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2005, New neural network technique to the numerical solution of mathematical physics problems. II: Complicated and nonstandard problems
Neural networks are considered to be the universal approach to the construction of mathematical models of systems wish distributed parameters. Networks effectively allow us to find the approximate solutions of initial and boundary problems for the partial differential equations and to take into account nonlinear effects and coefficient perturbation. Neural networks of known and new architectures are applied to the solution of Laplase, Helmholts and Schrodinger; heat condition equations in domains with fixed, free, and controlled boundaries; and original training algoritms of these networks are given. This work reviews jur work in 2003 to 2004 and consists of two parts. Part 2 deals withmore complicated and nonstandart problems.
Communications in Numerical Methods in Engineering
Neural-network-based approximations for solving partial differential equations1994 •
Computers, Materials & Continua
Artificial Neural Network Methods for the Solution of Second Order Boundary Value Problems2019 •
The aim of this work is to solve the case study singular model involving the Neumann–Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic programming method (SQPM), i.e., ANN-GA-SQPM. The inspiration to present this numerical framework comes through the objective of introducing a reliable structure that associates the operative ANNs features using the optimization procedures of soft computing to deal with such stimulating systems. Four different problems that are based on the singular equations involving Neumann–Robin, Dirichlet, and Neumann boundary conditions have been occupied to scrutinize the robustness, stability, and proficiency of the designed ANN-GA-SQPM. The proposed results through ANN-GA-SQPM have been compared with the exact results to check the efficiency of the scheme through the statistical performances for t...
IEEE Transactions on Neural Networks
Artificial neural networks for solving ordinary and partial differential equations1998 •
IEEE Transactions on Neural Networks
Neural-network methods for boundary value problems with irregular boundaries2000 •
2009 •
In this paper a strategy based on differential neural networks (DNN) for the identification of the parameters in a mathematical model described by partial differential equations is proposed. The identification problem is reduced to finding an exact expression for the weights dynamics using the DNNs properties. The adaptive laws for weights ensure the convergence of the DNN trajectories to the PDE states. To investigate the qualitative behavior of the suggested methodology, here the non parametric modeling problem for a distributed parameter plant is analyzed: the anaerobic digestion system
λ A DNN-based algorithm that solves the multi-diagonal linear equations is proposed. λ We employed an iteration method that decreased the error of the numerical solution to 10− 7. λ The computational efficiency of the proposed method is 2 to 10 times of the classic algorithms.
2021 •
Conventionally, partial differential equations (PDE) problems are solved numerically through discretization process by using finite difference approximations. The algebraic systems generated by this process are then finalized by using an iterative method. Recently, scientists invented a short cut approach, without discretization process, to solve the PDE problems, namely by using machine learning (ML). This is potential to make scientific machine learning as a new sub-field of research. Thus, given the interest in developing ML for solving PDEs, it makes an abundance of an easy-to-use methods that allows researchers to quickly set up and solve problems. In this review paper, we discussed at least three methods for solving high dimensional of PDEs, namely PyDEns, NeuroDiffEq, and Nangs, which are all based on artificial neural networks (ANNs). ANN is one of the methods under ML which proven to be a universal estimator function. Comparison of numerical results presented in solving the...
Research in Psychotherapy: Psychopathology, Process and Outcome
Introducing the QACP: development and preliminary validation of an instrument to measure psychotherapist’s core competenciesThe movement towards the conceptualization, description and evaluation of psychotherapists’ competencies has been widely developed in the last years and has relevant implications for psychotherapy, training, and continuous education. In Italy, this movement has been supported by the Committee for Psychotherapists’ Competencies established in 2010 by FIAP (Italian Federation of Psychotherapy’s Associations) and CNSP (National Association of Psychotherapy’s Training Institutes) and has involved more than 1000 psychotherapists from different approaches, by means of conferences, expert meetings, workshops, and focus groups. One of the outcomes of this process has been the development of a new self-assessment tool for core competencies (i.e., those that are shared by therapists from all modalities): the QACP (Questionario per l’Autovalutazione delle Competenze dello Psicoterapeuta). The present study aims to present the process of development and the preliminary proofs of the validity of...
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Forum Teologiczne
La Critica Teologica Dell’Odierno Umanesimo Laico. Parte Seconda2017 •
2024 •
Ejercicio de la función docente utilizando recursos Web 2.0 en tres distritos de las regiones Lima, Cusco y Puno.
Cita en Mendoza, L. & et al. (2015). Ejercicio de la función docente utilizando recursos Web 2.0 en tres distritos de las regiones Lima, Cusco y Puno. Pontificia Universidad Católica del Per{u (tesis maestría).2015 •
2010 •
Journal of Food Measurement and Characterization
Acid fuchsin dosimeter: a potential dosimeter for food irradiation dosimetry2018 •
2017 •
Interactive Systems. Design, Specification, and Verification
Resources for Situated ActionsMalaysian Journal of Learning and Instruction
Perspectives of Efl Doctoral Students on Challenges of Citations in Academic Writing2018 •
Frontiers in Veterinary Science
Field Evaluation of the Interferon Gamma Assay for Diagnosis of Tuberculosis in Water Buffalo (Bubalus bubalis) Comparing Four Interpretative Criteria2020 •
Journal of Environmental Protection
Decolourization and Mineralization of Aqueous Solution Containing C. I. Basic Blue 66 in the Presence of Titanium Dioxide2013 •
Operations Management Research
Analyzing the business models for circular economy implementation: a fuzzy TOPSIS approach2021 •
2013 •