We analyze pattern formation in a two-component system within an isotropically growing or shrinking domain. By studying the evolution of a Lyapunov-like function, we derive time-dependent Turing bifurcation conditions through a stability analysis of linear perturbations across all Fourier modes. This general framework enables explicit characterization of pattern formation dynamics. Numerically, we consider two cases: a steady base state (exponential growth) and a time-dependent state (linear growth). First, we validate our approach by recovering the well-known conditions for fixed domains. Then, we simulate the Brusselator reaction system in dynamic domains, obtaining excellent agreement with our model’s predictions. These simulations highlight key pattern features, including evolution, amplitude growth, and wavenumber inertia. Our findings provide a novel energetic and geometrical perspective on the Turing bifurcation.
{"title":"Turing conditions for a two-component isotropic growing system from a potential function","authors":"Aldo Ledesma-Durán, Consuelo García-Alcántara, Iván Santamaría-Holek","doi":"10.1016/j.rinam.2025.100664","DOIUrl":"10.1016/j.rinam.2025.100664","url":null,"abstract":"<div><div>We analyze pattern formation in a two-component system within an isotropically growing or shrinking domain. By studying the evolution of a Lyapunov-like function, we derive time-dependent Turing bifurcation conditions through a stability analysis of linear perturbations across all Fourier modes. This general framework enables explicit characterization of pattern formation dynamics. Numerically, we consider two cases: a steady base state (exponential growth) and a time-dependent state (linear growth). First, we validate our approach by recovering the well-known conditions for fixed domains. Then, we simulate the Brusselator reaction system in dynamic domains, obtaining excellent agreement with our model’s predictions. These simulations highlight key pattern features, including evolution, amplitude growth, and wavenumber inertia. Our findings provide a novel energetic and geometrical perspective on the Turing bifurcation.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100664"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An analytical approach to solve a time-fractional Cauchy problem of order based on the Ornstein–Uhlenbeck (OU), Cox–Ingersoll–Ross (CIR) and Jacobi processes with time-dependent parameters by transforming it into a system of linear fractional differential equations is established. We consider the process as an inhomogeneous Pearson diffusion and derive the analytical formulas for conditional expectations via the Volterra fractional integral equation. We also provide the -conditional moments of the OU, CIR and Jacobi processes where . Finally, we illustrate with examples of the first and second moments of the extended OU and extended CIR processes by obtaining solutions with different values and comparing to .
{"title":"Analytical solutions for time-fractional Cauchy problem based on OU, CIR and Jacobi processes with time-dependent parameters","authors":"Muntiranee Mongkolsin , Khamron Mekchay , Phiraphat Sutthimat","doi":"10.1016/j.rinam.2025.100657","DOIUrl":"10.1016/j.rinam.2025.100657","url":null,"abstract":"<div><div>An analytical approach to solve a time-fractional Cauchy problem of order <span><math><mrow><mn>0</mn><mo><</mo><mi>α</mi><mo>≤</mo><mn>1</mn></mrow></math></span> based on the Ornstein–Uhlenbeck (OU), Cox–Ingersoll–Ross (CIR) and Jacobi processes with time-dependent parameters by transforming it into a system of linear fractional differential equations is established. We consider the process as an inhomogeneous Pearson diffusion and derive the analytical formulas for conditional expectations via the Volterra fractional integral equation. We also provide the <span><math><mi>β</mi></math></span>-conditional moments of the OU, CIR and Jacobi processes where <span><math><mrow><mi>β</mi><mo>∈</mo><mi>R</mi></mrow></math></span>. Finally, we illustrate with examples of the first and second moments of the extended OU and extended CIR processes by obtaining solutions with different <span><math><mi>α</mi></math></span> values and comparing to <span><math><mrow><mi>α</mi><mo>=</mo><mn>1</mn></mrow></math></span>.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100657"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.rinam.2025.100671
Hassan Ranjbar, Afshin Babaei
This paper develops the balanced Euler–Maruyama integrator for stochastic Volterra integral equations. First, an upper bound for the designed integrator is rigorously established in the mean square sense. Next, the scheme is proved to give a strong convergence rate of 1/2 for general diffusion matrices. Furthermore, for a special case of diffusion matrices, we theoretically detect that the established integrator super-converges with strong order 1.0. Numerical experiments are provided to confirm the theoretical findings.
{"title":"Enhancing the Euler–Maruyama integrator via a balancing strategy for stochastic Volterra integral equations","authors":"Hassan Ranjbar, Afshin Babaei","doi":"10.1016/j.rinam.2025.100671","DOIUrl":"10.1016/j.rinam.2025.100671","url":null,"abstract":"<div><div>This paper develops the balanced Euler–Maruyama integrator for stochastic Volterra integral equations. First, an upper bound for the designed integrator is rigorously established in the mean square sense. Next, the scheme is proved to give a strong convergence rate of 1/2 for general diffusion matrices. Furthermore, for a special case of diffusion matrices, we theoretically detect that the established integrator super-converges with strong order 1.0. Numerical experiments are provided to confirm the theoretical findings.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100671"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145614875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.rinam.2025.100662
Mengdi Du, Qinzheng Xu, Zhengkang He, Tong Zhang
This paper considers the optimal -norm error estimates of numerical solutions in a decoupled, mass and charge-conservative mixed finite element method (FEM) for the two-phase inductionless MHD model, which consists of the incompressible inductionless MHD (iMHD) problem and the Cahn–Hilliard equations. Firstly, the targeted problem is split into three linear subproblems by treating the nonlinear terms in the explicit and semi-implicit schemes, and the computational size is reduced. Secondly, the unconditional stability of numerical scheme is provided by choosing different test functions and using the embedding theorem and the Cauchy inequalities. Thirdly, the optimal and -norms error estimates of numerical solutions are obtained based on the Ritz quasi-projection and Stokes projection. Finally, several numerical results are given to verify the established theoretical findings and show the performance of the considered numerical scheme.
{"title":"Optimal L2 error estimates of the decoupled, mass and charge-conservative mixed FEM for the two-phase inductionless MHD model","authors":"Mengdi Du, Qinzheng Xu, Zhengkang He, Tong Zhang","doi":"10.1016/j.rinam.2025.100662","DOIUrl":"10.1016/j.rinam.2025.100662","url":null,"abstract":"<div><div>This paper considers the optimal <span><math><msup><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>-norm error estimates of numerical solutions in a decoupled, mass and charge-conservative mixed finite element method (FEM) for the two-phase inductionless MHD model, which consists of the incompressible inductionless MHD (iMHD) problem and the Cahn–Hilliard equations. Firstly, the targeted problem is split into three linear subproblems by treating the nonlinear terms in the explicit and semi-implicit schemes, and the computational size is reduced. Secondly, the unconditional stability of numerical scheme is provided by choosing different test functions and using the embedding theorem and the Cauchy inequalities. Thirdly, the optimal <span><math><msup><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> and <span><math><msup><mrow><mi>H</mi></mrow><mrow><mn>1</mn></mrow></msup></math></span>-norms error estimates of numerical solutions are obtained based on the Ritz quasi-projection and Stokes projection. Finally, several numerical results are given to verify the established theoretical findings and show the performance of the considered numerical scheme.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100662"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145417118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.rinam.2025.100669
Shaher Momani , Iqbal M. Batiha , Issam Bendib , Adel Ouannas , Radwan M. Batyha
This study explores finite-time synchronization (FTS) in a discrete FitzHugh–Nagumo (FHN) reaction–diffusion system. Employing Lyapunov-based techniques and numerical simulations, we establish theoretical criteria to achieve synchronization within a finite duration. The proposed methodology involves discretization of the continuous FHN model using finite difference schemes to reformulate it into a computationally feasible framework. A tailored control strategy is introduced, ensuring rapid convergence to synchronization. Numerical results validate the theoretical framework, highlighting the critical roles of diffusion coefficients, system parameters, and control gains in shaping the spatiotemporal dynamics. The findings underscore the effectiveness of the proposed approach in applications such as neuronal network synchronization, chemical kinetics, and biological pattern formation. This study provides a robust theoretical and computational foundation for advancing FTS in reaction–diffusion systems, with practical implications across diverse scientific domains.
{"title":"Stability and finite-time synchronization of discrete FitzHugh–Nagumo systems using Lyapunov theory","authors":"Shaher Momani , Iqbal M. Batiha , Issam Bendib , Adel Ouannas , Radwan M. Batyha","doi":"10.1016/j.rinam.2025.100669","DOIUrl":"10.1016/j.rinam.2025.100669","url":null,"abstract":"<div><div>This study explores finite-time synchronization (FTS) in a discrete FitzHugh–Nagumo (FHN) reaction–diffusion system. Employing Lyapunov-based techniques and numerical simulations, we establish theoretical criteria to achieve synchronization within a finite duration. The proposed methodology involves discretization of the continuous FHN model using finite difference schemes to reformulate it into a computationally feasible framework. A tailored control strategy is introduced, ensuring rapid convergence to synchronization. Numerical results validate the theoretical framework, highlighting the critical roles of diffusion coefficients, system parameters, and control gains in shaping the spatiotemporal dynamics. The findings underscore the effectiveness of the proposed approach in applications such as neuronal network synchronization, chemical kinetics, and biological pattern formation. This study provides a robust theoretical and computational foundation for advancing FTS in reaction–diffusion systems, with practical implications across diverse scientific domains.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100669"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.rinam.2025.100660
Marcos A. Hernández-Ortega , C.M. Rergis , A. Román-Messina , Erlan R. Murillo-Aguirre
Carleman linearization is a mathematical technique that transforms nonlinear dynamical systems into infinite-dimensional linear systems, enabling simplified analysis. Initially developed for ordinary differential equations (ODEs) and later extended to partial differential equations (PDEs), it has found applications in control theory, biological systems, fluid dynamics, quantum mechanics, finance, and machine learning. This paper extends Carleman linearization to differential-algebraic equation (DAE) systems by introducing auxiliary functions and projecting the resulting system onto a higher-order ODE representation. Theoretical foundations are presented along with conditions under which the transformation is valid. The method is demonstrated on synthetic DAE examples, highlighting its effectiveness even when projection from algebraic variables to state variables is nontrivial or undefined.
{"title":"Carleman linearization of differential-algebraic equations systems","authors":"Marcos A. Hernández-Ortega , C.M. Rergis , A. Román-Messina , Erlan R. Murillo-Aguirre","doi":"10.1016/j.rinam.2025.100660","DOIUrl":"10.1016/j.rinam.2025.100660","url":null,"abstract":"<div><div>Carleman linearization is a mathematical technique that transforms nonlinear dynamical systems into infinite-dimensional linear systems, enabling simplified analysis. Initially developed for ordinary differential equations (ODEs) and later extended to partial differential equations (PDEs), it has found applications in control theory, biological systems, fluid dynamics, quantum mechanics, finance, and machine learning. This paper extends Carleman linearization to differential-algebraic equation (DAE) systems by introducing auxiliary functions and projecting the resulting system onto a higher-order ODE representation. Theoretical foundations are presented along with conditions under which the transformation is valid. The method is demonstrated on synthetic DAE examples, highlighting its effectiveness even when projection from algebraic variables to state variables is nontrivial or undefined.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100660"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145417119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.rinam.2025.100668
Yafeng Li
In this paper, we investigate a coupled hyperbolic-elliptic chemotaxis system posed on a network under nonhomogeneous boundary conditions. First, the boundary data are homogenized via a linear transformation. We then establish the local existence and uniqueness of solutions by combining analytic semigroup theory with the Lax–Milgram theorem. Finally, using sharp -estimates and Gronwall’s inequality, we show that sufficiently small initial data and boundary values lead to the existence of a unique nonnegative global solution.
{"title":"Global existence of solutions to a hyperbolic-elliptic chemotaxis model on networks with nonhomogeneous boundary conditions","authors":"Yafeng Li","doi":"10.1016/j.rinam.2025.100668","DOIUrl":"10.1016/j.rinam.2025.100668","url":null,"abstract":"<div><div>In this paper, we investigate a coupled hyperbolic-elliptic chemotaxis system posed on a network under nonhomogeneous boundary conditions. First, the boundary data are homogenized via a linear transformation. We then establish the local existence and uniqueness of solutions by combining analytic semigroup theory with the Lax–Milgram theorem. Finally, using sharp <span><math><msup><mrow><mi>L</mi></mrow><mrow><mi>p</mi></mrow></msup></math></span>-estimates and Gronwall’s inequality, we show that sufficiently small initial data and boundary values lead to the existence of a unique nonnegative global solution.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100668"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.rinam.2025.100658
K.O. Okorie , C. Izuchukwu , C.C. Okeke , K.C. Ukandu , M. Aphane
We introduce an inertial forward-reflected-backward method for solving the bilevel variational inequality problem. Our method involves a single projection onto the feasible set and one functional evaluation, which makes it cost-effective and efficient. The inertial technique in our algorithm improves its speed of convergence, and hence our algorithm performs faster than methods without inertial effect. Under moderate conditions, we obtain strong convergence of our algorithm. Lastly, we highlight the superior performance of our algorithm in comparison with other algorithms in the literature through our numerical experiments.
{"title":"Inertial forward-reflected-backward method for solving bilevel variational inequality problem","authors":"K.O. Okorie , C. Izuchukwu , C.C. Okeke , K.C. Ukandu , M. Aphane","doi":"10.1016/j.rinam.2025.100658","DOIUrl":"10.1016/j.rinam.2025.100658","url":null,"abstract":"<div><div>We introduce an inertial forward-reflected-backward method for solving the bilevel variational inequality problem. Our method involves a single projection onto the feasible set and one functional evaluation, which makes it cost-effective and efficient. The inertial technique in our algorithm improves its speed of convergence, and hence our algorithm performs faster than methods without inertial effect. Under moderate conditions, we obtain strong convergence of our algorithm. Lastly, we highlight the superior performance of our algorithm in comparison with other algorithms in the literature through our numerical experiments.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100658"},"PeriodicalIF":1.3,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-23DOI: 10.1016/j.rinam.2025.100659
Saman Bagherbana, Jafar Biazar, Hossein Aminikhah
We present a reliable numerical method for solving multidimensional partial Volterra integro-differential equations (PVIDEs). This comprehensive approach integrates techniques from product integration, the Nyström method, and spectral collocation, all founded on ultraspherical polynomials. The primary objective of our methodology is to employ variable and function transformations to reformulate the equations into a novel class of PVIDEs. Subsequently, the ultraspherical product integration-spectral collocation approach is applied to derive equivalent algebraic equations. Newton’s iterative method is then utilized to simultaneously compute the numerical solution and the first-order partial derivative. We rigorously analyze the error bounds of the proposed method in both - and -norms. Our results demonstrate that the errors in the numerical solution, as well as in the numerical first-order partial derivative, decay exponentially. Numerical examples are provided to validate reliability and efficiency of the ultraspherical product integration-spectral collocation approach.
{"title":"An ultraspherical product integration-spectral collocation method for multidimensional partial Volterra integro-differential equations and its convergence analysis","authors":"Saman Bagherbana, Jafar Biazar, Hossein Aminikhah","doi":"10.1016/j.rinam.2025.100659","DOIUrl":"10.1016/j.rinam.2025.100659","url":null,"abstract":"<div><div>We present a reliable numerical method for solving multidimensional partial Volterra integro-differential equations (PVIDEs). This comprehensive approach integrates techniques from product integration, the Nyström method, and spectral collocation, all founded on ultraspherical polynomials. The primary objective of our methodology is to employ variable and function transformations to reformulate the equations into a novel class of PVIDEs. Subsequently, the ultraspherical product integration-spectral collocation approach is applied to derive equivalent algebraic equations. Newton’s iterative method is then utilized to simultaneously compute the numerical solution and the first-order partial derivative. We rigorously analyze the error bounds of the proposed method in both <span><math><msup><mrow><mi>L</mi></mrow><mrow><mi>∞</mi></mrow></msup></math></span>- and <span><math><msup><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>-norms. Our results demonstrate that the errors in the numerical solution, as well as in the numerical first-order partial derivative, decay exponentially. Numerical examples are provided to validate reliability and efficiency of the ultraspherical product integration-spectral collocation approach.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100659"},"PeriodicalIF":1.3,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145363082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the valuation of commodity options within the context of a Wishart stochastic volatility model that is equipped with a jump process. To achieve this, we propose a semi-analytical solution for pricing European options on commodity futures by introducing the characteristic function of the proposed model. The unique challenges posed by this model underscore the necessity for effective calibration techniques. To address this, we utilize an Artificial Neural Network (ANN) designed to improve the precision and efficiency of the calibration process. To optimize the presented ANN model, we use the flower pollination (FP) algorithm. Empirical studies suggest that the Wishart stochastic volatility model incorporating a jump factor enhances calibration accuracy compared to common models in the literature. Moreover, applying the FP-optimized ANN to calibration leads to a marked improvement in accuracy, as demonstrated by both in-sample and out-of-sample data.
{"title":"Commodity options pricing under Wishart stochastic volatility model equipped with jump process: Model calibration by an optimized neural network","authors":"Abdelouahed Hamdi , Maryam Noorani , Farshid Mehrdoust","doi":"10.1016/j.rinam.2025.100661","DOIUrl":"10.1016/j.rinam.2025.100661","url":null,"abstract":"<div><div>This paper presents the valuation of commodity options within the context of a Wishart stochastic volatility model that is equipped with a jump process. To achieve this, we propose a semi-analytical solution for pricing European options on commodity futures by introducing the characteristic function of the proposed model. The unique challenges posed by this model underscore the necessity for effective calibration techniques. To address this, we utilize an Artificial Neural Network (ANN) designed to improve the precision and efficiency of the calibration process. To optimize the presented ANN model, we use the flower pollination (FP) algorithm. Empirical studies suggest that the Wishart stochastic volatility model incorporating a jump factor enhances calibration accuracy compared to common models in the literature. Moreover, applying the FP-optimized ANN to calibration leads to a marked improvement in accuracy, as demonstrated by both in-sample and out-of-sample data.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"28 ","pages":"Article 100661"},"PeriodicalIF":1.3,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145363609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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