24 papers · ranked by Valyu relevance
Luiza Guimarães Fabreti, Sebastian Höhna
Posterior distributions are commonly approximated by samples produced from a Markov chain Monte Carlo (MCMC) simulation. Every MCMC simulation has to be checked for convergence, i.e., that sufficiently many samples have been obtained and that these samples indeed represent the true posterior distribution. Here we…
Tianxiang Liu, Bruno F. Lourenço
We introduce the notion of consistent error bound functions which provides a unifying framework for error bounds for multiple convex sets. This framework goes beyond the classical Lipschitzian and H¨olderian error bounds and includes logarithmic and entropic error bounds found in the exponential cone. It also includes…
Yuhuan Wu, Haisong Wang, Daqun Guo, Yan Li + 3 more
'Tianyuan Shan' 'Tianlong You'] The rapid development of e-commerce has become a key driver of economic transformation and regional development in China. However, significant spatial and temporal disparities persist across regions. Understanding these disparities is essential for promoting balanced growth and…
Rihab Lakbichi, Farouq Zitouni, Saad Harous, Aridj Ferhat + 5 more
In recent years, opposition-based learning (OBL) has emerged as a powerful enhancement strategy in metaheuristic algorithms (MAs), gaining significant attention for its potential to accelerate convergence and improve solution quality. Existing research lacks a structured analysis of how different OBL variants influence…
Jai Rajyaguru, Mario E. Villanueva, Boris Houska, Benoît Chachuat
This article presents an arithmetic for the computation of Chebyshev models for factorable functions and an analysis of their convergence properties. Similar to Taylor models, Chebyshev models consist of a pair of a multivariate polynomial approximating the factorable function and an interval remainder term bounding…
Bernd Bassimir, Alexander Raß, Rolf Wanka
Particle Swarm Optimization (PSO) is a meta-heuristic for continuous black-box optimization problems. In this paper we focus on the convergence of the particle swarm, i. e., the exploitation phase of the algorithm. We introduce a new convergence indicator that can be used to calculate whether the particles will finally…
Yi-Shuai Niu
In this paper, we propose a clean and general proof framework to establish the convergence analysis of the Difference-of-Convex (DC) programming algorithm (DCA) for both standard DC program and convex constrained DC program. We first discuss suitable assumptions for the well-definiteness of DCA. Then, we focus on the…
Dina Issakova
Sequence convergence is a type of convergent evolution that results in similarity between orthologous genetic sequences. However, this can be difficult to evaluate statistically given classical paradigms for convergent evolution, which rest on the assumption that convergent phenotypes are achieved by unrelated genetic…
Nasim Iranmanesh, Nik Ahmad Sufian Burhan
Financial convergence is a process for establishing a relationship among the financial markets of different countries; as a result of such process the rates of similar financial assets in different markets and countries become very close to each other. Some factors might create financial convergence. of which the trade…
Nasiru Salihu, Sulaiman M. Ibrahim, P. Kaelo, Issam A.R. Moghrabi + 2 more
'Elissa Nadia Madi' 'Mohamed Kamel Riahi'] The spectral conjugate gradient (SCG) technique is highly efficient in addressing large-scale unconstrained optimization challenges. This paper presents a structured SCG approach that combines the Quasi-Newton direction and an extended conjugacy condition. Drawing inspiration…
Lars Berling, Remco Bouckaert, Alex Gavryushkin
Assessing convergence of Markov chain Monte Carlo (MCMC) based analyses is crucial but challenging, especially so in high dimensional and complex spaces such as the space of phylogenetic trees (treespace). In practice, it is assumed that the target distribution is the unique stationary distribution of the MCMC and…
David M. Grossnickle, William H. Brightly, Lucas N. Weaver, Kathryn E. Stanchak + 5 more
Tests of phenotypic convergence can provide evidence of adaptive evolution, and the popularity of such studies has grown in recent years due to the development of novel, quantitative methods for identifying and/or measuring convergence. Two commonly used methods include (i) ‘distance-based’ methods that measure…
María José Presno, Manuel Landajo
This paper assesses the convergence of the EU-28 countries toward their common goal of 20% in the renewable energy share indicator by year 2020. The potential presence of clubs of convergence toward different steady-state equilibria is also analyzed from both the standpoints of global convergence to the 20% goal and…
Authors not listed
Accurate and efficient calculation of alchemical free energies is a critical challenge in computational chemistry, frequently hindered by the inherent limitations of conventional Thermodynamic Integration (TI) methods. These limitations include poor phasespace overlap between discrete alchemical states, inefficient…
Akanksha Saxena, J. P. Jaiswal, Kamal Raj Pardasani
In this article, the local convergence analysis of the multistep seventh order method is presented for solving nonlinear equations. The point worth noting in our paper is that our analysis requires a weak hypothesis where the Fr´echet derivative of the nonlinear operator satisfies the ψ-continuity condition and extends…
Martin J. Gander, Mario Ohlberger, Stephan Rave
The Parareal algorithm was invented in 2001 in order to parallelize the solution of evolution problems in the time direction. It is based on parallel fine time propagators called F and sequential coarse time propagators called G, which alternatingly solve the evolution problem and iteratively converge to the fine…
Akanksha Saxena, J. P. Jaiswal, Kamal Raj PARADASANİ
In this paper, the local convergence analysis of the multistep seventh order method is presented for solving nonlinear equations assuming that the first-order Fr´echet derivative belongs to the Lipschitz class. The significance of our work is that it avoids the standard practice of Taylor expansion thereby, extends the…
Satoru Suzuki, Marcia Grabowecky, Melisa Menceloglu
Peak alpha frequencies vary along the anterior-posterior axis, but they also dynamically converge. We investigated such spontaneous anterior-posterior oscillation-frequency convergences by tracking oscillatory EEG activity in an extended alpha range (5-15 Hz) with appropriate temporal (∼370 ms) and spectral (∼1 Hz)…
Michael P. Speed, Kevin Arbuckle
While much of evolutionary biology attempts to explain the processes of diversification, there is an important place for the study of phenotypic similarity across life forms. When similar phenotypes evolve independently in different lineages this is referred to as convergent evolution. Although long recognised…
Authors not listed
Polymer electrolytes may play a crucial role in the development of safe, efficient energy-dense batteries thanks to their unique ability to facilitate ion transport while maintaining structural stability. However, experimental discovery is limited by the complexity of synthesizing and testing new monomer and polymer…
Authors not listed
Moving bed reactors (MBRs) are widely used in various industrial processes, making the development of mathematical models crucial for their design, optimization, and control. This study presents a semi-analytical solution (SAS) for a lumped parameter kinetic and heat transfer model of a tubular MBR, where a first-order…
Authors not listed
Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture…
Michael Hutcheon, Andrew Teale
Algorithms are presented for performing a topological analysis of an arbitrary function, evaluated on an arbitrary grid of points. These algorithms work strictly by post-processing the data and require no additional function evaluations. This is achieved by connecting the grid points with a neighbourhood graph…
Sudarshan Vijay, Hendrik Heenen, Aayush Singh, Karen Chan + 1 more
Kinetic models parameterised by ab-initio calculations have led to significant improvements in understanding chemical reactions in heterogeneous catalysis. These studies have been facilitated by implementations which determine steady-state coverages and rates of mean-field micro-kinetic models. As implemented in the…