A Learning Algorithm for Applying
نویسندگان
چکیده
In this paper we extend the models discussed by Cohen (1992) by introducing an input term. This allows the resulting models to be utilized for system identiication tasks. We prove that this model is stable in the sense that a bounded input leads to a bounded state when a minor restriction is imposed on the Lyapunov function. By employing this stability result, we are able to nd a learning algorithm which guarantees convergence to a set of parameters for which the error between the model trajectories and the desired trajectories vanishes.
منابع مشابه
Evaluating project’s completion time with Q-learning
Nowadays project management is a key component in introductory operations management. The educators and the researchers in these areas advocate representing a project as a network and applying the solution approaches for network models to them to assist project managers to monitor their completion. In this paper, we evaluated project’s completion time utilizing the Q-learning algorithm. So the ...
متن کاملEvaluating project’s completion time with Q-learning
Nowadays project management is a key component in introductory operations management. The educators and the researchers in these areas advocate representing a project as a network and applying the solution approaches for network models to them to assist project managers to monitor their completion. In this paper, we evaluated project’s completion time utilizing the Q-learning algorithm. So the ...
متن کاملEnhanced Comprehensive Learning Cooperative Particle Swarm Optimization with Fuzzy Inertia Weight (ECLCFPSO-IW)
So far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is Particle Swarm Optimization (PSO). Prior some efforts by applying fuzzy logic for improving defects of PSO such as trapping in local optimums and early convergence has been done. Moreover to overcome the problem of i...
متن کاملتأثیر یادگیری مبتنی بر الگوریتم بر تصمیمگیری بالینی دانشجویان فوریتهای پزشکی
Introduction: Improvement of students’ clinical decision making is one of the main challenges in medical education. There are numerous ways to improve these skills. The aim of this study was to examine the effect of algorithm-based learning on clinical decision making abilities of medical emergency students. Method: in this experimental study, twenty five medical emergency students were rand...
متن کاملCreating Algorithmic Symbols to Enhance Learning English Grammar
This paper introduces a set of English grammar symbols that the author has developed to enhance students’ understanding and consequently, application of the English grammar rules. A pretest-posttest control-group design was carried out in which the samples were students in two girls’ senior high schools (N=135, P ≤ 0.05) divided into two groups: the Treatment which received gramm...
متن کاملForecasting GDP Growth Using ANN Model with Genetic Algorithm
Applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. Artificial Neural Networks (ANN) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. Most ANN models applied in Economics use the gradient descent method as their learning algorithm. However, t...
متن کامل