BIN-CT: sistema inteligente para la gestión de la recogida de residuos urbanos

By Francisco J. Urbano, Enrique Alba Torres. 2018

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Javier Ferrer
2. Thomas Bäck
3. Andrés Camero
4. Jamal Toutouh
5. Yanan Sun
6. Enrique Alba
7. Shumeet Baluja
8. Wenyin Gong

Citations in the corpus

• Bayesian Neural Architecture Search using A Training-Free Performance Metric (2020, methodology): “Introduced in [33], consists of predicting the filling level of 217 recycling bins located in the metropolitan area of a city in Spain, recorded daily for one year.”
• Waste generation prediction under uncertainty in smart cities through deep neuroevolution (2019, methodology): “In order to continue with the evaluation of our proposal, we benchmark the predictions made by the RNN against the results published in [17, 28].”
• A Specialized Evolutionary Strategy Using Mean Absolute Error Random Sampling to Design Recurrent Neural Networks (2019, methodology): “Originally, Ferrer and Alba [44] proposed to predict the filling level of each container individually using Gaussian processes, linear regression, and SMReg.”