Results 11 to 20 of about 12,651,285 (254)

Modelling and solution methods for stochastic optimisation [PDF]

, 2011
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis we consider two research problems, namely, (i) language constructs for modelling stochastic programming (SP) problems and (ii) solution ...
Zverovich, Victor
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Multi-element stochastic reduced basis methods [PDF]

, 2007
This paper presents mutli-element Stochastic Reduced Basis Methods (ME-SRBMs) for solving linear stochastic partial differential equations. In ME-SRBMs, the domain of definition of the random inputs is decomposed into smaller subdomains or random ...
Surya Mohan, P., Andy J. Keane, Keane, Andy J., Prasanth B. Nair, P. Surya Mohan, Nair, Prasanth B.   +5 more
core   +1 more source

NeuralMinimizer: A Novel Method for Global Optimization

Information, 2023
The problem of finding the global minimum of multidimensional functions is often applied to a wide range of problems. An innovative method of finding the global minimum of multidimensional functions is presented here.
Ioannis G. Tsoulos, Alexandros Tzallas, Evangelos Karvounis, Dimitrios Tsalikakis   +3 more
doaj   +1 more source

Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method [PDF]

, 2014
BackgroundBiochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need ...
Barrio Solórzano, Manuel, Zygalakis, Konstantinos C., Kevin Burrage, Manuel Barrio, Zygalakis, Konstantinos C, Székely, Tamás, Burrage, Kevin, Barrio, Manuel, Szekely Jr, Tamas, Tamás Székely, Konstantinos C Zygalakis, Zygalakis, Konstantinos   +11 more
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Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 3

Proceedings, 2018
The design of energy-efficient electric motor is a complex problem since diverse requirements and competing goals have to be fulfilled simultaneously. Therefore, different approaches to the design optimization of electric motors have been developed, each
Johannes Schmelcher, Max Kleine Büning, Kai Kreisköther, Dieter Gerling, Achim Kampker   +4 more
doaj   +1 more source

Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 2

Proceedings, 2018
Designing energy-efficient electric motor is a task where multiple goals have to be achieved at once. To find the best design possible, different approaches have been developed.
Johannes Schmelcher, Max Kleine Büning, Kai Kreisköther, Dieter Gerling, Achim Kampker   +4 more
doaj   +1 more source

Uma abordagem simplificada do método Monte Carlo Quântico: da solução de integrais ao problema da distribuição eletrônica A simplified approach to the Quantum Monte Carlo method: from the solution of integrals to the electronic distribution problem

Química Nova, 2008
The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo ...
Wagner Fernando Delfino Angelotti, André Luiz da Fonseca, Guilherme Barreto Torres, Rogério Custodio   +3 more
doaj   +1 more source

An Intelligent Technique for Initial Distribution of Genetic Algorithms

Axioms, 2023
The need to find the global minimum in multivariable functions is a critical problem in many fields of science and technology. Effectively solving this problem requires the creation of initial solution estimates, which are subsequently used by the ...
Vasileios Charilogis, Ioannis G. Tsoulos, V. N. Stavrou   +2 more
doaj   +1 more source

A posteriori error estimation for stochastic static problems [PDF]

, 2014
To solve stochastic static field problems, a discretization by the Finite Element Method can be used. A system of equations is obtained with the unknowns (scalar potential at nodes for example) being random variables. To solve this stochastic system, the
MAC, Hung, CLENET, Stephane
core   +1 more source

Selecting Some Variables to Update-Based Algorithm for Solving Optimization Problems

Sensors, 2022
With the advancement of science and technology, new complex optimization problems have emerged, and the achievement of optimal solutions has become increasingly important.
Mohammad Dehghani, Pavel Trojovský
doaj   +1 more source