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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Rose, C., Pasquier, P., Nguyen, A., & Labib, R. (2025). Efficient construction of short-term transfer functions for closed-loop boreholes in stratified aquifers under groundwater flow using neural networks and wavelet decomposition. Science and Technology for the Built Environment, 17 pages. External link
Rose, C., Pasquier, P., Nguyen, A., & Labib, R. (2024, May). Short-term transfer function approximation using artificial neural network in a heterogeneous medium with groundwater advection [Paper]. IGSHPA Research Conference 2024, Montréal, Québec (10 pages). External link
Rose, C., Pasquier, P., Nguyen, A., & Beaudry, G. (2022, December). Forecasting hydraulic head changes in injection wells using LSTM network [Paper]. International Ground Source Heat Pump Association annual Conference, Las vegas, NV, USA. External link
Ben Aoun, M. A., Pasquier, P., Nguyen, A., & Rose, C. (2024, September). Applying CNN-LSTM Neural Network To Predict Water Levels in Injection Wells [Poster]. World Groundwater Congress (IAH 2024), Davos, Switzerland (1 page). Unavailable
Rose, C., Pasquier, P., Nguyen, A., & Labib, R. (2025, April). Near-instant prediction of short-term transfer functions for closed-loop boreholes in heterogeneous aquifers influenced by groundwater flow using wavelet decomposition and neural networks [Abstract]. EGU General Assembly 2025, Vienna, Austria (2 pages). External link
