The increase of energy consumption and their direct effects on pollution and global warming
have motivated governments to develop new strategies to promote a better usage of energy …

This paper proposes a novel ensemble approach, integrating Artificial Neural Networks
(ANNs), Symbolic Regression (SR), and Decision Trees (DTs), to predict fish mortality …

We present an approach for regression problems that employs analytic continued fractions
as a novel representation. Comparative computational results using a memetic algorithm are …

In this paper, we present a comparison between a collection of Artificial Neural Networks
(ANNs)—specifically, Multilayer Perceptrons—and a collection of Symbolic Regression (SR) …

Commercial greenhouses require sophisticated energy management strategies to ensure
optimal plant growth while minimizing operational costs. The ability to adapt energy usage …

This work addresses the problem of energy consumption time series forecasting. In our
approach, a set of time series containing energy consumption data is used to train a single …

This work addresses the problem of energy consumption time series forecasting. In our
approach, a set of time series containing energy consumption data is used to train a single …