Computational and analytical analysis of integral-differential equations for modeling avoidance learning behavior
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Title: | Computational and analytical analysis of integral-differential equations for modeling avoidance learning behavior |
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Authors: | Turab, Ali | Montoyo, Andres | Nescolarde-Selva, Josué Antonio |
Research Group/s: | Procesamiento del Lenguaje y Sistemas de Información (GPLSI) | Sistémica y Cibernética (SYC) |
Center, Department or Service: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | Universidad de Alicante. Departamento de Matemática Aplicada |
Keywords: | Integral-differential equations | Solutions | Numerical computations | Avoidance behavior |
Issue Date: | 3-Jun-2024 |
Publisher: | Springer Nature |
Citation: | Journal of Applied Mathematics and Computing. 2024, 70: 4423-4439. https://doi.org/10.1007/s12190-024-02130-3 |
Abstract: | This work emphasizes the computational and analytical analysis of integral-differential equations, with a particular application in modeling avoidance learning processes. Firstly, we suggest an approach to determine a unique solution to the given model by employing methods from functional analysis and fixed-point theory. We obtain numerical solutions using the approach of Picard iteration and evaluate their stability in the context of minor perturbations. In addition, we explore the practical application of these techniques by providing two examples that highlight the thorough analysis of behavioral responses using numerical approximations. In the end, we examine the efficacy of our suggested ordinary differential equations (ODEs) for studying the avoidance learning behavior of animals. Furthermore, we investigate the convergence and error analysis of the proposed ODEs using multiple numerical techniques. This integration of theoretical and practical analysis enhances the domain of applied mathematics by providing important insights for behavioral science research. |
Sponsor: | Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research is supported by the University of Alicante, Spain, the Spanish Ministry of Science and Innovation, the Generalitat Valenciana, Spain, and the European Regional Development Fund (ERDF) through the following funding: At the national level, the following projects were granted: TRIVIAL (PID2021-122263OB-C22); and CORTEX (PID2021- 123956OB-I00), funded by MCIN/AEI/10.13039/501100011033 and, as appropriate, by “ERDF A way of making Europe”, by the “European Union” or by the “European Union NextGenerationEU/PRTR”. At regional level, the Generalitat Valenciana (Conselleria d’Educacio, Investigacio, Cultura i Esport), Spain, granted funding for NL4DISMIS (CIPROM/2021/21). |
URI: | http://hdl.handle.net/10045/143517 |
ISSN: | 1598-5865 (Print) | 1865-2085 (Online) |
DOI: | 10.1007/s12190-024-02130-3 |
Language: | eng |
Type: | info:eu-repo/semantics/article |
Rights: | © The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Peer Review: | si |
Publisher version: | https://doi.org/10.1007/s12190-024-02130-3 |
Appears in Collections: | INV - SYC - Artículos de Revistas INV - GPLSI - Artículos de Revistas |
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