Electric-Parameter-Based Inversion of Dynamometer Card Using Hybrid Modeling for Beam Pumping System

Algorithm 2

IFS-DDKOS-ELM.

Input: Training samples , the Gaussian kernel function is selected as the basic

kernel function , the nonzero constant , the number of hidden nodes and

the number of data blocks in a data set.

Output: The predictive value of the polished rod load and suspension point displacement

Randomly generate the input layer parameters ;

Construct the data-dependent kernel function by modifying the initial basic kernel function according

to (29), whose parameters are optimized by Algorithm 1;

  for each   do

  Update the output weight by (27);

  end for

Compute the predictive value according to (20).