Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

As an epigenetic modification that plays an important role in modifying gene function and
controlling gene expression during cell development, DNA N4-methylcytosine (4mC) is still …

Randomized neural networks have become more and more attractive recently since they
use closed-form solutions for parameter training instead of gradient-based approaches …

Due to rapid climate change and man-made activities, the types of leaf diseases are
gradually increasing. As a result, taking the essential measures to recognize and diagnose …

Random vector functional link (RVFL) has always proven to be an excellent classifier in
various application areas of machine learning. In this work, inspired by RVFL and its twin …

Ensuring the prediction accuracy of a learning algorithm on a theoretical basis is crucial and
necessary for building the reliability of the learning algorithm. This paper analyzes prediction …

To ameliorate the precision of clothing image classification, we proposed a clothing image
classification method via the DenseNet201 network based on transfer learning and the …

Linear and quadratic discriminant analysis are two fundamental classification methods used
in statistical learning. Moments (MM), maximum likelihood (ML), minimum volume ellipsoids …

Effective ground delay programs (GDP) are needed to intervene when there are bad
weather or airport capacity issues. This paper proposes a new methodology for predicting …

Random vector function link (RVFL) network with direct links and closed form solution has
shown its strength among randomized neural networks (RNNs). RVFL assumes that all the …