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Open Access research that better understands changing marine ecologies...

Strathprints makes available scholarly Open Access content by researchers in the Department of Mathematics & Statistics.

Mathematics & Statistics hosts the Marine Population Modelling group which is engaged in research into topics surrounding marine resource modelling and ecology. Recent work has included important developments in the population modelling of marine species.

Explore the Open Access research of Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Number of items: 5.

Cabaneros, Sheen Mclean and Calautit, John Kaiser and Hughes, Ben (2020) Spatial estimation of outdoor NO2 levels in Central London using deep neural networks and a wavelet decomposition technique. Ecological Modelling, 424. 109017. ISSN 0304-3800

Cabaneros, Sheen Mclean and Calautit, John Kaiser and Hughes, Ben (2020) Short- and long-term forecasting of ambient air pollution levels using wavelet-based non-linear autoregressive artificial neural networks with exogenous inputs. International Journal of Environmental Impacts, 3 (2). pp. 143-154. ISSN 2398-2640

Cabaneros, Sheen Mclean and Calautit, John Kaiser and Hughes, Ben Richard (2019) A review of artificial neural network models for ambient air pollution prediction. Environmental Modelling and Software, 119. pp. 285-304. ISSN 1364-8152

Cabaneros, Sheen Mclean S. and Calautit, John Kaiser S. and Hughes, Ben Richard (2017) Hybrid artificial neural network models for effective prediction and mitigation of urban roadside NO2 pollution. Energy Procedia, 142. pp. 3524-3530. ISSN 1876-6102

Calautit, John and Aquino, Angelo and O'Connor, Dominic and Cabaneros, Sheen and Shahzad, Sally and Wazed, Saeed and Garwood, Tom and Calautit, Katrina and Hughes, Ben (2017) Indoor environmental quality (IEQ) analysis of a low energy wind catcher with horizontally-arranged heat transfer devices. Energy Procedia, 142. pp. 2095-2101. ISSN 1876-6102

This list was generated on Thu Mar 28 14:06:18 2024 GMT.