantity, and a wind power enterprise declarates a main-slave game model of transaction price according to the main-slave game model, so that Nash equilibrium is achieved through multiple rounds of games. The method has the advantages that the problems that pressure is brought to power grid peak regulation by large-scale new energy grid connection at the present stage and an existing transaction mechanism is difficult to effectively excite the heat storage device to participate in peak regulation are solved.

The application discloses a kind of based on extreme weather electric power transaction auxiliary decision processing method and system, it is related to electric power transaction decision-making technical field, including obtaining extreme weather early warning message formation original meteorological early warning data set;Space reference alignment is executed to the data set, and the grid chart containing meteorological intensity matrix and power generation facility distribution index is generated;Meteorological intensity matrix is mapped to obtain meteorological sensitivity coefficient matrix, and power generation facility distribution index topological correlation obtains power generation side asset vulnerability correlation table;Coupling deduction is generated in the risk transmission calculation engine by inputting both, and the electric power supply and demand imbalance risk thermodynamic diagram is generated;Based on the thermodynamic diagram, construct transaction price elasticity prediction model, form transaction strategy reference matrix;Through decision rule base matching generation offer interval suggestion, and conversion is standardized declaration instruction stream and is pushed to transaction interface end.This method can accurately connect extreme weather information and electric power transaction decision-making, improve the accuracy and standardization of transaction decision-making.

The application relates to a large model-based consumer market state insight method, which comprises the following steps: identifying target group chat information with a rule-breaking transaction target commodity from acquired group chat information based on a large language model and a pre-configured database; analyzing rule-breaking transaction behaviors of the target commodity existing in the target group chat information according to the target group chat information, classifying the rule-breaking transaction behaviors, and obtaining rule-breaking transaction classification results; analyzing transaction information of the rule-breaking transaction behaviors according to the target group chat information corresponding to the rule-breaking transaction classification results; comparing and filtering the standard transaction price and the standard commodity name of the target commodity according to the transaction information, and obtaining standard formatted transaction information; converting the standard formatted transaction information into a SQL statement and storing the SQL statement in the database; and generating and displaying rule-breaking transaction identification results according to the standard formatted transaction information.

The application discloses a user-side transaction strategy analysis method based on supply amount regulation, comprising the following steps: acquiring preset supply-demand response models for different types of producers and consumers, and acquiring first transaction electric power of the producers and consumers; constructing a first target optimization function, and solving the first target optimization function to obtain an optimal solution of a first transaction electricity price; completing a first-stage electric power transaction based on the first transaction electric power of each producer and consumer and the first transaction electricity price; constructing a second target optimization function, and obtaining an optimal solution of second transaction electric power of a first producer and consumer by solving the second target optimization function; analyzing and acquiring a unified second transaction price of power purchase / sale of the first producer and consumer to an upper-level power grid based on the second transaction electric power of the first producer and consumer; and completing a second-stage electric power transaction of the first producer and consumer based on the second transaction price and the second transaction electric power. The application adopts a two-stage transaction method and introduces a first parameter to realize suppression of malicious competition, thereby improving the flexibility of system platform regulation and transaction amount.

The invention relates to a transaction electricity price trend prediction method based on electric power spot transaction data, and the method comprises the steps: obtaining a first electric quantity data set of power station networking, carrying out the validity verification of the first electric quantity data of the first electric quantity data set, and obtaining a second electric quantity data set, the first electric quantity data being original electric quantity data; a first index data set of electric power spot transaction is obtained, a second index data set is obtained after validity verification is conducted on first index data of the first index data set, and the first index data comprises a set of original meteorological data, original node price clearing data and original new energy output data; the second electric quantity data set and the second index data set are input into an electricity price prediction model to obtain a predicted electricity price, the electricity price prediction model is a K-means + RF model, a transaction electricity price trend with high accuracy can be obtained, transaction loss caused by market fluctuation and unpredictable boundary conditions is reduced, and the overall income is increased.

This invention discloses a method for constructing a trust mechanism for electricity market transactions based on blockchain, relating to the field of electricity market transaction technology. The specific steps of this construction method are as follows: S100, data collection and feature fusion: collecting electricity user equipment operation data, electricity consumption behavior pattern data, power grid interaction data, as well as electricity market transaction price fluctuation data, historical default records, and power grid operation status data. By utilizing the distributed ledger characteristics of blockchain, this invention achieves encrypted storage and tamper-proofing of multi-dimensional information such as electricity user equipment operation data, electricity consumption behavior pattern data, power grid interaction data, and electricity market transaction price fluctuation data, effectively preventing data forgery and tampering. At the same time, by using fuzzy membership functions to create an initial credit scoring model and combining it with a real-time monitoring and scoring update mechanism, this invention can dynamically adjust the credit scores of trading entities, ensuring the accuracy and timeliness of credit assessment.

The invention discloses an electric power system double-layer optimization method based on a hybrid game, and the method comprises the steps: (1) setting an initial transaction electricity price between a power distribution network and a micro-grid, and enabling the initial transaction price to serve as a current transaction electricity price; (2) updating the transaction volume between the power distribution network and the micro-grid based on the principle of minimizing the cooperation cost of the power system; (3) updating the current transaction electricity price based on a dichotomy distributed optimization algorithm, executing the step (2) until the optimal transaction price between the power distribution network and the micro-grid is found out, and issuing the optimal transaction price between the power distribution network and the micro-grid to the micro-grid; (4) minimizing the single-day cost of the basic micro-grid to determine the transaction volume among the micro-grids; and (5) finding out the optimal transaction price between the microgrids based on the adaptive ADMM algorithm, so that the benefits between the microgrids are balanced. The cost of the power system is minimized, and the income balance of each micro-grid is realized at the same time.

To provide a transaction real estate estimation system, a transaction real estate estimation method and a program for estimating which real estate transaction price data managed by a real estate information library indicates the transaction price of which real estate.SOLUTION: A transaction real estate data acquisition part 30 acquires transaction real estate data including transaction price data showing a transaction price, location data showing a location character string common to a plurality of real estates, and transaction period data showing a transaction period. The registered real estate estimating unit 34 is related to a land registration application, and estimates a land that is a target of a registration application indicated by registration application information in which a character string including a location character string indicated by location data is indicated as a character string of a location, a registration purpose is an ownership transfer trade, and a reception date is within a search period determined based on transaction time data, as a land included in a real estate for which a transaction price is indicated in transaction real estate data.SELECTED DRAWING: Figure 1

The invention provides an agricultural supply chain production place field market transaction generation digital-intelligent quotation technology and an AI method, and relates to the technical field of agricultural supply chain transaction data resource utilization research and development, AI decision making and transaction price artificial intelligence prediction. The method is a digital intelligent technology innovation aiming at an agricultural supply chain production place field end product marketing transaction activity. The method mainly comprises the following steps: a transaction vector metadata data processing [3: 3: 3: + / -1] mixed structure of an artificial intelligence model of a digital intelligence technology: vector metadata interconnection of an input layer, hidden layers I and II and an output layer; the AI system physical assembly comprises an information acquisition module, a data processing and representing module, an intelligent calculation module, a feedback and optimization module, a multi-stage transaction supporting module and a modular interface, and replacement and upgrading of the calculation module, the data processing module and the transaction supporting module are achieved. And the artificial neuron performs reverse propagation training and weight adjustment on the model by using a BP algorithm so as to perform continuous optimization.

The invention belongs to the technical field of smart power grids, and particularly relates to a point-to-point energy transaction method and device for defining a price curve based on a virtual line. The method comprises the following steps: giving relevant parameters required by the energy exchange, including a demand-price curve, a supply-price curve and power grid parameters, and giving parameters of an energy storage battery for a participant containing the energy storage battery; each participant is used as a computing node for distributed optimization, an optimization model of the distributed P2P energy trading market is constructed based on given related parameters, and constraint conditions of the optimization model are determined; and iteratively solving the optimization model to obtain energy transaction data including the final transaction price and transaction volume. According to the invention, autonomous cooperation of market efficiency and power grid safety of energy transaction is realized.