Modeling pH Neutralization Process Via Support Vector Machines

Abstract

AbstractThis paper discusses the use of support vector machines for modeling and identification of pH neutralization process. Support vector machines (SVM) and kernel method have become very popular as methods for learning from examples. We apply SVM to model pH process which has strong nonlinearities. The experimental results show that the SVM based on the kernel substitution including linear and radial basis function kernel provides a promising alternative to model strong nonlinearities of the pH neutralization but also to control the system. Comparisons with other modeling methods show that the SVM method offers encouraging advantages and has better performance.KeywordsSupport Vector MachineMean Square ErrorKernel FunctionContinuously Stir Tank ReactorRadial Basis Function KernelThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.