| Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity AAM Ahmed, RC Deo, Q Feng, A Ghahramani, N Raj, Z Yin, L Yang Journal of Hydrology 599, 126350, 2021 | 122 | 2021 |
| A review of measuring, assessing and mitigating heat stress in dairy cattle B Ji, T Banhazi, K Perano, A Ghahramani, L Bowtell, C Wang, B Li Biosystems Engineering 199, 4-26, 2020 | 117 | 2020 |
| Effect of ground cover on splash and sheetwash erosion over a steep forested hillslope: a plot-scale study A Ghahramani, Y Ishikawa, T Gomi, K Shiraki, S Miyata Catena 85 (1), 34-47, 2011 | 110 | 2011 |
| Climate change and broadacre livestock production across southern Australia. 1. Impacts of climate change on pasture and livestock productivity, and on sustainable levels of … AD Moore, A Ghahramani Global change biology 19 (5), 1440-1455, 2013 | 109 | 2013 |
| LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4. 5 and RCP8. 5 global warming scenarios AAM Ahmed, RC Deo, A Ghahramani, N Raj, Q Feng, Z Yin, L Yang Stochastic Environmental Research and Risk Assessment, 1-31, 2021 | 75 | 2021 |
| Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale … AA Ahmed, RC Deo, N Raj, A Ghahramani, Q Feng, Z Yin, L Yang Remote Sensing 13 (4), 554, 2021 | 72 | 2021 |
| The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise D Wallach, T Palosuo, P Thorburn, Z Hochman, E Gourdain, ... Environmental Modelling & Software 145, 105206, 2021 | 67 | 2021 |
| Climate Change Impact, Adaptation, and Mitigation in Temperate Grazing Systems: A Review A Ghahramani, SM Howden, A del Prado, DT Thomas, AD Moore, B Ji, ... Sustainability 11 (24), 7224, 2019 | 63 | 2019 |
| Land use change in Australian mixed crop-livestock systems as a transformative climate change adaptation A Ghahramani, RS Kingwell, TN Maraseni Agricultural Systems 180, 102791, 2020 | 58 | 2020 |
| Hybrid deep learning method for a week-ahead evapotranspiration forecasting AAM Ahmed, RC Deo, Q Feng, A Ghahramani, N Raj, Z Yin, L Yang Stochastic Environmental Research and Risk Assessment, 1-19, 2022 | 53 | 2022 |
| The value of adapting to climate change in Australian wheat farm systems: farm to cross-regional scale A Ghahramani, PN Kokic, AD Moore, B Zheng, SC Chapman, ... Agriculture, Ecosystems & Environment 211, 112-125, 2015 | 53 | 2015 |
| New double decomposition deep learning methods for river water level forecasting AAM Ahmed, RC Deo, A Ghahramani, Q Feng, N Raj, Z Yin, L Yang Science of The Total Environment 831, 154722, 2022 | 52 | 2022 |
| Impact of climate changes on existing crop-livestock farming systems A Ghahramani, AD Moore Agricultural Systems 146, 142-155, 2016 | 50 | 2016 |
| Climate change and broadacre livestock production across southern Australia. 2. Adaptation options via grassland management A Ghahramani, AD Moore Crop and Pasture Science 64 (6), 615-630, 2013 | 48 | 2013 |
| Transformative and systemic climate change adaptations in mixed crop-livestock farming systems A Ghahramani, D Bowran Agricultural Systems 164, 236-251, 2018 | 47 | 2018 |
| Climate change and broadacre livestock production across southern Australia. 3. Adaptation options via livestock genetic improvement A Moore, A Ghahramani Animal Production Science 54 (2), 111–220, 2014 | 39 | 2014 |
| Modelling of heat stress in a robotic dairy farm. Part 1: Thermal comfort indices as the indicators of production loss B Ji, T Banhazi, A Ghahramani, L Bowtell, C Wang, B Li Biosystems Engineering 199, 27-42, 2020 | 37 | 2020 |
| How well do crop modeling groups predict wheat phenology, given calibration data from the target population? D Wallach, T Palosuo, P Thorburn, E Gourdain, S Asseng, B Basso, ... European Journal of Agronomy 124, 126195, 2021 | 34 | 2021 |
| Systemic adaptations to climate change in southern Australian grasslands and livestock: Production, profitability, methane emission and ecosystem function A Ghahramani, AD Moore Agricultural Systems 133, 158-166, 2015 | 32 | 2015 |
| Modelling of heat stress in a robotic dairy farm. Part 2: Identifying the specific thresholds with production factors B Ji, T Banhazi, A Ghahramani, L Bowtell, C Wang, B Li Biosystems Engineering 199, 43-57, 2020 | 31 | 2020 |
Andrew D. MooreResilience R&D Coordinator, CSIROVahvistettu sähköpostiosoite verkkotunnuksessa csiro.au
