An integrated GIS and knowledge-based system as an aid for the geological analysis of sedimentary basins

Abstract

The methods and advantages of integrating knowledge-based and geographical information system techniques for the analysis of provenance and diagenesis in sedimentary basins are demonstrated by examples from the Cheshire Basin located in north-west England. Approximate reasoning techniques to handle the vagueness and uncertainty inherent in a large amount of geological data, knowledge and reasoning are reviewed with particular emphasis on provenance analysis using subjective probability theory, Dempster-Shafer theory and fuzzy logic techniques. Object-oriented methods for analysing diagenetic history in user speci® ed volumes of the basin are discussed.

Neurofuzzy Modeling of Context–Contingent Proximity Relations

“…Examples of the use of ANN include knowledge discovery and data mining (e.g., Fischer and Abrahart 2000;Miller and Han 2001), remote-sensing data processing (e.g., Fiset et al 1998), simulation (e.g., Lloyd 1994Li and Yeh 2002), and spatial analysis and problem solving (e.g., Kathmann 1993;Thill and Mozolin 2000). Fuzzy set theory has been applied to various areas of GIScience including spatial analysis (e.g., Davis and Keller 1997;Ferrier and Wadge 1997), modeling spatial relations (Worboys 2001;Guesgen 2002a, b), spatial cognition and knowledge representation (Thill and Sui 1993;Brown, Groves, and Gedeon 2003), and others. More recently, it has been suggested that fuzzy set theory and the principles of neurocomputing can advantageously be brought together for geospatial modeling.…”