Buscar recursos académicos

The paper presents a formal model for a knowledge repository shared by members of a Virtual Community of Practice (VCPs), describes how the repository can be used to underpin collaborative problem solving, and how to bui...

"Owing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and pro...

"The placement of obstacles in front of doors is believed to be an effective strategy to increase the flow of pedestrians, hence improving the evacuation process. Since it was first suggested, this counterintuitive featu...

This paper presents a hybrid method to solve hard multiobjective problems. The proposed approach adopts an epsilon-constraint method which uses a Particle Swarm Optimizer to get points near of the true Pareto front. In t...

In this paper, we present a new model of an artificial immune system (AIS), based on the process that suffers the T-Cell, it is called T-Cell Model. It is used for solving constrained (numerical) optimization problems. T...

We consider the class of iterative shrinkage-thresholding algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods, which can be viewed as an extension of the classi...

Abstract Assuming that numerical scores are available for the performance of each of n persons on each of n jobs, the “assignment problem” is the quest for an assignment of persons to jobs so that the sum of the n sc...

Our interest is to define evolutionary algorithms to solve Constraint Satisfaction Problems (CSP), which indlude benefits of taditional resolution methods of CSPs as well as inherent characteristics of these kind of prob...

A method for accurate and efficient local density functional calculations (LDF) on molecules is described and presented with results. The method, Dmol for short, uses fast convergent three-dimensional numerical integrati...

We propose a new higher-dimensional mechanism for solving the hierarchy problem. The weak scale is generated from the Planck scale through an exponential hierarchy. However, this exponential arises not from gauge interac...

A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving. A number of "no free lunch" (NFL) theorems are presented which establish that for any algori...

In this Ph. D thesis, the main significant contributions are: formulation of a new non-linear membership function using fuzzy approach to capture and describe vagueness in the technological coefficients of constraints in...

From the Publisher: Using a practical approach, it discusses two-level factorial and fractional factorial designs, several aspects of empirical modeling with regression techniques, focusing on response surface methodolog...

Q-Learning is a Reinforcement Learning method for solving sequential decision problems, where the utility of actions depends on a sequence of decisions and there exists uncertainty about the dynamics of the environment t...

Evolving neural arrays (ENA) have proved to be capable of learning complex behaviors, i.e., problems whose solution requires strategy learning. For this reason, they present many applications in various areas such as rob...

Complex control tasks may be solved by dividing them into a more specific and more easily handled subtasks hierarchy. Several authors have demonstrated that the incremental layered evolution paradigm allows obtaining con...

The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software E...

The main objective of this paper centers on reviewing the evolution of Decision Support System´s (DSS) architectures, particularly as they apply to natural resources. Today it is difficult to conceive the existence of a...

We present a study of using fuzzy-based parameters for solving public bus routing problem where demand is uncertain. The fuzzy-based parameters are designed to provide data required by the route selection procedure. The ...

This work presents a traveltime inversion method that uses parametric functions to represent 2-D anomaly structures. These functions are described by a small set of unknown parameters which in turn are obtained after sol...

Scientists working with large volumes of high-dimensional data, such as global climate patterns, stellar spectra, or human gene distributions, regularly confront the problem of dimensionality reduction: finding meaningfu...

This tutorial provides an overview of the basic theory of hidden Markov models (HMMs) as originated by L.E. Baum and T. Petrie (1966) and gives practical details on methods of implementation of the theory along with a de...

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...

The main purpose of this project is to develop mathematical competences through interactive educational environments of multi-device access in the ninth grade students of the Institution Educativa Villa Estadio. The Mood...