Patent Document ID: 9111212
Application ID: 13772212
Patent Flag: 1

Claim One:
1. A system for reducing outlier bias in target variables measured for a facility, comprising: an input unit for inputting one or more data sets to be processed, wherein the input unit comprises a measuring device configured to: measure one or more target variables for the facility; and provide a corresponding data set for each of the target variables; a computing unit coupled to the input unit and for processing the data sets, wherein the computing unit comprises a processor and a storage subsystem; and an output unit coupled to the computing unit and for outputting one or more of the processed data sets received from the computing unit, wherein a computer program stored by the storage subsystem comprises instructions that, when executed reduces outlier bias for one of the processed data sets by causing the processor to: select one of the target variables for the reduction of outlier bias; obtain a complete data set of the one of the target variables from the input unit, wherein the complete data set of the one of the target variables comprises a plurality of inputted data values; obtain a bias criteria used to determine one or more outliers; determine a set of model coefficients for a mathematical model; (1) apply the mathematical model with the set of model coefficients to the complete data set to determine a set of model predicted values; (2) generate an error set by comparing the set of model predicted values to corresponding actual values of the complete data set; (3) generate a set of error threshold values from the error set and the bias criteria; (4) generate a removed data set comprising elements of the complete data set with corresponding error set values outside the set of error threshold values; (5) generate a censored data set comprising all elements of the complete data set that are not within the removed data set; (6) determine a set of updated model coefficients for the mathematical model based on the censored data set; and (7) repeat steps (1)-(6) as an iteration unless a censoring performance termination criteria is satisfied, whereby at the iteration the set of predicted values, the error set, the set of error threshold values, the removed data set, and the censored data set are generated using the set of updated model coefficients.