Data organization form representing cash flow and prediction method based on multi-task learning

A multi-task learning and data organization technology, applied in the field of data organization form representing cash flow, it can solve the problems of lack of data information, not yet seen neural network, ignoring the overall correlation nature, etc., to achieve robust results and reduce generalization errors. , the effect of less manual intervention
CN110264251BActive Publication Date: 2021-08-10杭州博钊科技有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
杭州博钊科技有限公司
Publication Date
2021-08-10

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Abstract

The invention relates to big data processing technology, and aims to provide a data organization form representing cash flow and a prediction method based on multi-task learning. Including: information mining and statistical analysis of historical data of sales flow and electricity consumption in the power sector; establishment of multiple tasks related to regression analysis, establishment of multi-dimensional data labels; cross-validation according to time series, using deep convolutional neural network or The recurrent neural network performs multi-task learning and performs performance testing on the model; the optimal hyperparameters of the neural network are obtained by using the grid method, and finally the configuration of the neural network model is determined, and the neural network model is used to predict the amount of electricity sales. The invention constructs a new data organization form combining these information, which can describe the source of daily cash flow. Compared with the traditional statistical model, the multi-task learning constructed by the present invention requires less manual intervention, and the result is more robust and more adaptable to big data.
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Description

technical field

[0001] The invention relates to big data processing, in particular to a data organization form representing cash flow and a prediction method based on multi-task learning. Background technique

[0002] Sales amount forecast refers to the estimation of the sales quantity and sales amount of all products or specific products within a certain period of time in the future. Sales forecasting aims to put forward feasible sales targets through certain analysis methods on the basis of fully considering various influencing factors in the future, and to help enterprises make financial budgets. The results are of great significance to the development planning and strategic deployment of enterprises .

[0003] Still, producing high-quality consumption forecasts is no easy task. The data mining tools currently available for cash flow forecasting are mainly some statistical analysis methods, such as time series analysis, linear / nonlinear regression model, gray system mod...

Claims

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