Output details
12 - Aeronautical, Mechanical, Chemical and Manufacturing Engineering
Cranfield University
A new adaptive fast cellular automaton neighborhood detection and rule identification algorithm
Supported by EPSRC Platform Grant (EP/H00453X/1 £1.2M 2010-2015), this paper introduces a novel algorithm that significantly reduces computational complexity for Cellular Automaton modelling meanwhile prevents ill conditioning and over fitting. This algorithm has been applied to Irritable Bowel Syndrome data analysis in collaboration with Dr BM Corfe (Department of Surgical Oncology, University of Sheffield, email: b.m.corfe@shef.ac.uk), based on which a research grant proposal has been submitted to Yorkshire Cancer Research (£80,278). It has also facilitated the research of the EPSRC grant titled “Spatio-Temporal Systems Estimation, Modelling and Analysis” (EP/G042209/1, £480K 01/2010-06/2013).