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Jennifer Marohasy
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Input selection and optimisation for monthly rainfall forecasting in Queensland, Australia, using artificial neural networks
J Abbot, J Marohasy
Atmospheric Research 138, 166-178, 2014
2682014
Application of artificial neural networks to rainfall forecasting in Queensland, Australia
J Abbot, J Marohasy
Advances in Atmospheric Sciences 29, 717-730, 2012
2342012
The design and interpretation of host-specificity tests for weed biological control with particular reference to insect behaviour
J Marohasy
Biocontrol News and Information 19, 13N-20N, 1998
2131998
Host shifts in biological weed control: real problems, semantic difficulties or poor science?
J Marohasy
International Journal of Pest Management 42 (2), 71-75, 1996
901996
A taxonomic revision of Cryptostegia R. Br.(Asclepiadaceae: Periplocoideae)
J Marohasy, PI Forster
Australian Systematic Botany 4 (3), 571-577, 1991
601991
Skilful rainfall forecasts from artificial neural networks with long duration series and single-month optimization
J Abbot, J Marohasy
Atmospheric Research 197, 289-299, 2017
462017
The application of machine learning for evaluating anthropogenic versus natural climate change
J Abbot, J Marohasy
GeoResJ 14, 36-46, 2017
372017
The gall midges (Diptera: Cecidomyiidae) of Acacia spp. (Mimosaceae) in Kenya
RJ Gagne, J Marohasy
Insecta Mundi, 77-124, 1993
351993
Prospects for the biological control of prickly acacia, Acacia nilotica (L.) Willd. ex Del.(Mimosaceae) in Australia
J Marohasy
Plant Protection Quarterly 10, 24-24, 1995
341995
Myth and the Murray: measuring the real state of the river environment
J Marohasy
272003
A leaf feeding moth,Euclasta whalleyi [Lep.: Pyralidae] for the biological control ofCryptostegia grandiflora [Asclepiadaceae] in Queensland, Australia
RE McFadyen, JJ Marohasy
Entomophaga 35, 431-435, 1990
271990
Acceptability and suitability of seven plant species for the mealybug Phenacoccus parvus
J Marohasy
Entomologia Experimentalis et Applicata 84 (3), 239-246, 1997
261997
A survey of fireweed (Senecio madagascariensis Poir) and its natural enemies in Madagascar with a view to biological control in Australia.
JJ Marohasy
231989
Application of artificial neural networks to forecasting monthly rainfall one year in advance for locations within the Murray Darling basin, Australia
J Abbot, J Marohasy
International Journal of Sustainable Development and Planning 12 (8), 1282-1298, 2017
222017
The potential benefits of using artificial intelligence for monthly rainfall forecasting for the Bowen Basin, Queensland, Australia
J Abbot, J Marohasy
Water resources management VII. WIT Transactions on Ecology and the …, 2013
212013
Assessing the quality of eight different maximum temperature time series as inputs when using artificial neural networks to forecast monthly rainfall at Cape Otway, Australia
J Marohasy, J Abbot
Atmospheric Research 166, 141-149, 2015
202015
Forecasting of medium-term rainfall using Artificial Neural Networks: Case studies from Eastern Australia
J Abbot, J Marohasy
Engineering and mathematical topics in rainfall 33, 2018
182018
Has the herbicide diuron caused mangrove dieback? A re-examination of the evidence
J Abbot, J Marohasy
Human and Ecological Risk Assessment: An International Journal 17 (5), 1077-1094, 2011
172011
Importation Protocols and Risk Assessment of Weed Biological Control Agents in Australia: The Example of Carmenta nr Ithacae
T Withers, R McFadyen, J Marohasy
Nontarget effects of biological control, 195-214, 1999
171999
Using lagged and forecast climate indices with artificial intelligence to predict monthly rainfall in the Brisbane Catchment, Queensland, Australia
J Abbot, J Marohasy
International Journal of Sustainable Development and Planning 10 (1), 29-41, 2015
162015
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