3 results about "Calculation error" patented technology

To provide functional system and method for data filtering for reducing outlier bias of a trend line.SOLUTION: The present invention is directed to an objective, statistic method of eliminating an outlier from a data set. The method has the steps of determining a bias based on an absolute error, a relative error or both of them, calculating an error value from calculation of data, model coefficients or trend lines, and eliminating an outlier data record if the error value exceeds a reference set by a user. For the purpose of a repeated calculation such as an optimization method, the eliminated data is re-applied to the model for use in calculation of a new result upon each repeated calculation. With use of a model value for a completed data set, a new error value is calculated, and an outlier bias reduction process is re-applied to minimize the total error for the model coefficient and the outlier eliminated data repeated until the value reaches a user definition error improvement limit. Filtered data is used for the purpose of authentication, the outlier bias reduction, and data quality operation.SELECTED DRAWING: Figure 1

The application belongs to the technical field of sub-seasonal prediction, and discloses a sub-seasonal prediction bias correction method, system, device and medium based on Swin Transformer, to solve the problem of large prediction bias. The method comprises: obtaining sub-seasonal historical prediction data as to-be-corrected training data, and ERA5 reanalysis data and ground observation data as true value reference data, and performing pretreatment; constructing a correction model by combining an autoregressive Swin Transformer network with a sliding time window, inputting the to-be-corrected training data of a preset time length in the past, and predicting the bias field of a preset time length in the future; adopting a point-to-point residual correction form to output the corrected meteorological element field; comparing the corrected meteorological element field with the true value reference data, calculating the error by a composite loss function, and optimizing the network weight by back propagation, to obtain an optimized correction model; and inputting the sub-seasonal future prediction data into the model, and outputting the corrected meteorological element field.