TY - GEN
T1 - Insights into the health of defence simulated workforce systems using data farming and analytics
AU - Hill, Brendan
AU - Vukcevic, Damjan
AU - Caelli, Terrence
AU - Novak, Ana
N1 - Funding Information:
TERRENCE CAELLI is a Research Professor in Division of Engineering at the University of South Australia funded by the Defence Science and Technology Group at Port Melbourne, Victoria. Previous to this he has held a number of senior positions with National ICT Australias (NICTA) including Laboratory Director and Director of NICTA Health Program. His interests lie in Signal Processing, Human and Machine Perception, Cognitive Engineering, Machine Learning and their applications in Health, Environment and Defence. He is a Fellow of the International Association for Pattern Recognition (FIAPR) and a Fellow of the Institute for Electronic and Electrical Engineers (FIEEE). He is also a Convocation Medalist from the University of Newcastle. He has spent 15 years in North American universities and research institutes (Bell Laboratories and NASA Commercial Space Centre), has been a DFG Professor, Germany, Killam Professor of Science, the University of Alberta, Canada. He has served on the editorial boards of many international journals including IEEE: PAMI, Pattern Recognition and numerous international conference committees. His email address is [email protected].
Publisher Copyright:
© 2019 IEEE.
PY - 2019
Y1 - 2019
N2 - This work is motivated by the need for the Australian Defence Force to produce the right number of trained aircrew in the right place at the right time. It is critical to understand the impact of structural/resourcing policies on the ability to maintain squadron capability, both for individual squadrons and jointly across the Force. By combining techniques in experimental design, simulation, data analysis and optimization, we have created an automated system to efficiently identify significant relationships between simulation parameters and squadron capability, as well as propose optimal parameter ranges for each individual squadron. The interplay of competing demands between squadrons was then analysed in the context of the entire Force and the stability of these extrapolations over sampling noise was also evaluated. Finally, we present compact summaries and visualisations of the most important insights about the most significant contributors to the health of the whole system.
AB - This work is motivated by the need for the Australian Defence Force to produce the right number of trained aircrew in the right place at the right time. It is critical to understand the impact of structural/resourcing policies on the ability to maintain squadron capability, both for individual squadrons and jointly across the Force. By combining techniques in experimental design, simulation, data analysis and optimization, we have created an automated system to efficiently identify significant relationships between simulation parameters and squadron capability, as well as propose optimal parameter ranges for each individual squadron. The interplay of competing demands between squadrons was then analysed in the context of the entire Force and the stability of these extrapolations over sampling noise was also evaluated. Finally, we present compact summaries and visualisations of the most important insights about the most significant contributors to the health of the whole system.
UR - http://www.scopus.com/inward/record.url?scp=85081134857&partnerID=8YFLogxK
U2 - 10.1109/WSC40007.2019.9004849
DO - 10.1109/WSC40007.2019.9004849
M3 - Conference Paper
AN - SCOPUS:85081134857
SP - 2491
EP - 2502
BT - Proceedings of 2019 Winter Simulation Conference (WSC)
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - USA
T2 - Winter Simulation Conference 2019
Y2 - 8 December 2019 through 11 December 2019
ER -