Instantaneous Modelling and Reverse Engineering of DataConsistent Prime Models in Seconds!

TL;DR

This paper introduces a rapid, automated framework for constructing data-driven dynamic models of complex systems from experimental time series data, enabling instant reverse engineering and network inference.

Contribution

The paper presents a novel, robust mathematical and computational method for instantaneously building data-consistent prime models from small datasets, advancing system identification techniques.

Findings

Models constructed in less than a minute

Effective reverse engineering of complex systems

Robust approach for small data scenarios

Abstract

A theoretical framework that supports automated construction of dynamic prime models purely from experimental time series data has been invented and developed, which can automatically generate (construct) data-driven models of any time series data in seconds. This has resulted in the formulation and formalisation of new reverse engineering and dynamic methods for automated systems modelling of complex systems, including complex biological, financial, control, and artificial neural network systems. The systems/model theory behind the invention has been formalised as a new, effective and robust system identification strategy complementary to process-based modelling. The proposed dynamic modelling and network inference solutions often involve tackling extremely difficult parameter estimation challenges, inferring unknown underlying network structures, and unsupervised formulation and construction of smart and intelligent ODE models of complex systems. In underdetermined conditions, i.e., cases of dealing with how best to instantaneously and rapidly construct data-consistent prime models of unknown (or well-studied) complex system from small-sized time series data, inference of unknown underlying network of interaction is more challenging. This article reports a robust step-by-step mathematical and computational analysis of the entire prime model construction process that determines a model from data in less than a minute.