All a b c d e f g h i j k l m n o p q r s t u v w x y z Other

Previous Page 28 Next

Displaying 541 – 560 of 891

Showing per page

Active fault diagnosis based on stochastic tests

Niels K. Poulsen, Henrik Niemann (2008)

International Journal of Applied Mathematics and Computer Science

The focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow us to obtain a fast change detection/isolation by considering the output or an error output from the system. The classical cumulative sum (CUSUM) test will be modified with respect to the AFD approach applied. The CUSUM method will be altered such that it will be able to detect a change...

Acyclic orientations with path constraints

Rosa M. V. Figueiredo, Valmir C. Barbosa, Nelson Maculan, Cid C. de Souza (2008)

RAIRO - Operations Research - Recherche Opérationnelle

Many well-known combinatorial optimization problems can be stated over the set of acyclic orientations of an undirected graph. For example, acyclic orientations with certain diameter constraints are closely related to the optimal solutions of the vertex coloring and frequency assignment problems. In this paper we introduce a linear programming formulation of acyclic orientations with path constraints, and discuss its use in the solution of the vertex coloring problem and some versions of the frequency...

Acyclic Orientations with Path Constraints

Rosa M. V. Figueiredo, Valmir C. Barbosa, Nelson Maculan, Cid C. de Souza (2009)

RAIRO - Operations Research

Many well-known combinatorial optimization problems can be stated over the set of acyclic orientations of an undirected graph. For example, acyclic orientations with certain diameter constraints are closely related to the optimal solutions of the vertex coloring and frequency assignment problems. In this paper we introduce a linear programming formulation of acyclic orientations with path constraints, and discuss its use in the solution of the vertex coloring problem and some versions of the frequency...

Adaptive control for discrete-time Markov processes with unbounded costs: Discounted criterion

Evgueni I. Gordienko, J. Adolfo Minjárez-Sosa (1998)

Kybernetika

We study the adaptive control problem for discrete-time Markov control processes with Borel state and action spaces and possibly unbounded one-stage costs. The processes are given by recurrent equations x t + 1 = F ( x t , a t , ξ t ) , t = 0 , 1 , ... with i.i.d. ℜ k -valued random vectors ξ t whose density ρ is unknown. Assuming observability of ξ t we propose the procedure of statistical estimation of ρ that allows us to prove discounted asymptotic optimality of two types of adaptive policies used early for the processes with bounded costs.

Adaptive high gain observer extension and its application to bioprocess monitoring

Sergej Čelikovský, Jorge Antonio Torres-Muñoz, Alma Rosa Dominguez-Bocanegra (2018)

Kybernetika

The adaptive version of the high gain observer for the strictly triangular systems subjected to constant unknown disturbances is proposed here. The adaptive feature is necessary due to the fact that the unknown disturbance enters in a way that cannot be suppressed by the high gain technique. The developed observers are then applied to a culture of microorganism in a bioreactor, namely, to the model of the continuous culture of Spirulina maxima. It is a common practice that just the biomass (or substrate)...

Adaptive thresholding technique for solving optimization problems on attainable sets of (max, min)-linear systems

Mahmoud Gad (2018)

Kybernetika

This article develops a parametric method depend on threshold technique for solving some optimization problems on attainable sets of so called (max, min)-separable linear systems. The concept of attainable set for (max, min)-separable linear equation systems will be introduced. Properties of the attainable sets will be studied in detail. The (max, min) - separable linear equation systems, in which the function of unknown variable occur only on one side, will be consider. The main idea of the proposed...

Additivities in fuzzy coalition games with side-payments

Milan Mareš (1999)

Kybernetika

The fuzzy coalition game theory brings a more realistic tools for the mathematical modelling of the negotiation process and its results. In this paper we limit our attention to the fuzzy extension of the simple model of coalition games with side-payments, and in the frame of this model we study one of the elementary concepts of the coalition game theory, namely its “additivities”, i. e., superadditivity, subadditivity and additivity in the strict sense. In the deterministic game theory these additivites...

Adjustment of the scaling parameter of Dai-Kou type conjugate gradient methods with application to motion control

Mahbube Akbari, Saeed Nezhadhosein, Aghile Heydari (2024)

Applications of Mathematics

We introduce a new scaling parameter for the Dai-Kou family of conjugate gradient algorithms (2013), which is one of the most numerically efficient methods for unconstrained optimization. The suggested parameter is based on eigenvalue analysis of the search direction matrix and minimizing the measure function defined by Dennis and Wolkowicz (1993). The corresponding search direction of conjugate gradient method has the sufficient descent property and the extended conjugacy condition. The global...

Advanced approach for the public transportation regulation system based on cybercars

Asma Melki, Slim Hammadi, Yves Sallez, Thierry Berger, Christian Tahon (2010)

RAIRO - Operations Research

In the last decade, the authorities require the use of safe, comfortable vehicles to assure a door to door aspect with respect of environment in the urban context. In this paper, we propose an advanced approach of transport regulation where we integrate cybercars into a regulation process as an alternative in disruption cases. For that, we propose an ITS architecture including public transportation and cybercars into the same framework. We will show that collaboration between these two systems...

Advances in model-based fault diagnosis with evolutionary algorithms and neural networks

Marcin Witczak (2006)

International Journal of Applied Mathematics and Computer Science

Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, the classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as evolutionary algorithms and neural networks become more and more popular in industrial applications of fault diagnosis. The main objective of this paper is to present recent developments regarding the application of evolutionary algorithms and neural...

Currently displaying 541 – 560 of 891