A Methodology for Neural Spatial Interaction Modeling

A Facet-Based Methodology for Geo-Spatial Modeling

Space, together with time, is one of the two fundamental dimensions of the universe of knowledge. Geo-spatial ontologies are essential for our shared understanding of the physical universe and to achieve semantic interoperability between people and between software agents. In this paper we propose a methodology and a minimal set of guiding principles, mainly inspired by the faceted approach, to...

Principles of Neural Spatial Interaction Modelling

The focus of this paper is on the neural network approach to modelling origin-destination flows across geographic space. The novelty about neural spatial interaction models lies in their ability to model non-linear processes between spatial flows and their determinants, with few – if any – a priori assumptions of the data generating process. The paper draws attention to models based on the theo...

From Conventional to Neural Spatial Interaction Modelling

SERIE RESEARCH mEmORIMDn A NEW METHODOLOGY FOR THE ANALYSIS OF DYNAMIC SPATIAL INTERACTION MODELS

A Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network

Abstract   Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...