APRIS: Library and On-Line Tools to Drive Parallel Adaptive and Neural Heuristic to Improve System Identification Precision

Abstract

In this paper are shown the methodologies and tools developed to increase the accuracy of the system identification as method of modelization, simulation and prediction of the behaviour of dynamic systems, so much of the type single-input-single-output as the well known time series. These developments are mainly based on an adaptive parallel algorithm. The adaptive part consists of the evolution of its main parameter through the time, so it self-adjusts to offer good solutions. The parallel part consists of the implementation of processing units of parallel running. The codes have been programmed in Matlab language, organizing themselves in a free and public domain library, which is handled by a set of graphic tools through Web services for its on-line control and experimentation