Add to ORKGThis paper examines the application of stochastic search techniques for the solution of two typical problems in mod- elling nonlinear systems using a multi-modelling approach: interpolation function determination and linear model structure determination. Two candidate stochastic search techniques are employed, genetic algorithms and swarm intelligence, which show dierent advantages for each of the problems considered
The concept of partial evaluation of ¯tness functions, together with mechanisms manipulating the res...
The main objective of this paper is to investigate efficiency and correctness of different real-code...
Theoretical analyses of stochastic search algorithms, albeit few, have always existed since these al...
This paper examines the application of stochastic search techniques for the solution of two typical ...
Stochastic Diffusion Search, first incepted in 1989, belongs to the extended family of swarm intelli...
A modified versions of metaheuristic algorithms are presented to compare their performance in identi...
This study presents a new approach to solve multi-response simulation optimization problems. This ap...
The work presented here advances the technology to analyze experimental data and automatically hypot...
An exhaustive review on the use of structured stochastic search approaches towards system identifica...
This dissertation considers several common notions of complexity that arise in large-scale systems o...
We describe the performance of two population based search algorithms (genetic algorithms and partic...
During the last three decades there has been a growing interest in algorithms which rely on analogie...
Stochastic diffusion search (SDS) is a multi-agent global optimisation technique based on the behavi...
In Multi-objective Optimization many solutions have to be evaluated in order to provide the decision...
A new approach to dynamic systems modeling is given. Stochastic Cellular Automata SCA are used as t...
The concept of partial evaluation of ¯tness functions, together with mechanisms manipulating the res...
The main objective of this paper is to investigate efficiency and correctness of different real-code...
Theoretical analyses of stochastic search algorithms, albeit few, have always existed since these al...
This paper examines the application of stochastic search techniques for the solution of two typical ...
Stochastic Diffusion Search, first incepted in 1989, belongs to the extended family of swarm intelli...
A modified versions of metaheuristic algorithms are presented to compare their performance in identi...
This study presents a new approach to solve multi-response simulation optimization problems. This ap...
The work presented here advances the technology to analyze experimental data and automatically hypot...
An exhaustive review on the use of structured stochastic search approaches towards system identifica...
This dissertation considers several common notions of complexity that arise in large-scale systems o...
We describe the performance of two population based search algorithms (genetic algorithms and partic...
During the last three decades there has been a growing interest in algorithms which rely on analogie...
Stochastic diffusion search (SDS) is a multi-agent global optimisation technique based on the behavi...
In Multi-objective Optimization many solutions have to be evaluated in order to provide the decision...
A new approach to dynamic systems modeling is given. Stochastic Cellular Automata SCA are used as t...
The concept of partial evaluation of ¯tness functions, together with mechanisms manipulating the res...
The main objective of this paper is to investigate efficiency and correctness of different real-code...
Theoretical analyses of stochastic search algorithms, albeit few, have always existed since these al...