Modelling population flows using spatial interaction models

Modelling and Optimising Flows Using Parallel Spatial Interaction Models

The paper demonstrates some of the benefits that high performance computing has to offer geographers. It reports the results of porting and then using very large spatial interaction models on the Cray T3D parallel supercomputer in modelling and spatial optimisation applications that would otherwise have been judged computationally infeasible.

Modelling Models of Robot Navigation Using Formal Spatial Ontology

In this paper we apply a formal ontological framework in order to deconstruct two prominent approaches to navigation from cognitive robotics, the Spatial Semantic Hierarchy of Kuipers and the Route Graph of Krieg-Brückner, Werner and others. The ontological framework is based on our current work on ontology specification, where we are investigating Masolo et al.’s Descriptive Ontology for Lingu...

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

Spatial Interaction Modelling on theConnection Machine 200

Spatial interaction models are used to simulate interactions between residents in a given area and some facility. Principal factors innuencing the degree of interaction are the distance from a household to the facility, the size and type of population within the area, the attractiveness of the facility and the competition from other facilities in the area. The spatial interaction model discusse...