This paper presents a new systematic adaptive fuzzy neural network for inverse modelling of robot manipulators. An inductive learning algorithm is applied to generate the required inverse modelling rules from the robot’s input/output records. A full differentiable fuzzy neural network is developed to construct the inverse models of the robot manipulator, while any adaptation technique, such as ...

Procedural tree models have been popular in computer graphics for their ability to generate a variety of output trees from a set of input parameters and to simulate plant interaction with the environment for a realistic placement of trees in virtual scenes. However, defining such models and their parameters is a difficult task. We propose an inverse modelling approach for stochastic trees that ...

We address function misspecification and model heterogeneity, two critical issues in empirical work. A nonparametric approach is proposed for single-index, binary-choice models when parametric models such as Probit and Logit are potentially misspecified. The new approach involves two steps: first, we estimate index coefficients using sliced inverse regression without knowing the conditional pro...

In many countries emissions of particulate matter from urban sources, such as traffic and domestic wood burning, can lead to high episodic concentrations. Though it is important for air quality management and exposure studies to understand the individual source contributions to these concentrations, the complexity of the urban environment does not always allow a clear separation of sources when...