In this study, we propose a method to find an optimal combination of hyperparameters to
improve the accuracy of respiration pattern recognition in a 1D (Dimensional) convolutional …

The weak classifier ensemble algorithms based on the decision tree model, mainly include
bagging (eg, fandom forest-RF) and boosting (eg, gradient boosting decision tree, eXtreme …

Researchers from different domains have developed several metaheuristic algorithms that
are inspired by the biological phenomenon. In this work, we propose a novel algorithm that …

Nowadays, there are various optimization problems that exact mathematical methods are
not applicable. Metaheuristics are considered as efficient approaches for finding the …

The state of the art in Sentiment Analysis is defined by deep learning methods, and currently
the research efforts are focused on improving the encoding of underlying contextual …

According to the no-free-lunch theorem, there is no single meta-heuristic algorithm that can
optimally solve all optimization problems. This motivates many researchers to continuously …

An automatic and robust algorithm for the first‐break picking is necessary to build the near‐
surface velocity model. We propose the algorithm based on a convolution neural network …

This paper proposes a solution to enhance and compare different neural network (NN)-
based side-slip angle estimators. The feed-forward neural networks (FFNNs), recurrent …

Cloud computing is widely applied by modern software development companies. Providing
digital services in a cloud environment offers both the possibility of cost-efficient usage of …

Concealed threat detection is at the heart of critical security systems designed to en-sure
public safety. Currently, methods for threat identification and detection are primarily manual …