Author Index

* Please note this includes full papers only

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

A

• Aarao, J.
  • A strategy for using cooperating missiles for missile defence
    

    Kapsis, M., Pudney, P., Aarao, J., Miller, W. and Freebairn, G.
    https://doi.org/10.36334/modsim.2021.M7.kapsis

• Abolghasemi, M.
  • Forecasting sales with Bayesian networks: a case study of a supermarket product in the presence of promotions
    

    Hamza, M., Abolghasemi, M. and Alvandi, A.O.
    https://doi.org/10.36334/modsim.2021.M9.hamza

• Abril, D.
  • The Standard Refuelling Facility Expansion Problem: A case study in Australia
    

    Calle, J., Perez-Franco, R., Mak-Hau, V., Abril, D. and Rojas, D.
    https://doi.org/10.36334/modsim.2021.M1.calle

• Adame, M.F.
  • A sensitivity analysis of a water quality model for a constructed wetland
    

    Roberts, M.E., Lu, J., Kavehei, E. and Adame, M.F.
    https://doi.org/10.36334/modsim.2021.L2.roberts

• Adams, M.P.
  • Considering unknown uncertainty in imperfect models: nitrogen mineralization as a case study
    

    Vilas, M.P., Bennett, F.R., Verburg, K. and Adams, M.P.
    https://doi.org/10.36334/modsim.2021.B3.vilas

• Alhuzali, T.
  • Multi-way correspondence analysis approach to examine Nobel Prize data from 1901 to 2018
    

    Alhuzali, T., Beh, E.J. and Stojanovski, E.
    https://doi.org/10.36334/modsim.2021.A1.alhuzali

• Aljoorfri, S.
  • Analytic approaches to understanding future Defence workforce needs
    

    Rowe, C., Crockett, A., Rohan-Jones, S., Aljoorfri, S., Tay, N., Coutts, A., Bishop, C., Pay, A., Sim, W., Date, V. and Boyce, J.
    https://doi.org/10.36334/modsim.2021.M8.rowe

• Alsaedi, Y.
  • The use of exponential smoothing (ES), Holts and Winter (HW) and ARIMA models in electricity price analysis
    

    Alsaedi, Y. and Tularam, G.A.
    https://doi.org/10.36334/modsim.2021.A1.alsaedi

• Alvandi, A.O.
  • Forecasting sales with Bayesian networks: a case study of a supermarket product in the presence of promotions
    

    Hamza, M., Abolghasemi, M. and Alvandi, A.O.
    https://doi.org/10.36334/modsim.2021.M9.hamza

• Alzahrani, A.
  • Model-based clustering with mclust R package: Multivariate assessment of mathematics performance of students in Qatar
    

    Alzahrani, A., Beh, E. and Stojanovski, E.
    https://doi.org/10.36334/modsim.2021.A1.alzahrani

• Amini, S.
  • Lessons learned using dSedNet plug-in within a water supply catchment for Greater Sydney
    

    Amini, S., Pont, J., van der Sterren, M. and Freebairn, A.
    https://doi.org/10.36334/modsim.2021.F7.amini

• Amirghasemi, M.
  • The dial-a-ride problem in the case of a patient transportation system in Brazil
    

    Bernardo, M., Souza, A.L., Amirghasemi, M., Barthelemy, J. and Perez, P.
    https://doi.org/10.36334/modsim.2021.M1.bernardo

• Anwar, A.H.M.F.
  • A comparative study on 10 and 30-year simulation of CMIP5 decadal hindcast precipitation at catchment level
    

    Hossain, M.M., Garg, N., Anwar, A.H.M.F., Prakash, M. and Bari, M.
    https://doi.org/10.36334/modsim.2021.K5.hossain

• Armstrong, M.S.
  • Robust detection of statistically significant correlations in geophysical timeseries: A Monte Carlo method accounting for serial dependence and sampling uncertainty
    

    Armstrong, M.S., Kiem, A.S. and Kuczera, G.
    https://doi.org/10.36334/modsim.2021.A1.armstrong

• Armstrong, R.D.
  • OneWorld: Evolving an architecture for complex system representation in engagement simulation
    

    Armstrong, R.D., Christie, M.J. and Mellen, P.R.
    https://doi.org/10.36334/modsim.2021.M7.armstrong

• Awad, J.
  • A model based on DOC data for determination of alum dosing for drinking water treatment
    

    Daraei, H., Awad, J., Bertone, E., Stewart, R.A., Chow, C.W.K., Duan, J. and van Leeuwen, J.
    https://doi.org/10.36334/modsim.2021.L2.daraei

• Azzollini, N.
  • Optimal location of launchers in a missile defence system
    

    Azzollini, N., Babu, B., Reade, A. and Rodda, J.
    https://doi.org/10.36334/modsim.2021.M7.azzollini

B

• Babu, B.
  • Optimal location of launchers in a missile defence system
    

    Azzollini, N., Babu, B., Reade, A. and Rodda, J.
    https://doi.org/10.36334/modsim.2021.M7.azzollini

• Badlan, R.L.
  • Spotfire Utilisation Project: Development of a mapping tool for regions prone to vorticity-driven lateral spread
    

    Badlan, R.L. and Sharples, J.J.
    https://doi.org/10.36334/modsim.2021.G3.badlan

• Baldock, J.A.
  • A nationally scalable approach to simulating soil organic carbon in agricultural landscapes
    

    Coelli, K.M., Karunaratne, S.B., Baldock, J.A., Ugbaje, S., Buzacott, A.J.V., Filippi, P., Cattle, S. and Bishop, T.F.A.
    https://doi.org/10.36334/modsim.2021.B6.coelli

• Barber, D.G.
  • Preliminary results of parameterisation of DairyMod pasture model for tropical pasture; Brachiaria
    

    Jayasinghe, J.M.P., Donaghy, D.J., Pembleton, K.G., Barber, D.G. and Ramilan, T.
    https://doi.org/10.36334/modsim.2021.B1.jayasinghe

• Bari, M.
  • A comparative study on 10 and 30-year simulation of CMIP5 decadal hindcast precipitation at catchment level
    

    Hossain, M.M., Garg, N., Anwar, A.H.M.F., Prakash, M. and Bari, M.
    https://doi.org/10.36334/modsim.2021.K5.hossain

• Barthelemy, J.
  • The dial-a-ride problem in the case of a patient transportation system in Brazil
    

    Bernardo, M., Souza, A.L., Amirghasemi, M., Barthelemy, J. and Perez, P.
    https://doi.org/10.36334/modsim.2021.M1.bernardo

• Bax, K.
  • Impacts of localizing food system on farmers’ livelihood resilience
    

    Loo, P.S., Önal, F., Bax, K., Smairy, M. and Surovets, V.
    https://doi.org/10.36334/modsim.2021.B5.loo

• Beh, E.J.
  • Multi-way correspondence analysis approach to examine Nobel Prize data from 1901 to 2018
    

    Alhuzali, T., Beh, E.J. and Stojanovski, E.
    https://doi.org/10.36334/modsim.2021.A1.alhuzali

  • Model-based clustering with mclust R package: Multivariate assessment of mathematics performance of students in Qatar
    

    Alzahrani, A., Beh, E.J. and Stojanovski, E.
    https://doi.org/10.36334/modsim.2021.A1.alzahrani

• Behrendt, K.
  • Building responsive bio-economic models to replicate complex farm management decisions for mixed irrigation farming systems in southern NSW
    

    Broadfoot, K., Cashen, M., Behrendt, K., Clark, A.J. and Graham, P.
    https://doi.org/10.36334/modsim.2021.B8.broadfoot

• Beletse, Y.G.
  • Changing crop management improves farm level productivity and profitability for smallholder farmers in northern India
    

    Beletse, Y.G., Laing, A.M., Prestwidge, D.B., Gathala, M.K., Subash, N. and Liedloff, A.C.
    https://doi.org/10.36334/modsim.2021.B8.beletse

• Bell, S.S.
  • Tropical cyclone-induced extreme winds in climate datasets: East coast of Australia
    

    Bell, S.S., Chand, S.S., Dowdy, A.J., Ramsay, H.A., Deo, A., Su, C.-H., Brown, A. and Ye, H.
    https://doi.org/10.36334/modsim.2021.G4.bell

  • Extreme bushfire projections using a standardised method
    

    Dowdy, A.J., Thatcher, M., Rafter, T., Evans, J., Ye, H., Su, C.-H., Stassen, C., Pepler, A., Bell, S.S. and Steinle, P.
    https://doi.org/10.36334/modsim.2021.G3.dowdy

• Bellette, K.
  • A framework for engaging stakeholders in solving real-world water resources management problems
    

    Wu, W., Maier, H.R., Dandy, G.C., Leonard, R., Bellette, K., Cuddy, S.M. and Maheepala, S.
    https://doi.org/10.36334/modsim.2021.F3.wu

• Bennamoun, M.
  • A discrete event simulation for modelling Aljamarat Bridge rituals and evacuation scenarios
    

    Owaidah, A.A., Olaru, D., Bennamoun, M., Sohel, F. and Khan, R.N.
    https://doi.org/10.36334/modsim.2021.I8.owaidah

• Bennett, B.
  • Water security analysis of the Middle River supply system: a foreSIGHT application
    

    Culley, S., Westra, S., Bennett, B., Maier, H.R., Newman, J., Van Der Linden, L. and Irvine, M.
    https://doi.org/10.36334/modsim.2021.J5.culley

• Bennett, F.R.
  • Estimating rainfall-runoff model parameters using the iterative ensemble smoother
    

    Bennett, F.R. and Doherty, J.
    https://doi.org/10.36334/modsim.2021.L1.bennett

  • Opportunistic emulation of computationally expensive simulations via Deep Learning
    

    Sanderson, C., Pagendam, D., Power, B., Bennett, F.R. and Darnell, R.
    https://doi.org/10.36334/modsim.2021.L1.sanderson

  • Considering unknown uncertainty in imperfect models: nitrogen mineralization as a case study
    

    Vilas, M.P., Bennett, F.R., Verburg, K. and Adams, M.P.
    https://doi.org/10.36334/modsim.2021.B3.vilas

• Bennett, S.
  • The use of modelling in design of wastewater subsurface drip irrigation
    

    Cook, F.J., Gearing, P., Bennett, S. and Oakley, R.
    https://doi.org/10.36334/modsim.2021.L2.cook

• Bernardo, M.
  • The dial-a-ride problem in the case of a patient transportation system in Brazil
    

    Bernardo, M., Souza, A.L., Amirghasemi, M., Barthelemy, J. and Perez, P.
    https://doi.org/10.36334/modsim.2021.M1.bernardo

• Berres, S.
  • Bushfire propagation speed: Combining the effects of wind and slope
    

    Berres, S. and Cárcamo, N.
    https://doi.org/10.36334/modsim.2021.G3.berres

  • Algorithms for diffusion and convection models implemented using open source libraries
    

    Mas-Hernandez, E., Mancilla-Barría, E.A., de la Torre-Sanzana, M. and Berres, S.
    https://doi.org/10.36334/modsim.2021.C3.mas-hernandez

• Bertone, E.
  • A model based on DOC data for determination of alum dosing for drinking water treatment
    

    Daraei, H., Awad, J., Bertone, E., Stewart, R.A., Chow, C.W.K., Duan, J. and van Leeuwen, J.
    https://doi.org/10.36334/modsim.2021.L2.daraei

• Bertram, N.
  • The local influence of residential infill on the urban water flows: a multi-city analysis
    

    Moravej, M., Kenway, S., Renouf, M., Urich, C., Sainsbury, O., Bertram, N. and London, G.
    https://doi.org/10.36334/modsim.2021.J4.moravej

• Bilusich, D.
  • An evaluation model and tool for Defence capability options
    

    Nguyen, M.-T., Coutts, A., Knoll, J., Zuparic, M., Peacock, J., Bilusich, D., Galister, M. and Johns, K.
    https://doi.org/10.36334/modsim.2021.M8.nguyen

• Bishop, C.
  • Analytic approaches to understanding future Defence workforce needs
    

    Rowe, C., Crockett, A., Rohan-Jones, S., Aljoorfri, S., Tay, N., Coutts, A., Bishop, C., Pay, A., Sim, W., Date, V. and Boyce, J.
    https://doi.org/10.36334/modsim.2021.M8.rowe

• Bishop, T.F.A.
  • A nationally scalable approach to simulating soil organic carbon in agricultural landscapes
    

    Coelli, K.M., Karunaratne, S.B., Baldock, J.A., Ugbaje, S., Buzacott, A.J.V., Filippi, P., Cattle, S. and Bishop, T.F.A.
    https://doi.org/10.36334/modsim.2021.B6.coelli

• Bista, S.
  • A layered meta-data approach to the design of joint experimentation data warehouse
    

    Jiang, L., Boyle, M., Johns, K., Muniyappagounder Subramanian, C. and Bista, S.
    https://doi.org/10.36334/modsim.2021.M8.jiang

  • An instance space analysis of combat simulations to understand the impact of force and information advantage on survival ratios
    

    Smith-Miles, K., Bista, S. and Jiang, L.
    https://doi.org/10.36334/modsim.2021.M7.smith-miles

• Blackmore, K.
  • Evaluating instruction quality across narrative modality using measures of real-time cognitive load
    

    Smith, S.P., Blackmore, K., Wark, S. and Nowina-Krowicki, M.
    https://doi.org/10.36334/modsim.2021.M2.smith

• Blaess, S.G.
  • Comet: A naval Combat Management System model for combat analysis
    

    Blaess, S.G., Christie, M.J. and Mitchell, J.L.
    https://doi.org/10.36334/modsim.2021.M7.blaess

• Blockley, I.
  • Enhancement of lightning strike forecasts using a machine learning approach
    

    Gow, D., Lerat, J., Warren, R. and Blockley, I.
    https://doi.org/10.36334/modsim.2021.K7.gow

• Blumson, D.
  • Operational effectiveness of future land combat teams: model conceptualisation
    

    Richmond, M.K., Gary, M.S., Cao, T., Blumson, D., Kosowski, L., Hock, K., Elsawah, S. and Kempt, N.
    https://doi.org/10.36334/modsim.2021.M4.richmond

• Bogomolov, T.
  • Regression-based approaches for simulation meta-modelling in the presence of heterogeneity and correlation
    

    Garces, L.P.D.M., Bogomolov, T. and Chiera, B.A.
    https://doi.org/10.36334/modsim.2021.M5.garces

• Bolger, M.
  • Using Workspace to implement Digital Twins in the Mixed Reality Lab
    

    Watkins, D., Bolger, M., Hetherton, L., Zhang, Z., Xie, P., Harrison, S.M. and Cohen, R.C.Z.
    https://doi.org/10.36334/modsim.2021.C1.watkins

• Boulomytis, V.T.G.
  • Evaluation of the time of concentration estimation methods for small rural watersheds
    

    Rezende, B.N., Boulomytis, V.T.G., Duarte, S.N., Jacomazzi, M.A. and Zuffo, A.C.
    https://doi.org/10.36334/modsim.2021.J7.rezende

• Boyce, J.
  • Consideration of enabling and enterprise functions within Defence force design
    

    Boyce, J., Tay, N. and Rowe, C.
    https://doi.org/10.36334/modsim.2021.M8.boyce

  • Analytic approaches to understanding future Defence workforce needs
    

    Rowe, C., Crockett, A., Rohan-Jones, S., Aljoorfri, S., Tay, N., Coutts, A., Bishop, C., Pay, A., Sim, W., Date, V. and Boyce, J.
    https://doi.org/10.36334/modsim.2021.M8.rowe

• Boyle, M.
  • A layered meta-data approach to the design of joint experimentation data warehouse
    

    Jiang, L., Boyle, M., Johns, K., Muniyappagounder Subramanian, C. and Bista, S.
    https://doi.org/10.36334/modsim.2021.M8.jiang

• Bretas, A.M.C.
  • Freight train scheduling via decentralised multi-agent deep reinforcement learning
    

    Bretas, A.M.C., Mendes, A., Chalup, S., Jackson, M., Clement, R. and Sanhueza, C.
    https://doi.org/10.36334/modsim.2021.M1.bretas

• Broadfoot, K.
  • Building responsive bio-economic models to replicate complex farm management decisions for mixed irrigation farming systems in southern NSW
    

    Broadfoot, K., Cashen, M., Behrendt, K., Clark, A.J. and Graham, P.
    https://doi.org/10.36334/modsim.2021.B8.broadfoot

• Brown, A.
  • Tropical cyclone-induced extreme winds in climate datasets: East coast of Australia
    

    Bell, S.S., Chand, S.S., Dowdy, A.J., Ramsay, H.A., Deo, A., Su, C.-H., Brown, A. and Ye, H.
    https://doi.org/10.36334/modsim.2021.G4.bell

• Buzacott, A.J.V.
  • A nationally scalable approach to simulating soil organic carbon in agricultural landscapes
    

    Coelli, K.M., Karunaratne, S.B., Baldock, J.A., Ugbaje, S., Buzacott, A.J.V., Filippi, P., Cattle, S. and Bishop, T.F.A.
    https://doi.org/10.36334/modsim.2021.B6.coelli

• Caelli, T.
  • Simulation and data analytics for a Defence workforce transition
    

    Mortimer, K., Nguyen, V., Caelli, T. and Hill, B.
    https://doi.org/10.36334/modsim.2021.A3.mortimer

• Calbert, G.
  • Portfolio optimisation and scheduling using temporal tolerances
    

    Calbert, G.
    https://doi.org/10.36334/modsim.2021.M8.calbert

• Calle, J.
  • The Standard Refuelling Facility Expansion Problem: A case study in Australia
    

    Calle, J., Perez-Franco, R., Mak-Hau, V., Abril, D. and Rojas, D.
    https://doi.org/10.36334/modsim.2021.M1.calle