Diabetes is one of the most common diseases worldwide. Many Machine Learning (ML)
techniques have been utilized in predicting diabetes in the last couple of years. The …

Artificial intelligence and machine learning (AI–ML) offer vast potential in optimal design,
monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption …

Faulty structural design may cause multistory reinforced concrete (RC) buildings to collapse
suddenly. All attempts are directed to avoid structural failure as it leads to human life danger …

Neural networks are a computing paradigm that is finding increasing attention among
computer scientists. In this book, theoretical laws and models previously scattered in the …

The origins of artificial intelligence can be traced back to early centuries, even to the times of
ancient philosophers, especially if we consider the philosophical aspects of this field of …

River flow forecasting is required to provide basic information on a wide range of problems
related to the design and operation of river systems. The availability of extended records of …

In this paper, using a large database from the Long Term Pavement Performance program,
the authors developed an Artificial Neural Network (ANN) to estimate the structural …

This paper presents an axiomatic approach for constructing radial basis function (RBF)
neural networks. This approach results in a broad variety of admissible RBF models …

The paper illustrates an artificial neural network (ANN) approach based on supervised
neural networks for the transport energy demand forecasting using socio-economic and …

This paper introduces quantum neural networks (QNNs), a class of feedforward neural
networks (FFNNs) inherently capable of estimating the structure of a feature space in the …