10 results about "Potential market" patented technology

A government official document fair competition review method and system based on causal inference relates to the technical field of data processing, and comprises the following steps: policy text analysis and causal element extraction, causal graph construction, causal effect estimation, anti-fact simulation and index evaluation, and review conclusion generation. According to the fair competition examination method and system for the government official documents, through a method of combining natural language processing, a causal graph model, quantitative effect estimation and anti-fact simulation, automatic, quantitative and explainable intelligent examination on the fair competition risk of the government official documents is realized, and the potential market effect of policy modification can be predicted.

The invention relates to the technical field of power supply and demand prediction, and discloses a power supply and demand prediction method suitable for a complex market environment. The method comprises the following steps: collecting multi-dimensional real-time data of a power market, wherein the multi-dimensional real-time data covers a user-side load fluctuation sequence and a market electricity price fluctuation signal; constructing a power supply and demand dynamic prediction model based on the data, and outputting a theoretical supply and demand prediction value; comparing the theoretical predicted value with the actual measurement electric power data, carrying out multi-dimensional difference analysis containing load sequence deviation response delay, and generating a market-level difference coefficient matrix; inputting the matrix into a regional energy network analysis model, generating a supply and demand abnormal propagation path probability distribution diagram and positioning a potential market imbalance region in combination with power grid node transmission capability and economic main body distribution information; and a prediction adjustment strategy is adaptively configured according to the probability distribution diagram, high-frequency data monitoring is started for a high-probability imbalance area, policy disturbance testing is applied to an associated market subject, and stable operation of the power market is supported.

The present disclosure provides a system for quantifying drivers of growth of niche categories. The system includes a data collection module configured to receive consumer data collected using surveys, an analysis module configured to identify consumer segments using factor analysis of the received consumer data, a market size estimation module configured to estimate market size for each identified consumer segment based on current consumption, a demographic categorization module configured to create sub-groups based on demographics, a growth potential determination module configured to determine growth potential by regressing consumption behavior on the identified consumer segments and consumer demographics using multinomial regression, and a market size prediction module configured to predict potential market size based on model weights and predicted probability of switching between consumer classes.

The invention relates to an electricity market transaction optimization decision-making system for micro-grid assets, and belongs to the technical field of electricity market transaction and financial risk management. The system obtains risk event signals such as market electricity price, plan power, financial data and extreme weather in real time; the risk quantification module constructs a risk factor reflecting the comprehensive financial risk level based on the quantified potential market opportunity income and the plan deviation penalty cost; the strategy decision and weight generation module dynamically generates weight coefficients of income and deviation penalty through a nonlinear mapping function according to the financial risk, and constructs a real-time optimization objective function with income maximization as an objective after risk adjustment. Finally, the system solves the function to determine an optimal transaction decision. According to the invention, the complex market financial risk is quantified as a dynamic decision basis, so that the transaction strategy can be adaptively adjusted between financial loss avoidance and arbitrage opportunity chasing.

The invention provides a multi-subject bidding behavior simulation method and device based on non-independent opponent modeling. The method comprises the following steps: loading a pre-constructed fitting function in an SOM-based multi-subject market framework; for each market subject of the electricity market, when the market subject makes each round of decision, a fitting function speculation mode is started to infer action probability distribution of other market subjects and estimate a potential market clearing result; starting an action mode of a fitting function to determine the quotation quantity of the market subject according to the potential market clearing result; and calculating a real market clearing result by using a preset electricity market clearing mechanism and the quantity report quoted price of all the market subjects. According to the scheme, possible bidding of multiple opponents is taken into consideration in the strategy of the market subject, and electricity market transaction is simulated from bottom to top under behavior driving, so that a more competitive quotation strategy is obtained.

The invention discloses a data prediction and joint training method and a related device, and relates to the field of artificial intelligence, and the method comprises the steps: carrying out the preprocessing of obtained first financial time series data, and obtaining second financial time series data meeting a model processing requirement; and inputting the second financial time series data and the random noise data into the first artificial intelligence model to carry out data prediction processing so as to obtain market scene data conforming to the change rule of the second financial time series data. And inputting the market scene data into a second artificial intelligence model for transaction decision processing to obtain a transaction decision result under the market scene data. Modeling prediction is carried out on financial time series data to obtain data which can better reflect potential market scenes, so that the diversity and representativeness of the data are enhanced. And on the basis, the generated data is analyzed through an artificial intelligence model with a decision making function, a transaction strategy is formulated, strategy optimization and stability improvement are realized, and the reliability of a prediction result is improved.

The present application relates to the technical field of operation and maintenance. Provided are a machine-learning-based operation and maintenance method and system. The method specifically comprises: collecting historical order data; establishing a customer relationship-machine learning model to predict the potential market value of processing orders for quartz devices; performing high-dimensional clustering analysis on the potential market value of the processing orders for quartz devices; calculating and acquiring the customer stability of relevant customers for different processing orders for quartz devices, and grading enterprise customers on the basis of the customer stability; and executing differentiated operation and maintenance services and personalized marketing plans. The present application solves the problem in the prior art of quartz processing plants suffering from poor enterprise customer stability and lacking personalized services due to the absence of different customized products for different customers.

The invention discloses an international market public opinion analysis and business opportunity mining system based on deep learning, and relates to the technical field of cross-language emotion calculation, causal reasoning and anomaly detection. The system comprises a multi-source public opinion data acquisition module, a cross-cultural emotion recognition module, a causal graph neural network analysis module, an emotion anti-fact simulation module, a cross-context nested causal chain business opportunity discovery module, an abnormal emotion group detection module, a causal graph generation type learning engine and a business opportunity early warning output module. Through cooperative work of all the modules, the system can automatically identify hidden causal relationship chains from public opinion data of different languages in the world, predict potential market influences in advance, discover commercial opportunities such as supply gaps and sudden demand increase, and give an early warning for abnormal public opinions. According to the system provided by the invention, the depth and accuracy of international market public opinion analysis are remarkably improved, and interpretable business opinion intelligence and decision suggestions can be provided in time.

The application is a kind of micro-grid asset power market transaction optimization decision system, belonging to the technical field of power market transaction and financial risk management;The system obtains market electricity price, planned power, financial data and extreme weather risk event signals in real time;The risk quantification module quantifies potential market opportunity income and planned deviation penalty cost based on this, and constructs a risk factor reflecting the comprehensive financial risk level;The strategy decision and weight generation module dynamically generates the weight coefficients of income and deviation penalty through a nonlinear mapping function according to the financial risk, and constructs a real-time optimization objective function with the goal of maximizing risk-adjusted income. Finally, the system solves the function to determine the optimal transaction decision;The application quantifies complex market financial risks into dynamic decision-making basis, enabling the transaction strategy to adaptively adjust between avoiding financial losses and pursuing arbitrage opportunities.

The invention relates to the technical field of electricity transaction management, in particular to an electricity transaction retail package optimization method and system, and the method comprises the steps: constructing an electricity selling company cost measurement and calculation model to calculate a monthly cost measurement and calculation price, and setting the monthly cost measurement and calculation price as a package pricing cost base line; establishing an objective function of package optimization by taking the revenue maximization of the electricity selling company as an objective, and forming an initial optimization model; a compliance package optimization model is formed by loading preset package constraint conditions; solving the compliance package optimization model by adopting an intelligent optimization algorithm, ensuring that the solved package price is higher than the cost base line, and outputting an optimal package solution; the optimal package solution comprises a scheme for dividing peak, flat and valley time periods of all moments generated every month, and electricity prices which correspond to all the time periods and conform to the package price multiple rule. The problems that an existing package mode is low in efficiency, low in customer satisfaction and unstable in income, and market contradictions are likely to be caused are solved.