Numerical and Symbolic Computation: Developments and Applications 2025

A special issue of Mathematical and Computational Applications (ISSN 2297-8747).

Deadline for manuscript submissions: 15 August 2025 | Viewed by 602

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1. CIMOSM—Centro de Investigação em Modelação e Otimização de Sistemas Multifuncionais, ISEL, IPL—Instituto Politécnico de Lisboa, Av. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
2. IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Avenue Rovisco Pais, 1, 1049-001 Lisboa, Portugal
Interests: computational mechanics of solids; composite materials; adaptive structures; optimization; reverse engineering
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Dear Colleagues,

The ECCOMAS Thematic Conference on Numerical and Symbolic Computation: Developments and Applications (SYMCOMP2025) will be the seventh conference in a series that started in 2013, and it aims to bring together academic and scientific communities involved in numerical and symbolic computation across various scientific areas.

Sharing experiences and knowledge about current and emerging research and development areas is a major goal. The multidisciplinary character of this conference makes it a privileged forum to establish and cross-fertilize new multidisciplinary and cross-sector collaborations.

This Special Issue will mainly consist of selected papers presented at the "7th International Conference on Numerical and Symbolic Computation: Developments and Applications". Papers considered to fit the scope of the journal and be of sufficient quality, after evaluation by the reviewers, will be published free of charge.

Dr. Maria Amélia Ramos Loja
Guest Editor

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Keywords

  • symbolic and numerical applications
  • advanced parallel computing
  • system identification, modelling, and optimization
  • intelligent systems’ control and automation

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Published Papers (1 paper)

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Research

13 pages, 2920 KiB  
Article
Dynamic Time Warping as Elementary Effects Metric for Morris-Based Global Sensitivity Analysis of High-Dimension Dynamical Models
by Dhan Lord B. Fortela, Ashley P. Mikolajczyk, Rafael Hernandez, Emmanuel Revellame, Wayne Sharp, William Holmes, Daniel Gang and Mark E. Zappi
Math. Comput. Appl. 2024, 29(6), 111; https://doi.org/10.3390/mca29060111 - 27 Nov 2024
Viewed by 396
Abstract
This work focused on demonstrating the use of dynamic time warping (DTW) as a metric for the elementary effects computation in Morris-based global sensitivity analysis (GSA) of model parameters in multivariate dynamical systems. One of the challenges of GSA on multivariate time-dependent dynamics [...] Read more.
This work focused on demonstrating the use of dynamic time warping (DTW) as a metric for the elementary effects computation in Morris-based global sensitivity analysis (GSA) of model parameters in multivariate dynamical systems. One of the challenges of GSA on multivariate time-dependent dynamics is the modeling of parameter perturbation effects propagated to all model outputs while capturing time-dependent patterns. The study establishes and demonstrates the use of DTW as a metric of elementary effects across the time domain and the multivariate output domain, which are all aggregated together via the DTW cost function into a single metric value. Unlike the commonly studied coefficient-based functional approximation and covariance decomposition methods, this new DTW-based Morris GSA algorithm implements curve alignment via dynamic programing for cost computation in every parameter perturbation trajectory, which captures the essence of “elementary effect” in the original Morris formulation. This new algorithm eliminates approximations and assumptions about the model outputs while achieving the objective of capturing perturbations across time and the array of model outputs. The technique was demonstrated using an ordinary differential equation (ODE) system of mixed-order adsorption kinetics, Monod-type microbial kinetics, and the Lorenz attractor for chaotic solutions. DTW as a Morris-based GSA metric enables the modeling of parameter sensitivity effects on the entire array of model output variables evolving in the time domain, resulting in parameter rankings attributed to the entire model dynamics. Full article
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