Application of Fuzzy Lattice Neurocomputing (FLN) for Environmental Data Estimation

This paper addresses the problem of wind speed prediction at a particular location in the urban area of Thessaloniki, Greece, based on a data set containing wind parameter values at two other different locations. The problem is formulated and processed, and clusters in the data domain are identified by means of the Fuzzy Lattice Neurocomputing (FLN) methodology which can be used on any data set with the structure of a lattice. The results of the specific application are presented comparatively to past work, involving neural networks, on the same data set, demonstrating both the performance and the accuracy of the method.