This paper proposes a modified particle swarm optimization algorithm (MPSO) to design adaptive neuro-fuzzy controller parameters for controlling the behavior of non-linear dynamical systems. The modification of the proposed algorithm includes adding adaptive weights to the swarm optimization algorithm, which introduces a new update. The proposed MPSO algorithm uses a minimum velocity threshold ...

Autonomous navigation of mobile robots is a fruitful research area because the diversity methods adopted by artificial intelligence. Recently, several works have generally surveyed to solve path-planning problem robots. But in this paper, we focus on that combine neuro-fuzzy techniques reactive previously unknown environment. Based information sensed locally an onboard system, these aim design ...

Linear regression is a very simple regression model, However, the linear relation made by it is not realistic in many data mining application domains. Locally weighted linear regression and Model trees both combine locally learning and linear regression to imoprove linear regression. Our previous work called instance weighted linear regression is designed to improve the accuracy of linear regre...

We introduce the Locally Linear Latent Variable Model (LL-LVM), a probabilistic model for non-linear manifold discovery that describes a joint distribution over observations, their manifold coordinates and locally linear maps conditioned on a set of neighbourhood relationships. The model allows straightforward variational optimisation of the posterior distribution on coordinates and locally lin...

We introduce the Locally Linear Latent Variable Model (LL-LVM), a probabilistic model for non-linear manifold discovery that describes a joint distribution over observations, their manifold coordinates and locally linear maps conditioned on a set of neighbourhood relationships. The model allows straightforward variational optimisation of the posterior distribution on coordinates and locally lin...