5 results about "Demand estimation" patented technology

In an aspect, input data can be received, including at least time series data associated with purchases of at least one product and causal influencer data associated with the purchases. The causal influencer data can include at least non-stationary data, where lost shares associated with said at least one product are unobserved. An artificial neural network can be trained based on the received input data to predict a future global demand associated with at least one product and individual market shares associated with at least one product. The artificial neural network can include at least a first temporal network to predict the global demand and a second temporal network to predict each of the individual market shares. The first temporal network and the second temporal network can be trained simultaneously.

The invention discloses a charging demand-oriented city charging facility constant volume planning visualization system, which comprises a demand prediction module, which combines the market sales volume, vehicle performance parameters and regional driving characteristics of all electric vehicle types, and constructs an electric quantity demand estimation model in a vehicle type, version, region and season division mode; obtaining a predicted charging demand; a capacity optimization configuration module introduces a multi-objective optimization framework to construct a charging facility constant volume planning model on the basis of the predicted charging demand, and realizes optimization configuration under the condition of satisfying multiple constraints; and the display module constructs an interactive visual interface, and displays an output result of the charging facility constant volume planning model and auxiliary decision analysis. According to the invention, through key technologies such as multi-source data fusion, demand modeling and dynamic simulation, accurate planning and optimal configuration of the capacity of the charging facility are realized. Meanwhile, a three-dimensional visualization function is integrated to visually display a planning result, and the understanding and decision-making efficiency of the scheme is improved.

A configuration mapping system and method increase the effectiveness of mapping of information from an established product line to a new product offering. In at least one embodiment, the configuration mapping system herein uses configuration mapping rules to map individual product features and entire configurations from established products to a new product offering. The configuration mapping system also provides a way to appropriately map, for example, demand and sales information for the purpose of demand estimation and sales prediction. Conventionally, mapping can be ineffective because the configuration mapping rules usually focus on one part of the product at a time, and, if applied in isolation, the impact on other parts is missed. The systems and method herein provide a way to integrate configuration mapping rules across feature parts, time periods, and product lines into a unified, holistic view, allowing for new insights.

The present invention relates to a virtual power plant to which an optimal price determination and contract renewal system based on digital twin modeling and artificial intelligence is applied. More specifically, the invention comprises: an optimal price determination system including a power generation estimation module that estimates the power generation amount of a power source per reference period, a power demand estimation module that estimates the power consumption amount of a power demander, and a price determination module that derives an optimal price by reinforcement-learned artificial intelligence based on power generation and power consumption data estimated from the power generation estimation module and the power demand estimation module, respectively; a power source management module that manages data on real-time energy transactions and history of power sources and calculates a parameter value that compensates for the difference between the price determined by the optimal price determination system and the actual transaction price, and outputs it to the power generation estimation module; a demand source management module that manages data on real-time energy transactions and history of power demanders and calculates a parameter value that compensates for the difference between the price determined by the optimal price determination system and the actual transaction price, and outputs it to the power demand estimation module; and a monitoring module that manages the optimal price determination system, monitors real-time power transactions, and manages their history. A cloud data server module that processes and manages all data regarding power trading input / output from the above monitoring module and provides it to the user;A contract renewal system comprising: a supply-side digital twin modeling module that generates multiple supply-side contract renewal digital twin modules by modeling supply-side contract renewal conditions based on supply-side power supply history data for the entire contract period and maximum / minimum range data calculated therefrom from the cloud data server module; a demand-side digital twin modeling module that generates multiple demand-side contract renewal digital twin modules by modeling demand-side contract renewal conditions based on demand-side power demand or consumption history data for the entire contract period and maximum / minimum range data calculated therefrom from the cloud data server module; and a contract renewal module that combines multiple supply-side contract renewal digital twin modules and demand-side contract renewal digital twin modules to calculate and output contract matching condition ranges by artificial intelligence for each, wherein the power generation estimation module includes multiple supply-side digital twin models that model supply quantities for price based on data regarding estimated power supply and maximum / minimum range data calculated therefrom, and the power demand estimation module includes multiple demand quantities that model demand quantities for price based on data regarding estimated power demand and maximum / minimum range data calculated therefrom The present invention relates to a virtual power plant to which a system for optimal price determination and contract renewal by digital twin modeling and artificial intelligence is applied, wherein the system includes a demand-side digital twin model, and the price determination module determines an optimal price range by artificial intelligence from multiple prices determined by matching the supply and demand quantities for each price derived from multiple supply-side digital twin models and multiple demand-side digital twin models.

Aspects of the current subject matter are directed to privacy-preserving demand estimation. According to an aspect, a method includes receiving, by a first party, a request to provide a projection; receiving, by the first party, a key; in response to the request, performing, by the first party, a partial projection using private data of the first party without sharing the private data with at least one other party; encrypting, by the first party, the partial projection using the key; sending, by the first party, the encrypted partial projection to an aggregator; combining, by the aggregator; the encrypted partial projection provided by the first party with at least one other encrypted partial projection provided by the at least one other party to generate an encrypted combined projection. Related systems, methods, and articles of manufacture are also disclosed.