151 results about "Transaction model" patented technology

The invention relates to a multi-time scale optimization regulation and control method for a multi-energy virtual power plant based on digital twinning, and the method comprises the following steps: obtaining real-time data of the multi-energy virtual power plant in a physical scene, and constructing a digital twinning model based on a deep neural network; constructing a dynamic stepped carbon transaction model by considering a carbon transaction reward and punishment mechanism; constructing a three-stage optimization framework of a day-ahead stage, an intra-day rolling optimization stage and a real-time adjustment stage based on the digital twinborn model and the stepped carbon transaction model; the three-stage optimization framework is solved, a regulation and control instruction is obtained, and the regulation and control process is completed. Compared with the prior art, the method has the advantages of realizing carbon emission reduction, improving the consumption rate of renewable energy sources and the like.

The invention belongs to the technical field of computer server management, and particularly discloses a laboratory collaborative environment-oriented user and data full-life-cycle server management system, which comprises a container virtualization layer, a server management layer and a server management layer, dynamic resource allocation is supported through a state saving-resource reallocation-environment recovery mechanism; the heterogeneous transaction coordination layer adopts a Saga transaction mode to coordinate a heterogeneous system so as to realize cross-system transaction consistency; the data collaboration ecological layer establishes typed management of a personal data volume, a shared software environment volume and a public data set volume, and supports software environment encapsulation sharing and versioning management; and the metadata management layer realizes real-time update and high-performance query of metadata based on a Redis hot update architecture. According to the method, the problems of inflexible resource allocation, incomplete environment isolation, dilemma in authority management and difficulty in data collaboration and recovery in the prior art are solved.

The invention relates to a risk control method for cross-border trade data. Cross-border trade behaviors are divided into three levels, namely a system type layer of national system / policy triggered transaction, a business type layer of a process chain and an execution type layer of data submission / customs clearance / payment behaviors. Modeling a behavior stability mapping relation among the three hierarchies through sparse matrix reconstruction and adversarial noise regression; introducing an interlayer fluctuation tension coefficient for each transaction to measure offset appearing in a behavior chain; when the tension peak value exceeds a training threshold value, even if single-point data is not abnormal, the event is marked as a potential risk transition event; according to the method, cross-border transaction behaviors are divided into a system type layer, a business type layer and an execution type layer, and an interlayer fluctuation tension coefficient is introduced, so that a cross-level collaborative imbalance phenomenon in a transaction chain is effectively captured. Even under the condition that no obvious field anomaly exists, the pseudo-legal transaction mode caused by behavior chain structure mutation can be recognized, and early warning of non-dominant structure anomaly is achieved.

The invention relates to the technical field of financial information management, and particularly discloses a financial accounting information management system based on artificial intelligence, an automatic financial processing module can automatically identify and extract financial voucher information, process repetitive tasks, analyze unstructured financial texts and convert the unstructured financial texts into structured data; the intelligent risk monitoring module constructs a transaction mode analysis model based on a machine learning algorithm, identifies abnormal transactions in real time, monitors financial indexes and gives an early warning, and also can compare financial operations with criteria and regulations to generate a compliance report; the decision support module constructs and trains a prediction model, carries out financial analysis and generates a customized report; the identity verification module performs multi-factor authentication in combination with voiceprint, facial recognition and dynamic passwords. The financial information can be efficiently and accurately processed, risks are effectively monitored, powerful support is provided for decision making, and meanwhile system information safety is guaranteed.

A device may receive a preauthorization associated with missed transaction prevention for a transaction account of a user, wherein the missed transaction prevention involves preventing a missed transaction associated with merchant accounts of the user. The device may monitor a transaction log of the transaction account and identify a transaction pattern associated with a merchant account based on a plurality of historical transactions identified in the transaction log related to the merchant account. The device may determine that a historical transaction of the plurality of historical transactions is not designated for automatic execution and that an execution of an upcoming transaction corresponding to the plurality of historical transactions is not scheduled. The device may cause an account transaction associated with the upcoming transaction to be automatically executed before a transaction period expiration, associated with the merchant account, passes.

The invention discloses a low-code platform-oriented distributed transaction engine generation method and system and a medium, mainly relates to the technical field of engine generation, and is used for solving the problems of high transaction model selection error rate, low compensation logic development efficiency and poor static strategy adaptability of an existing low-code platform. Comprising the following steps: acquiring a business process, converting the business process into a 128-dimensional feature vector, and determining a corresponding CART decision tree type; inputting the 128-dimensional feature vector into a corresponding CART decision tree to generate a transaction execution plan; inputting specific data of preset core features into the TD3 model, and generating transaction submission intervals and resource allocation data of transactions in the transaction execution plan; collecting a transaction rollback log corresponding to the transaction execution plan, encoding the transaction rollback log into a 512-dimensional semantic vector, and inputting the 512-dimensional semantic vector into the LSTM model to obtain a compensation code; and when the compensation code is updated, injecting the updated compensation code into the runtime environment through a code instrumentation technology.

The invention provides a low-carbon optimal scheduling method for an integrated energy system based on a green certificate-carbon transaction mechanism, so as to reduce the carbon emission of the integrated energy system and improve the renewable energy consumption capability. In order to improve the running flexibility of the IES containing the electro-hydrogen coupling unit, a proton exchange membrane electrolytic cell is introduced, and refined modeling is carried out on the hydrogen energy using process and equipment. A transaction model of a common stepped carbon transaction is improved and combined with a green certificate transaction mechanism, and a combined heat and power energy system model with an adjustable heat and power ratio is constructed; secondly, taking the minimum total cost of the system as an objective function, coupling a carbon transaction mechanism and a green certificate strategy, and performing optimization solution by using a Cplex solver; analyzing the influence of different carbon transaction mechanism parameters and green evidence parameters on the system; finally, four typical scenes are established, the proposed strategy is obtained through comparative analysis, the carbon emission can be remarkably reduced, the consumption amount of renewable energy sources is increased, meanwhile, good economic benefits are achieved, and reference can be provided for low-carbon economic dispatching of the comprehensive energy system.

The invention provides a day-ahead electricity market-oriented multi-virtual power plant transaction decision-making method and device, and relates to the technical field of virtual power plant optimization operation. The method comprises the following steps: establishing a power distribution network operator-virtual power plant master-slave game double-layer structure according to a power distribution network operator and a multi-virtual power plant system; constructing an objective function and constraint conditions of the power distribution network operator pricing game model; constructing an objective function and constraint conditions of the robust transaction model of the deterministic virtual power plant; the uncertainty of wind power, photovoltaic and controllable loads is considered, the deterministic virtual power plant robust transaction model is converted into an uncertainty virtual power plant robust transaction model, and then a distributed robust scheduling model is obtained; solving by adopting a dynamic Kriging meta-model and introducing a local search mechanism to obtain a transaction decision; wherein the column and constraint generation algorithm is adopted to solve the distributed robust scheduling model. The method can help the virtual power plant aggregator to significantly improve the earnings in the day-ahead transaction.

A methodological technical approach is proposed herein that utilizes historical data to employ a heuristic optimization algorithm for data message routing. While not specifically limited to the banking sector and financial institutions, as a practical example, the approach can utilize historical data relating to patterns of transactions for analyzing customer behavior and detecting fraudulent activities. For example, trajectory mining can be used to analyze the transaction patterns of credit card users, or behavioural patterns of mobile banking users, such as checking account balance, transferring funds and paying bills.

The invention provides a flexible distributed energy network multi-agent collaborative optimization method based on MARL, and the method comprises the steps: building a distributed energy network multi-agent interaction framework which comprises a local energy transaction model for distinguishing an intelligent soft switching path, a network cost model based on a power transmission distribution factor, and a power distribution network operator and user income model; a physical system operation constraint model is established and covers intelligent soft switch operation characteristics, network topology radial constraint, energy storage charging and discharging dynamic states, controllable distributed power supply and photovoltaic output limitation, translational load scheduling and DistFlow power flow constraint. And finally, constructing a collaborative optimization mechanism based on a multi-agent near-end strategy optimization algorithm, modeling the system into a partially observable Markov decision process, adopting a centralized training distributed execution framework, and guaranteeing transaction security and data privacy through block chain evidence storage, RSA encryption and an intelligent contract. The system economy and the operation flexibility are improved.

The invention provides a code-free SaaS application rapid development method and system based on data source driving, and the method comprises the steps: constructing a forward business process directed acyclic graph, defining compensation association and reality binding for a forward operation node of the forward business process directed acyclic graph, and generating a visual transaction model; analyzing the transaction model to generate a transaction step sequence, constructing a finite state set and a state transfer function based on the sequence, and packaging the finite state set and the state transfer function into an SAGA process state machine definition object; generating a global transaction ID when a transaction life cycle is started, constructing a transaction context object in combination with the state machine definition object, and serializing to generate an initial transaction context instance; and loading and deserializing the instance, starting a state-driven execution loop, terminating by iterating single-step state transition when the current state belongs to a termination state set, judging a final result of the transaction, and archiving an audit log. According to the method, transaction process modeling and formalized state driving execution are fused, and the method is suitable for SaaS application development of cross-heterogeneous data sources.

The invention discloses an interconnected micro-grid online distributed point-to-point electric energy management method and system, relates to the technical field of interconnected micro-grid management, and aims to construct an electric energy transaction model by taking the minimum energy transaction cost as an optimization target and taking the electric energy of each micro-grid as a decision variable. Respectively inputting the working condition parameters of each micro-grid and the corresponding historical operation data into a preset electric energy optimization model to obtain initial electric energy corresponding to each micro-grid, and performing distributed iterative optimization on the electric energy transaction model according to the working condition parameters and the initial electric energy corresponding to each micro-grid, and obtaining the target energy transaction cost and the target electric energy corresponding to each micro-grid. The problem that a traditional micro-grid electric energy management method is generally low in convergence speed is solved, the real-time requirement of online management is difficult to meet in a large-scale interconnected micro-grid cluster scene, and the running reliability of a micro-grid is reduced.

The intelligent data processing system comprises a distributed edge probe group, a dynamic fraud strategy engine, an intelligent evidence chain construction module and a credible evidence storage interface, the distributed edge probe group is deployed in a core transaction system, a lightweight protocol analyzer is arranged in the distributed edge probe group, an SWIFT / UnionPay private protocol and a real-time desensitization module are adapted in the analyzer, and transaction account masking and behavior track hash solidification are executed at a data source end; the dynamic fraud strategy engine accesses an abnormal transaction flow of the edge probe group, and stores a cross-mechanism transaction mode vector through a graph neural network fraud feature library; the real-time threat evaluation unit detects the transaction time sequence abnormal probability based on a hidden Markov model; the self-adaptive evidence obtaining controller dynamically activates a targeted evidence obtaining instruction according to the threat value, capital flow of a cross-platform is captured through a high priority, and the evidence storage period of a suspicious session is prolonged.

The invention discloses a recommendation method and device for an abnormal transaction model. The method comprises the following steps: extracting model multi-dimensional tag features and a target type realized by the model from abnormal transaction model construction business requirements; disassembling each type of target to obtain a tag feature and a tag parameter corresponding to each type of target; selecting a plurality of to-be-recommended abnormal transaction sub-models containing the label parameters from a pre-constructed abnormal transaction model self-service application library according to the label characteristics and the label parameters thereof; determining a integrating degree value, a main target completion rate and an interpretability strength value of each abnormal transaction sub-model to be recommended; and according to the integrating degree value, the main target completion rate and the interpretability strength value, sorting the plurality of to-be-recommended abnormal transaction sub-models and then recommending the to-be-recommended abnormal transaction sub-models to the user. According to the method, the user can be helped to judge the interpretability strength of the model, the understanding, correction and monitoring capabilities of the user on the model are improved, and the accuracy and efficiency of abnormal transaction model recommendation are improved.

The invention discloses a hydrogen production and hydrogenation integrated station electric energy-peak regulation combined market transaction method considering hydrogen load demand response. The method comprises the following steps: 1) constructing a hydrogen production and hydrogenation integrated station day-ahead electric energy-peak regulation combined market transaction mechanism and framework; 2) constructing a cost model of the hydrogen production and hydrogenation integrated station for regulating and controlling multi-type hydrogen load demand response; 3) considering uncertainty factors such as hydrogenation load of the hydrogen fuel cell vehicle, and proposing a hydrogen production and hydrogenation integrated station market transaction model with maximum operation income as a target based on distribution robustness; 4) constructing a day-ahead electric energy-peak regulation combined market clearing model containing the hydrogen production and hydrogenation integrated station by taking social welfare maximization as a target; and 5) proposing a market transaction strategy solving method based on a differential privacy-consistent alternating direction multiplier method (DP-C-ADMM). According to the invention, a cooperative transaction mechanism in which the hydrogen production and hydrogenation integrated station participates in multiple markets is constructed, and a transaction model based on distributed robustness and a transaction strategy solving method considering privacy protection are proposing.

The invention discloses a multi-time scale peak regulation optimization scheduling method based on an electricity-carbon transaction virtual power plant. A carbon step transaction model, a virtual power plant demand side participation peak regulation scheme and a virtual power plant source side participation peak regulation scheme are improved. And establishing a day-ahead optimization model objective function and establishing a virtual power plant day-ahead stochastic programming model. And establishing an intra-day rolling optimization model objective function. And establishing an improved Shapley value method-based virtual power plant internal income distribution method. The scheme is solved, and multi-time-scale peak regulation optimization scheduling based on the electricity-carbon transaction virtual power plant is achieved. According to the method, the actual carbon emission of the virtual power plant is described more accurately, load side / original side peak regulation is effectively promoted, the influence of new energy output and load deviation can be reduced, the carbon emission, the peak regulation benefit and the output deviation are taken as correction factors to correspond to the virtual power plant carbon transaction model and the peak regulation model, and the method is more efficient and reliable. And participation of users in the virtual power plant is promoted while fairness in profit distribution is ensured.

A computer system, computer-implemented method and non-transitory computer-readable medium to predict transaction activity for a cyclical time period. A predictive transaction model is developed for individual user accounts, where the transaction model incorporates a cyclical data structure representation to detect and analyze transactions.

The invention discloses a virtual power plant game transaction rapid convergence method and system, a storage medium and equipment. The method comprises the following steps: constructing a reference auxiliary service electricity price coefficient including response efficiency, response quality and response reliability of a virtual power plant based on response information; constructing a basic electricity price based on the real-time supply and demand condition and the real-time electricity price of the power grid; constructing a virtual power plant game transaction model based on the reference auxiliary service electricity price coefficient and the basic electricity price; and finally, carrying out iterative convergence on the virtual power plant game transaction model based on the reference auxiliary service electricity price through a Markov decision process and a reinforcement learning algorithm. According to the method, the reference auxiliary service electricity price is constructed in the game transaction model between the virtual power plant and the auxiliary service market, so that the deviation between the initial electricity price and the final market clearing electricity price can be effectively reduced, the number of times of game iteration is reduced, the convergence speed of the game is improved, and the market clearing efficiency is improved.

The invention discloses a resource collaborative and complementary low-carbon configuration method, system and device and a medium, and belongs to the technical field of power system planning, and the method comprises the following steps: building a carbon power market transaction model according to a carbon market transaction mechanism; the method comprises the following steps: establishing a double-layer optimization model of the adjustable resource collaborative complementary configuration by combining the operating characteristics of wind power, photoelectricity, energy storage and thermal power and taking the carbon transaction cost and the carbon quota income of a carbon power market transaction model as constraint conditions through the characteristics of the adjustable resource collaborative complementary configuration; and aiming at the double-layer optimization model, setting a genetic algorithm to solve the double-layer optimization model. According to the invention, by establishing the carbon power market transaction model, the carbon emission cost and the carbon quota income are organically integrated into the power system optimization decision, and deep coupling of economic benefits and environmental benefits is realized.

The invention relates to the technical field of finance, and particularly discloses a compliance risk early-warning detection method for bank-enterprise direct-connection cross-border payment, and the method comprises the steps: obtaining an original transaction sequence of bank-enterprise cross-border payment, and synchronously collecting transaction object information, fund flow data and an error-related supervision parameter sequence; obtaining a transaction mode component according to the original transaction sequence; generating a preliminary risk early warning parameter according to the transaction mode component and the error-related supervision parameter sequence; and obtaining an accumulated number of payment services, and generating an early warning threshold factor and a risk weight factor based on the accumulated number and the fund flow data. According to the method, the hidden association of the amount, the purpose and the time is mined by means of the feature association index, the risk is quantified in combination with the mode compliance deviation degree, and the early warning threshold value and the weight factor which are dynamically generated are matched, so that the risk identification accuracy is greatly improved, the missing report rate and the false report rate are reduced, and particularly, the hidden risk in complex cross-border payment can be accurately captured.

The invention provides a digital employee-based transaction method, device and business system, and the method comprises the steps: obtaining user input data under the condition that a user call instruction is received, and enabling the user call instruction to be used for initiating a transaction process; calling a pre-trained large language model to analyze the user input data so as to determine a user operation intention; determining a transaction risk level of the transaction process according to the user operation intention; and determining a target transaction mode according to the transaction risk level, and interacting with the user according to the target transaction mode to complete the transaction process, the target transaction mode including digital employee independent handling, manual supervision of digital employee handling and manual handling. According to the method, the problem that in the prior art, in the process of taking over digital employees by real employees, due to the fact that delay of voice link establishment is high, service handling efficiency is low is solved.

The application discloses a kind of multi-virtual power plant point-to-point transaction method, electronic equipment and storage medium.First, collect and aggregate virtual power plant internal distributed resources, construct multi-virtual power plant electricity-carbon-backup point-to-point transaction model;Set conditional value at risk model confidence and risk preference coefficient, construct multi-virtual power plant electricity-carbon-backup point-to-point transaction model based on conditional value at risk;Adaptive alternating direction multiplier algorithm (ADMM) based on consensus is used to solve the model in distributed manner, and the transaction strategy of each virtual power plant is obtained.The application considers that virtual power plant aggregates photovoltaic, fuel cell, energy storage, central air conditioning, flexible load and other distributed resources to participate in electricity-carbon-backup point-to-point transaction, which widens the transaction channel of virtual power plant;Value at risk quantifies the potential risk brought by photovoltaic randomness, so that virtual power plant decision makers can weigh benefits and risks;Adaptive ADMM algorithm based on consensus effectively improves the calculation efficiency of model solving.

The invention relates to the technical field of computer security, in particular to a feature space backdoor attack method, system and device based on fusion data transaction model parameter constraint and a storage medium. Obtaining an original training data set, constructing a data transaction model, calculating malicious sample loss values, and screening samples with smaller loss values as target samples; poisoning features are randomly extracted from the original data set, discrete noise is generated through a noise generator to form a trigger, the trigger is added to a target sample, a label is turned over, and an attack data set is formed; original training data are sampled, and a toll-snow information matrix of each layer is calculated; using the original model parameters to initialize the backdoor model, adding the L1 norm of the parameter disturbance difference value and the parameter difference constraint term based on the Feisnow information matrix into a loss function, and training the backdoor model; performance fluctuation caused by random sample selection is avoided through sample screening based on loss values, so that the backdoor model maintains the classification capability of clean samples while learning trigger features.

A transaction method and a transaction system based on a digital currency hardware wallet. The transaction method comprises: a mobile communication apparatus acquires capability information of a digital currency hardware wallet from same during interaction, and determines whether the digital currency hardware wallet has a payment receiving capability, a display capability and a network connectivity capability on the basis of the capability information; in response to the determination that the digital currency hardware wallet has the payment receiving capability and the display capability and does not have the network connectivity capability, the mobile communication apparatus sends digital currency transaction information to a background server for transaction processing; and in response to an echo command generated after the background server executes transaction processing on the basis of the digital currency transaction information, the mobile communication apparatus receives and sends the echo command to the digital currency hardware wallet, such that the digital currency hardware wallet updates and displays information comprising a transaction amount and a balance by means of the display capability of the digital currency hardware wallet according to the echo command. The transaction method provides a transaction mode using the digital currency hardware wallet as a payment receiving terminal.

The invention discloses an abnormal transaction identification method and device, equipment, a storage medium and a program product. Comprises: obtaining a sample set; performing hash processing on samples in the sample set and then sending the samples to a preset platform, so that the preset platform performs privacy intersection operation on hash values; receiving a privacy intersection result sent by the preset platform, and performing standardization processing on the samples in the sample set based on the privacy intersection result; performing split federation learning on the abnormal transaction model based on the standardized sample set to obtain a trained abnormal transaction model; and identifying the abnormal transaction based on the abnormal transaction model. According to the abnormal transaction identification method provided by the embodiment of the invention, the abnormal transaction is identified on the basis of the abnormal transaction model obtained by split federal learning, so that the accuracy of abnormal transaction identification can be improved, and the security of data can also be improved.

The invention provides a park integrated energy system optimization scheduling method considering green certificate carbon transaction, which comprises the steps of establishing an optimization scheduling model comprising a step green certificate transaction model, a step type carbon transaction model and a demand response model, establishing a master-slave game double-layer optimization model on the basis of the model, taking an energy operator as a leader, and taking the energy operator as the leader as a leader; and an energy supplier, an energy storage operator and a load aggregator serve as followers. And then, solving the established double-layer master-slave game model by adopting a differential evolution algorithm in combination with a Cplex solver. And finally, verifying the effectiveness of the model and the solving method by adopting example analysis. After a green certificate transaction mechanism, a stepped carbon transaction mechanism and demand response are introduced, the peak clipping and valley filling effect is obvious, reduction of electric, thermal and cold loads is realized in a reasonable range, an optimization result can form a reasonable energy purchase and sale price and supply and demand balance relationship, the carbon emission of the system is reduced, and the energy consumption of the system is reduced. The method is of great significance to energy conservation and emission reduction of a park comprehensive energy system and improvement of main body benefits.

The invention provides a payment fraud real-time identification and disposal method and system based on machine learning, and relates to the technical field of computers, and the method comprises the steps: constructing a transaction relation graph, recognizing an abnormal transaction mode through a graph attention network, and calculating a transaction suspicious degree score; and when the preset threshold value is exceeded, triggering a self-adaptive verification strategy based on the knowledge graph and reinforcement learning, executing a corresponding verification means and processing a transaction result. According to the invention, accurate identification and efficient disposal of fraudulent transactions can be realized, the payment security is improved, the error interception rate is reduced, and the user experience is optimized.

The invention provides an interconnected multi-energy micro-grid point-to-point energy transaction method and system considering energy transaction consistency, and relates to the technical field of energy transaction. The method comprises the following steps: constructing a system, and establishing system models including a point-to-point energy transaction model, an energy conversion equipment model and an energy storage equipment model; a system optimization target is determined, and a cost function is constructed according to the point-to-point energy transaction cost of the multi-energy micro-grid, the energy transaction cost of the external network and the environment cost; physical constraints are constructed, wherein the physical constraints comprise energy conversion constraints, energy storage constraints and energy balance constraints; modeling a complex optimization problem including a point-to-point energy transaction and energy conversion process as a partial objective Markov decision process, and introducing energy transaction consistency; and optimizing an energy transaction and conversion strategy of the interconnected multi-energy micro-grid by using an MASAC method. According to the invention, unreasonable energy transaction behaviors can be avoided, and the total operation cost of the system is reduced.

The application discloses a kind of multi-element load linkage regulation method, system, equipment and medium, comprising: constructing the two-stage operation transaction model of multi-element load aggregation main body user, forms lower user response model;Establish two-stage robust regulation model dominated by distribution network operator;Introduce power grid topology adjustable constraint;Coupling user response model and enhanced operator regulation model, build double-layer interactive optimization framework, form two-stage robust double-layer optimization problem containing integer variable;Optimization problem is solved using nested column constraint generation algorithm, output optimal electricity price guide strategy, direct load control amount and topology adjustment scheme, as the total scheme of multi-element load linkage regulation for weak point uncertainty.

The invention discloses a reconfigurable power distribution network end-to-end energy transaction method based on block chain on-chain and off-chain collaboration, relates to a block chain technology, and provides an on-chain and off-chain collaboration end-to-end energy transaction block chain architecture, in the architecture, representatives selected by producers and diasters jointly solve a transaction model, and the energy transaction efficiency is improved. Transparent and credible transaction results are ensured. The method comprises the following steps of: firstly, dividing a solution space of a transaction model into redundant sub-solution spaces on a chain by representatives, and distributing the sub-solution spaces; then, each representative searches an optimal solution in a sub-solution space of the representative under the chain, and submits the optimal solution to the block chain; and finally, performing cross communication on the representatives on the chain, comparing to obtain a global optimal solution of the P2P transaction model, and determining a final transaction result. And through on-chain-off-chain cooperation, a complex optimization task is transferred to offline, so that the calculation burden of the block chain is reduced.