Patent ID: 8781979
Filing Date: 2014-07-15
Classification: G06K,G06N

Abstract:
1. A prediction method for monitoring performance of power plant instruments, comprising: displaying measurement data in a matrix; normalizing the measurement data into a normalized measurement data set; trisecting the normalized measurement data set into three data sets, wherein the three trisected data sets comprising a normalized training data set, a normalized optimization data set, and a normalized test data set; extracting principal components of each of the three trisected data sets; calculating an optimal constant of a Support Vector Regression (SVR) model, based on the normalized measurement data set and the extracted principal components thereof, to optimize prediction value errors of data for optimization with a response surface method; generating the SVR training model with the optimal constant; obtaining a Kernel function matrix with the normalized test data set as an input and predicting an output value of the SVR training model; and de-normalizing the output value into an original range to obtain a predicted value of a variable, wherein the displaying of the measurement data in the matrix is represented by the following equation: where: