Temporal meta-optimiser based sensitivity analysis (TMSA) for agent-based models and applications in children’s services

White, Luke and Basurra, Shadi and Alsewari, AbdulRahman and Saeed, Faisal and Addanki, Sudhamshu Mohan (2024) Temporal meta-optimiser based sensitivity analysis (TMSA) for agent-based models and applications in children’s services. Scientific Reports, 14 (1). ISSN 2045-2322

[img]
Preview
Text
s41598-024-59743-8.pdf - Published Version
Available under License Creative Commons Attribution.

Download (3MB)

Abstract

With current and predicted economic pressures within English Children’s Services in the UK, there is a growing discourse around the development of methods of analysis using existing data to make more effective interventions and policy decisions. Agent-Based modelling shows promise in aiding in this, with limitations that require novel methods to overcome. This can include challenges in managing model complexity, transparency, and validation; which may deter analysts from implementing such Agent-Based simulations. Children’s Services specifically can gain from the expansion of modelling techniques available to them. Sensitivity analysis is a common step when analysing models that currently has methods with limitations regarding Agent-Based Models. This paper outlines an improved method of conducting Sensitivity Analysis to enable better utilisation of Agent-Based models (ABMs) within Children’s Services. By using machine learning based regression in conjunction with the Nomadic Peoples Optimiser (NPO) a method of conducting sensitivity analysis tailored for ABMs is achieved. This paper demonstrates the effectiveness of the approach by drawing comparisons with common existing methods of sensitivity analysis, followed by a demonstration of an improved ABM design in the target use case.

Item Type: Article
Identification Number: https://doi.org/10.1038/s41598-024-59743-8
Dates:
DateEvent
15 April 2024Accepted
20 April 2024Published Online
Uncontrolled Keywords: Computational science, Computer science, Mathematics and computing, Software
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Gemma Tonks
Date Deposited: 10 May 2024 13:45
Last Modified: 10 May 2024 13:45
URI: https://www.open-access.bcu.ac.uk/id/eprint/15488

Actions (login required)

View Item View Item

Research

In this section...