1. A prediction method for monitoring performance of power plant instruments comprising: displaying entire data in a matrix; normalizing the entire data into a data set; trisecting the normalized data set into three data sets, wherein the three data sets comprising a training data set, a optimization data set, and a test data set; extracting a principal component of each of the normalized training data set, the optimization data set, and the test data set; calculating an optimal constant of a Support Vector Regression (SVR) model to optimize prediction value errors of data for optimization using a response surface method; generating the Support Vector Regression (SVR) training model using the optimal constant; obtaining a Kernel function matrix using the normalized test data set as an input and predicting an output value of the support vector regression model; and de-normalizing the output value into an original range to obtain a predicted value of a variable.