Accurate long-range forecasting of COVID-19 mortality in the USA
The need for improved models that can accurately predict COVID-19 dynamics is vital to
managing the pandemic and its consequences. We use machine learning techniques to …
managing the pandemic and its consequences. We use machine learning techniques to …
Novel analytic methods for predicting extinctions in ecological networks
Ecological networks describe the interactions between different species, informing us how
they rely on one another for food, pollination, and survival. If a species in an ecosystem is …
they rely on one another for food, pollination, and survival. If a species in an ecosystem is …
Predicting insect outbreaks using machine learning: A mountain pine beetle case study
Planning forest management relies on predicting insect outbreaks such as mountain pine
beetle, particularly in the intermediate‐term future, eg, 5‐year. Machine‐learning algorithms …
beetle, particularly in the intermediate‐term future, eg, 5‐year. Machine‐learning algorithms …
Cyberinfrastructure for sourcing and processing ecological data
F Recknagel - Ecological Informatics, 2023 - Elsevier
Cyberinfrastructure is a product of the information age that provides a framework for
informing adaptive management of ecological entities under the impact of regional and …
informing adaptive management of ecological entities under the impact of regional and …
Effect of physical geographic and socioeconomic processes on interactions among ecosystem services based on machine learning
X Sun, D Ye, R Shan, Q Peng, Z Zhao, J Sun - Journal of Cleaner …, 2022 - Elsevier
A thorough understanding of the interactions of ecosystem services (ESs) can enable
effective ES planning and management to curtail their degradation and enhance restoration …
effective ES planning and management to curtail their degradation and enhance restoration …
Integrating food webs in species distribution models can improve ecological niche estimation and predictions
Biotic interactions play a fundamental role in shaping multitrophic species communities, yet
incorporating these interactions into species distribution models (SDMs) remains …
incorporating these interactions into species distribution models (SDMs) remains …
A novel approach to assessing natural resource injury with Bayesian networks
Quantifying the effects of environmental stressors on natural resources is problematic
because of complex interactions among environmental factors that influence endpoints of …
because of complex interactions among environmental factors that influence endpoints of …
From Policy to Prediction: Assessing Forecasting Accuracy in an Integrated Framework with Machine Learning and Disease Models
AK Chakraborty, H Wang, P Ramazi - Journal of Computational …, 2024 - liebertpub.com
To improve the forecasting accuracy of the spread of infectious diseases, a hybrid model
was recently introduced where the commonly assumed constant disease transmission rate …
was recently introduced where the commonly assumed constant disease transmission rate …
A hypothesis-free bridging of disease dynamics and non-pharmaceutical policies
Accurate prediction of the number of daily or weekly confirmed cases of COVID-19 is critical
to the control of the pandemic. Existing mechanistic models nicely capture the disease …
to the control of the pandemic. Existing mechanistic models nicely capture the disease …
Tackling data challenges in forecasting effluent characteristics of wastewater treatment plants
In wastewater treatment plants (WWTPs), the stochastic nature of influent wastewater and
operational and weather conditions cause fluctuations in effluent quality. Data-driven …
operational and weather conditions cause fluctuations in effluent quality. Data-driven …