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This paper presents an efficient method for solving fully fuzzy linear fractional programming (FFLFP) problems using pentagonal fuzzy numbers (PFNs) and the decomposition method. In real-world decision-making, uncertaint...

The study of inequalities in mathematics is fundamental for understanding areas such as analysis, probability theory, and optimization. Notable inequalities include Jensen's and Young's convolution inequalities. Jensen's...

Abstract Normally the physical dimensions of the taper transition that realizes the impedance matching between the impedance of the feeding line built in microstrip line technology and the impedance of the component buil...

Abstract Busyness is a pervasive feature of contemporary consumer life, yet its implications for choice remain underexplored. This paper investigates how consumers’ subjective appraisals of busyness shape preferences f...

Introduction We developed an innovative, active learning workshop to introduce foundations of point-of-care ultrasound (POCUS) physics and instrumentation. The workshop design aimed to reduce cognitive load and encourage...

The prediction and design of photonic features have traditionally been guided by theory-driven computational methods, spanning a wide range of direct solvers and optimization techniques. Motivated by enormous advances in...

The article is devoted to the problem of using the methods of statistical analysis in the financial management processes in the conditions of uncertainty. A review of theoretical studies showed that efficiency of decisio...

Abstract Regarding the lane keeping system, path tracking accuracy and lateral stability at high speeds need to be taken into account especially for commercial vehicles due to the characteristics of larger mass, longer w...

The agreement between theoretical and experimental vibrational circular dichroism curves of (4R,9R,10R)-(+)-african-l(5)-ene-2,6-dione (1) and (4R,9S,10R)-lippifoli-l(6)-en-5-one (2), isolated from the widely used plant ...

The purpose of the study is to explore the application of qualitative methods in evaluating business relocation management, particularly focusing on optimizing business models through a qualimetric approach. The methodol...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be...

The MATLAB toolbox YALMIP is introduced. It is described how YALMIP can be used to model and solve optimization problems typically occurring in systems and control theory. In this paper, free MATLAB toolbox YALMIP, devel...

The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm. Benchmark test...

One of the problems which has plagued those attempting to predict the behavior of capital markets is the absence of a body of positive microeconomic theory dealing with conditions of risk. Although many useful insights c...

Although the problem of determining the minimum cost path through a graph arises naturally in a number of interesting applications, there has been no underlying theory to guide the development of efficient search procedu...

A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n + 1) vertices of a general simplex, followed by the replacement of the vertex with the...

Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and sharing have been criticized mainly for: (1) their O(MN/sup 3/) computational complexity (where M is the number of objectives and N is th...

Materias / palabras clave: Model predictive control; Optimal control; Control theory (sociology); Stability (learning theory); Sequence (biology); Mathematical optimization; Horizon; Nonlinear system; Control (management); Time horizon; Mathematic...

The particle swarm is an algorithm for finding optimal regions of complex search spaces through the interaction of individuals in a population of particles. This paper analyzes a particle's trajectory as it moves in disc...

Previous article Next article An Algorithm for Least-Squares Estimation of Nonlinear ParametersDonald W. MarquardtDonald W. Marquardthttps://doi.org/10.1137/0111030PDFPDF PLUSBibTexSections ToolsAdd to favoritesExport Ci...

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version ...

This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal f/spl isin/C/sup N/ and a randomly chosen set of frequencies /spl Omega/. Is it possib...

Real-time object detection is one of the most important research topics in computer vision. As new approaches regarding architecture optimization and training optimization are continually being developed, we have found t...

Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a collection of training examples and learn th...