Wissenschaftliche Artikel

Purcell, W., & Neubauer, T. (2023). Digital Twins in Agriculture: A State-of-the-art review. Smart Agricultural Technology, 3, Article 100094. https://doi.org/10.1016/j.atech.2022.100094 ( reposiTUm)
Purcell, W., Neubauer, T., & Mallinger, K. (2023). Digital Twins in agriculture: challenges and opportunities for environmental sustainability. Current Opinion in Environmental Sustainability, 61, Article 101252. https://doi.org/10.34726/4522 ( reposiTUm)
Raubitzek, S., & Neubauer, T. (2022). An Exploratory Study on the Complexity and Machine Learning Predictability of Stock Market Data. Entropy, 24(3), Article 332. https://doi.org/10.3390/e24030332 ( reposiTUm)

Beiträge in Tagungsbänden

Purcell, W., Klipic, A., & Neubauer, T. (2022). A Digital Twin for Grassland Management. In 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET). 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET), Czechia. IEEE. https://doi.org/10.1109/icecet55527.2022.9873446 ( reposiTUm)
Hoxhallari, K., Purcell, W., & Neubauer, T. (2022). The potential of Explainable Artificial Intelligence in Precision Livestock Farming. In D. Berckmans, M. Oczak, M. Iwersen, & K. Wagener (Eds.), Precision Livestock Farming 2022 : papers presented at the 10th European Conference on Precision Livestock Farming (pp. 710–717). University of Veterinary Medicine Vienna. https://doi.org/10.34726/4701 ( reposiTUm)
Mallinger, K., Purcell, W., & Neubauer, T. (2022). Systemic design requirements for sustainable Digital Twins in precision livestock farming. In D. Berckmans, M. Oczak, M. Iwersen, & K. Wagener (Eds.), Precision Livestock Farming ’22 (pp. 718–725). https://doi.org/10.34726/4644 ( reposiTUm)