12 results about "Price fluctuation" patented technology

The invention discloses a price trend prediction method for bulk commodities whose prices are in an oscillation environment for a long time, and relates to the technical field of data analysis, and the method comprises the steps: obtaining historical data; based on the historical data, constructing a time sequence prediction model of a multi-dimensional time dimension and a machine learning prediction model, obtaining a corresponding time sequence prediction result through the time sequence prediction model of the multi-dimensional time dimension, and obtaining a machine learning prediction result through the machine learning prediction model; and taking the minimum variance of the prediction result as an optimization target, obtaining corresponding weight parameters of the time sequence prediction model and the machine learning prediction model of the multi-dimensional time dimension by applying a constraint optimization algorithm, and combining all prediction results based on the corresponding weight parameters to form a target prediction price. According to the method, multiple prediction models are creatively fused, analysis support is provided for final price trend prediction from multiple dimensions, and the model accuracy is greatly improved.

The invention belongs to a price determination method, and provides a method for determining upper and lower limits of contract price fluctuation of a power market and a related device, aiming at the technical problems that a price limit mechanism for setting fixed upper and lower limits of prices is adopted in the current power transaction, a price discovery suppression function exists, and violent price swing within a day cannot be effectively coped with. Calculating a positive excess sample and / or a negative excess sample, then taking the positive excess sample and / or the negative excess sample as input, and obtaining a morphological parameter and a scale parameter when a log-likelihood value of the positive excess sample and / or a log-likelihood value of the negative excess sample converges through generalized Pareto distribution iterative calculation; and finally, positive tail risk measurement index expected loss and / or negative tail risk measurement index expected loss are / is obtained through calculation and serve as an upper limit and a lower limit of contract price fluctuation of the electricity market. And the technical problem of violent price swing within the day can be effectively solved.

An object of a system according to an embodiment is to predict price fluctuations of raw materials in real time and provide the predicted price fluctuations to consumers and companies.SOLUTION: A system includes a price data collection part, a price fluctuation analysis part, a prediction part, and a provision part. The price data collection unit collects price data of various raw materials. The price fluctuation analysis unit analyzes the price data collected by the price data collection unit. The prediction unit predicts the price fluctuation based on the data analyzed by the price fluctuation analysis unit. The providing unit provides the price change information predicted by the prediction unit to the consumer and the company.SELECTED DRAWING: Figure 1

The invention provides an anchor point selection method and system for asset price prediction. The method comprises the following steps: receiving historical price data of target assets and candidate assets in a predetermined period; determining the correlation between the candidate assets and the target assets based on the historical price data of the target assets and the candidate assets; determining the sensitivity of the target asset to the price fluctuation of the candidate assets for the determined candidate assets with high correlation; and taking the determined candidate assets with high sensitivity as anchor assets, so as to predict the asset price of the target asset based on the anchor assets.

The system according to this embodiment aims to maximize sales and profits by responding to fluctuations in demand and price changes by competitors. [Solution] The system according to the embodiment comprises a data collection unit, an analysis unit, a pricing unit, a monitoring unit, and an adjustment unit. The data collection unit collects sales data, competitor data, and market trends. The analysis unit analyzes the data collected by the data collection unit. The pricing unit sets prices based on the analysis results obtained by the analysis unit. The monitoring unit adjusts the prices set by the pricing unit in accordance with price fluctuations of competitors. The adjustment unit further adjusts the prices adjusted by the monitoring unit based on market seasonality and trends.

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

Provided is a technique that is useful for predicting a price fluctuation in an investment brand.　This information processing method includes: a step for reading past price data pertaining to an investment brand according to a plurality of prediction indexes including a technical index or a chart pattern for predicting a price fluctuation in the investment brand; a determination step for determining, with respect to one or more prediction indexes for which the prediction of the price fluctuation has proven to be correct, whether the prediction satisfies a signal accuracy rate; and a step for selecting the prediction index satisfying the signal accuracy rate as an effective prediction index. The signal accuracy rate is an index indicating the relationship between the number of occurrences of a trading signal for each prediction index and the number of occurrences of proven-correct prediction in which a price fluctuation predicted by the trading signal has occurred.

The invention provides an individual share popularity transaction sorting display method and system based on a fluctuation range and a change rate, and relates to the technical field of individual share popularity transaction sorting display. An initial optical image containing fluctuation range and change rate data in a data display interface is collected in real time through an optical image collection device; and a final optical image is obtained after noise reduction. Performing Laplacian operator operation on the data to obtain a definition analysis result, and taking an area of which the definition exceeds a preset threshold value as an effective data area; converting the image signal of the area into an initial electric signal, and obtaining a target electric signal through adaptive filtering interference suppression and signal amplification; analyzing real-time individual stock data, matching the real-time individual stock data with a preset popularity evaluation data set to obtain scores, and sorting to obtain a preliminary result; and a final result is generated through stability verification and is displayed by using a dynamic rendering technology, so that accurate sorting and dynamic display of individual share popularity transactions can be realized through image acquisition processing, signal optimization, data matching scoring and sorting verification, and data processing reliability and display intuition are guaranteed.

The embodiment of the invention provides a method and device for generating MIDI music based on a stock K line. The method comprises the steps that a convolution model of a closing price sequence is constructed to solve a reference pitch sequence, note strength is generated in combination with price fluctuation characteristics, a playing time sequence is determined through Fourier spectrum analysis, and finally music works with market characteristic expression ability are synthesized. According to the method and the device for generating the MIDI music based on the stock K line disclosed by the embodiment of the invention, multi-dimensional mapping from financial data to music parameters is realized, so that the generated melody has higher music performance, better conforms to natural music rhythm and has more dynamic expressive force.

The invention provides a performance project management method and device, and relates to the technical field of venue operation management and data processing, and the method comprises the steps: obtaining a target performance schedule of a target venue in a target time period, and the target performance schedule is determined by a time sequence extraction model, a feature extraction model and a genetic algorithm based on multi-modal performance historical data; n price elastic coefficients are determined based on the multi-modal performance historical data, the N price elastic coefficients are in one-to-one correspondence with N performance types, and the price elastic coefficients represent demand fluctuations corresponding to price fluctuations of the performance types; and inputting the target performance schedule and the N price elasticity coefficients into a particle swarm algorithm, and generating a target performance ticket price corresponding to each performance in the target performance schedule by the particle swarm algorithm by taking the maximum net income of a target venue in the target time period as a target.

We provide the system. [Solution] Information gathering means for acquiring energy consumption information, An anomaly detection means that analyzes consumption patterns based on acquired information and detects abnormalities, A pricing plan optimization method that proposes the most suitable pricing plan to the user, A price fluctuation prediction method that predicts future price fluctuations based on market price information, A user terminal that displays the user's energy consumption status in real time and notifies them when an anomaly occurs, A system that includes this.

The invention discloses a bulk commodity price fluctuation prediction system and method based on multi-source heterogeneous data fusion, and belongs to the technical field of data analysis and prediction, and the system comprises a multi-source data collection module which is used for collecting related data corresponding to a target commodity, the related data comprises unstructured data, related information is obtained from the unstructured data, and the unstructured data is stored in a database; the related information comprises the transaction information and the transaction party associated with the transaction information. According to the method, multi-source heterogeneous data is comprehensively collected, the influence range of transaction information is finely distinguished, key features such as inventory, production planning and sales plans of a transaction party are deeply extracted, and data fusion and dynamic prediction analysis are combined, so that the accuracy, timeliness and practicability of price fluctuation prediction of bulk commodities are improved, and the method is suitable for popularization and application. Therefore, decision making of enterprises is effectively supported, market adaptability is enhanced, and market risks are reduced.