Data prediction method and device
A data prediction and data technology, applied in the computer field, can solve the problem of low accuracy of annual power load and achieve the effect of improving accuracy
Active Publication Date: 2022-01-11
HUAWEI TECH CO LTD +1
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[0005] This application provides a data forecasting method and device, which are used to solve the technical problem of low accuracy of forecasted annual electric load in the prior art
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[0072] The present application provides a data forecasting method, which can be used to forecast annual electric load, and aims to solve the technical problem of low accuracy of forecasted annual electric load in the prior art. Of course, the data prediction method provided by this application includes but is not limited to the above application scenarios. For example, the data prediction method provided by this application can also be applied to any data mining scenario, so that through the analysis of historical data and current data, Help decision-makers extract potential relationships and patterns hidden in data, and then assist them in predicting possible future conditions and upcoming results. Wherein, the aforementioned scenario of data mining may be, for example, data mining in financial industry, retail industry, medical care, telecommunications, electric power and other fields.
[0073] Taking the forecasted annual electric load as an example, the technical solution ...
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The present application provides a data prediction method and device, the method comprising: obtaining sample data; the sample data includes historical data of N different periods; according to the sample data, using the simulated annealing quantum particle swarm optimization algorithm SAQPSO to calculate the optimal control parameter value and The optimal penalty parameter value; SAQPSO determines whether to update the control parameter value and penalty parameter value corresponding to the particle in the next iteration cycle in SAQPSO according to the random number of the current iteration cycle and the annealing temperature of the current iteration cycle; the optimal control parameter value and the maximum The best penalty parameter value is the control parameter value and penalty parameter value used by the support vector machine SVM model with the smallest prediction error; input the best control parameter value and the best penalty parameter value into the SVM model to obtain the optimized SVM model; according to the sample Data, use the optimized SVM model to calculate the forecast data. The present application can improve the accuracy of the forecasted annual electric load.
Description
technical field [0001] The present application relates to computer technology, and in particular to a data prediction method and device. Background technique [0002] Power load forecasting is to predict future power load through historical power load data. Power load forecasting is the main basis for formulating power generation plans and transmission schemes, and is of great significance for rationally arranging unit startup and shutdown, determining fuel supply plans, and conducting energy transactions. Due to the strong mutation of the power system and the inconvenient storage of electric energy, the power generation of the power system must closely follow the change of the system load to maintain a dynamic balance. Therefore, the accuracy of power load forecasting directly affects the safety, economy and power supply quality of power system operation. [0003] At present, the electricity load forecasting mainly forecasts the annual electricity load. That is, the tota...
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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 温世平任光华薛希俊
Owner HUAWEI TECH CO LTD