Abstract: Neural networks (NNs) are commonly used to approximate functions based on data samples, as they are a universal function approximator for a large class of ...

In this study a real case multi-objective material and supplier selection problem in cardboard box production industries is studied. This problem for the first time optimizes the objective functions ...

Forbes contributors publish independent expert analyses and insights. Forbes Senior Contributor. 30+ Years Wall Street Career. Professor. For a brief time, I worked for a pricing service, then Thomson ...

As a powerful modelling method, piecewise linear neural networks (PWLNNs) have proven successful in various fields, most recently in deep learning. To apply PWLNN methods, both the representation and ...

Abstract: The use of radial basis functions networks as physics-informed neural networks for solving direct and inverse boundary value problems is demonstrated. On the Levenberg-Marquardt basis ...

The records of maintenance activities are required for modeling the track irregularity deterioration process. However, it is hard to guarantee the completeness and accuracy of the maintenance records.

This column comes with a warning: Do not try to solve this math problem. You will be tempted. This problem is simply stated, easily understood, and all too inviting. Just pick a number, any number: If ...

The inverse problem of electrocardiography consists in reconstructing cardiac electrical activity from given body surface electrocardiographic measurements. Despite tremendous progress in the field ...

Partial differential equations (PDEs) are among the most ubiquitous tools used in modeling problems in nature. However, solving high-dimensional PDEs has been notoriously difficult due to the “curse ...

In this paper, we propose a method for finding the best piecewise linearization of nonlinear functions. For this aim, we try to obtain the best approximation of a nonlinear function as a piecewise ...

The Mori–Zwanzig formalism is an effective tool to derive differential equations describing the evolution of a small number of resolved variables. In this paper we present its application to the ...